Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
스크립트에서 "bar"에 대해 찾기
Percentage price changeThis indicator marks bars whose values increase or decrease by an amount greater than or equal to the value of the specified parameter as a percentage. Bars that meet the condition are marked with labels, boxes and colors. In addition to the standard method of calculating the percentage change at the closing price of the current and previous bars, the indicator allows you to choose non-standard calculation methods (at the prices of opening and closing the current bar, as well as at the prices of the maximum at the minimum of the current bar). You can choose to display the percentage changes of individual bars as well as a series of bars. You can select the number of bars in a series of bars. You can also apply filters by the direction of the bars in the series or by the percentage of individual bars in the series.
It is important to remember that in version 5 of Pine Script™, the maximum possible number of labels and the maximum possible number of boxes cannot exceed 500!
There are several main parameters that can be changed in section PARAMETERS FOR CALCULATION:
1. 'Bars count' - The number of bars for which the percentage rise or fall is calculated.
2. ‘Percentage change’ - sets the price change as a percentage. Bars with a price range above or equal to the specified value will be marked on the chart.
3. ‘First and second points of calculation’ - the first and second points for calculating the percentage change. Here you can set several different values for the calculation:
- 'Cl.pr., Close' - Closing price of the previous bar and closing price of the current bar (or a series of bars) (these values are used for the standard calculation of the percentage change on the chart).
- 'Open, Close' - Opening and closing prices of the current bar (or a series of bars).
- 'High|Low' - Highest and lowest price of the current bar (or a series of bars).
- 'Cl.pr.|High|Low' - Highest or lowest price of the current bar (or a series of bars) (depending on whether the bar is going up or down) or closing price of the previous bar for first point (one of these values is automatically selected, which gives a larger result, depending on whether there is a gap between these values). Highest or lowest price of the current bar for second point.
In the LIMITS section, you can set the following parameters.
1. ‘Only for the last bar’ - If this option is selected, the indicator will be applied only for the last bar (or series of bars).
2. 'Only bars in one direction' - A condition that takes into account sequences from the selected number of bars going in only one direction. If at least one bar has a different direction from the other bars, then such a sequence will not be taken into account. This only works if the 'Bars count' is > 1.
3. "Cut off higher values" - This field cuts off higher values. Bars with a price range above or equal to the specified value will not be marked on the chart. This can be used in some cases to make the chart less loaded with data and more visual. Of course, you can also use this option however you want.
4. ‘Min percent in series of bars’ - If the value 'Number of bars' is > 1, then a series of bars is taken into account, in which the percentage change of individual bars is greater than or equal to the set value.
In the DATE RANGE section, you can set the limits of the time and date range in which the calculation will be performed. In some cases, this can be used in order not to exceed the limit on the number of labels or boxes, which cannot exceed 500. Of course, you can also use this option however you want. By default, the date range is unlimited.
'Timezone offset, hours' - It is used only for the correct display of the limits of the date range in the parameter table.
In the PRICE INCREASE LABELS and PRICE REDUCTION LABELS section, you can define the design of labels bars and boxes, such as colors, shapes, sizes, and location. You can set the colors of the bars separately on the Style tab. On the Style tab, you can also turn on/off the display of frames, labels and color markings of bars.
The PARAMETER TABLE section is designed to adjust the display of the table for a more visual display of the selected values of all parameters on the Arguments tab. Depending on which values have been set and which parameters have been enabled or disabled, the table will change its appearance, display or hide some rows. A single line 'Total found' will be displayed all the time. It shows the count of bars that meet the condition and count of labels or boxes used in the diagram. Since the bars are labeled with labels or boxes, their number cannot exceed 500 for Pine script version 5.
1. 'Pos.' - sets the main position of the table on the screen.
2. 'X off.', 'Y off.' - You can set the offset of the table along the X and Y axes. This option can be useful to avoid overlapping multiple tables if you want to use two or more instances of this indicator on your chart. The minimum value is -30, the maximum is 30. Positive values shift the table to the right on the X axis and up on the Y axis. Negative values shift the table to the left on the X axis and down on the Y axis.
3. 'Font color' - The font color in the table.
'Warn. font color', 'Warn. backgr. color' - The font and background colors in the 'Total found' row in the table. If the number of labels or boxes exceeds 500, the font and background will be colored in these colors.
4. ‘Font size’ – Sets the font size in the table.
5. 'Show hours and minutes in date/time range' - changes the date and time format of time range from {yyyy.MM.dd HH:mm} to {yyyy.MM.dd}.
6. 'View all params' - used to display all parameters, even those duplicated in the main line of the indicator.
7. ‘Title’ – If desired, you can make a header for the table.
The last row of the table shows the number of bars found that meet the conditions. Since these bars are marked with labels (in the case of one bar) or boxes (in the case of series of bars), the limit that can be marked on the chart is 500. Exceeding this value will be displayed in the table and additionally highlighted in red font. This will signal that not all bars found are displayed on the chart.
On the Style tab, you can turn the table display on/off.
Auto Volume Spread Analysis (VSA) [TANHEF]Auto Volume Spread Analysis (visible volume and spread bars auto-scaled): Understanding Market Intentions through the Interpretation of Volume and Price Movements.
All the sections below contain the same descriptions as my other indicator "Volume Spread Analysis" with the exception of 'Auto Scaling'.
█ Auto-Scaling
This indicator auto-scales spread bars to match the visible volume bars, unlike the previous "Volume Spread Analysis " version which limited the number of visible spread bars to a fixed count. The auto-scaling feature allows for easier navigation through historical data, enabling both more historical spread bars to be viewed and more historical VSA pattern labels being displayed without requiring using the bar replay tool. Please note that this indicator’s auto-scaling feature recalculates the visible bars on the chart, causing the indicator to reload whenever the chart is moved.
Auto-scaled spread bars have two display options (set via 'Spread Bars Method' setting):
Lines: a bar lookback limit of 500 bars.
Polylines: no bar lookback limit as only plotted on visible bars on chart, which uses multiple polylines are used.
█ Simple Explanation:
The Volume Spread Analysis (VSA) indicator is a comprehensive tool that helps traders identify key market patterns and trends based on volume and spread data. This indicator highlights significant VSA patterns and provides insights into market behavior through color-coded volume/spread bars and identification of bars indicating strength, weakness, and neutrality between buyers and sellers. It also includes powerful volume and spread forecasting capabilities.
█ Laws of Volume Spread Analysis (VSA):
The origin of VSA begins with Richard Wyckoff, a pivotal figure in its development. Wyckoff made significant contributions to trading theory, including the formulation of three basic laws:
The Law of Supply and Demand: This fundamental law states that supply and demand balance each other over time. High demand and low supply lead to rising prices until demand falls to a level where supply can meet it. Conversely, low demand and high supply cause prices to fall until demand increases enough to absorb the excess supply.
The Law of Cause and Effect: This law assumes that a 'cause' will result in an 'effect' proportional to the 'cause'. A strong 'cause' will lead to a strong trend (effect), while a weak 'cause' will lead to a weak trend.
The Law of Effort vs. Result: This law asserts that the result should reflect the effort exerted. In trading terms, a large volume should result in a significant price move (spread). If the spread is small, the volume should also be small. Any deviation from this pattern is considered an anomaly.
█ Volume and Spread Analysis Bars:
Display: Volume and spread bars that consist of color coded levels, with the spread bars scaled to match the volume bars. A displayable table (Legend) of bar colors and levels can give context and clarify to each volume/spread bar.
Calculation: Levels are calculated using multipliers applied to moving averages to represent key levels based on historical data: low, normal, high, ultra. This method smooths out short-term fluctuations and focuses on longer-term trends.
Low Level: Indicates reduced volatility and market interest.
Normal Level: Reflects typical market activity and volatility.
High Level: Indicates increased activity and volatility.
Ultra Level: Identifies extreme levels of activity and volatility.
This illustrates the appearance of Volume and Spread bars when scaled and plotted together:
█ Forecasting Capabilities:
Display: Forecasted volume and spread levels using predictive models.
Calculation: Volume and Spread prediction calculations differ as volume is linear and spread is non-linear.
Volume Forecast (Linear Forecasting): Predicts future volume based on current volume rate and bar time till close.
Spread Forecast (Non-Linear Dynamic Forecasting): Predicts future spread using a dynamic multiplier, less near midpoint (consolidation) and more near low or high (trending), reflecting non-linear expansion.
Moving Averages: In forecasting, moving averages utilize forecasted levels instead of actual levels to ensure the correct level is forecasted (low, normal, high, or ultra).
The following compares forecasted volume with actual resulting volume, highlighting the power of early identifying increased volume through forecasted levels:
█ VSA Patterns:
Criteria and descriptions for each VSA pattern are available as tooltips beside them within the indicator’s settings. These tooltips provide explanations of potential developments based on the volume and spread data.
Signs of Strength (🟢): Patterns indicating strong buying pressure and potential market upturns.
Down Thrust
Selling Climax
No Effort ➤ Bearish Result
Bearish Effort ➤ No Result
Inverse Down Thrust
Failed Selling Climax
Bull Outside Reversal
End of Falling Market (Bag Holder)
Pseudo Down Thrust
No Supply
Signs of Weakness (🔴): Patterns indicating strong selling pressure and potential market downturns.
Up Thrust
Buying Climax
No Effort ➤ Bullish Result
Bullish Effort ➤ No Result
Inverse Up Thrust
Failed Buying Climax
Bear Outside Reversal
End of Rising Market (Bag Seller)
Pseudo Up Thrust
No Demand
Neutral Patterns (🔵): Patterns indicating market indecision and potential for continuation or reversal.
Quiet Doji
Balanced Doji
Strong Doji
Quiet Spinning Top
Balanced Spinning Top
Strong Spinning Top
Quiet High Wave
Balanced High Wave
Strong High Wave
Consolidation
Bar Patterns (🟡): Common candlestick patterns that offer insights into market sentiment. These are required in some VSA patterns and can also be displayed independently.
Bull Pin Bar
Bear Pin Bar
Doji
Spinning Top
High Wave
Consolidation
This demonstrates the acronym and descriptive options for displaying bar patterns, with the ability to hover over text to reveal the descriptive text along with what type of pattern:
█ Alerts:
VSA Pattern Alerts: Notifications for identified VSA patterns at bar close.
Volume and Spread Alerts: Alerts for confirmed and forecasted volume/spread levels (Low, High, Ultra).
Forecasted Volume and Spread Alerts: Alerts for forecasted volume/spread levels (High, Ultra) include a minimum percent time elapsed input to reduce false early signals by ensuring sufficient bar time has passed.
█ Inputs and Settings:
Indicator Bar Color: Select color schemes for bars (Normal, Detail, Levels).
Indicator Moving Average Color: Select schemes for bars (Fill, Lines, None).
Price Bar Colors: Options to color price bars based on VSA patterns and volume levels.
Legend: Display a table of bar colors and levels for context and clarity of volume/spread bars.
Forecast: Configure forecast display and prediction details for volume and spread.
Average Multipliers: Define multipliers for different levels (Low, High, Ultra) to refine the analysis.
Moving Average: Set volume and spread moving average settings.
VSA: Select the VSA patterns to be calculated and displayed (Strength, Weakness, Neutral).
Bar Patterns: Criteria for bar patterns used in VSA (Doji, Bull Pin Bar, Bear Pin Bar, Spinning Top, Consolidation, High Wave).
Colors: Set exact colors used for indicator bars, indicator moving averages, and price bars.
More Display Options: Specify how VSA pattern text is displayed (Acronym, Descriptive), positioning, and sizes.
Alerts: Configure alerts for VSA patterns, volume, and spread levels, including forecasted levels.
█ Usage:
The Volume Spread Analysis indicator is a helpful tool for leveraging volume spread analysis to make informed trading decisions. It offers comprehensive visual and textual cues on the chart, making it easier to identify market conditions, potential reversals, and continuations. Whether analyzing historical data or forecasting future trends, this indicator provides insights into the underlying factors driving market movements.
CandleAnalysisLibrary "CandleAnalysis"
A collection of frequently used candle analysis functions in my scripts.
isBullish(barsBack)
Checks if a specific bar is bullish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bullish, otherwise returns false.
isBearish(barsBack)
Checks if a specific bar is bearish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bearish, otherwise returns false.
isBE(barsBack)
Checks if a specific bar is break even.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is break even, otherwise returns false.
getBodySize(barsBack, inPriceChg)
Calculates a specific candle's body size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the body size as a price change value. The default is false (in points).
Returns: The candle's body size in points.
getTopWickSize(barsBack, inPriceChg)
Calculates a specific candle's top wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's top wick size in points.
getBottomWickSize(barsBack, inPriceChg)
Calculates a specific candle's bottom wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's bottom wick size in points.
getBodyPercent(barsBack)
Calculates a specific candle's body size as a percentage of its entire size including its wicks.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: The candle's body size percentage.
isHammer(fib, bullish, barsBack)
Checks if a specific bar is a hammer candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bullish (bool) : (bool) True if the candle must to be green. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a hammer candle, otherwise returns false.
isShootingStar(fib, bearish, barsBack)
Checks if a specific bar is a shooting star candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bearish (bool) : (bool) True if the candle must to be red. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a shooting star candle, otherwise returns false.
isDoji(wickSize, bodySize, barsBack)
Checks if a specific bar is a doji candle based on a given wick and body size.
Parameters:
wickSize (float) : (float) The maximum top wick size compared to the bottom and vice versa. The default is 1.5.
bodySize (float) : (bool) The maximum body size as a percentage compared to the entire candle size. The default is 5.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a doji candle.
isBullishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bullish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum top wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bullish engulfing candle.
isBearishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bearish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum bottom wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bearish engulfing candle.
MarcosLibraryLibrary "MarcosLibrary"
A colection of frequently used functions in my scripts.
bullFibRet(priceLow, priceHigh, fibLevel)
Calculates a bullish fibonacci retracement value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given retracement level.
bearFibRet(priceLow, priceHigh, fibLevel)
Calculates a bearish fibonacci retracement value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given retracement level.
bullFibExt(priceLow, priceHigh, thirdPivot, fibLevel)
Calculates a bullish fibonacci extension value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
thirdPivot (float) : (float) The third price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given extension level.
bearFibExt(priceLow, priceHigh, thirdPivot, fibLevel)
Calculates a bearish fibonacci extension value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
thirdPivot (float) : (float) The third price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given extension level.
isBullish(barsBack)
Checks if a specific bar is bullish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bullish, otherwise returns false.
isBearish(barsBack)
Checks if a specific bar is bearish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bearish, otherwise returns false.
isBE(barsBack)
Checks if a specific bar is break even.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is break even, otherwise returns false.
getBodySize(barsBack, inPriceChg)
Calculates a specific candle's body size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the body size as a price change value. The default is false (in points).
Returns: The candle's body size in points.
getTopWickSize(barsBack, inPriceChg)
Calculates a specific candle's top wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's top wick size in points.
getBottomWickSize(barsBack, inPriceChg)
Calculates a specific candle's bottom wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's bottom wick size in points.
getBodyPercent(barsBack)
Calculates a specific candle's body size as a percentage of its entire size including its wicks.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: The candle's body size percentage.
isHammer(fib, bullish, barsBack)
Checks if a specific bar is a hammer candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bullish (bool) : (bool) True if the candle must to be green. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a hammer candle, otherwise returns false.
isShootingStar(fib, bearish, barsBack)
Checks if a specific bar is a shooting star candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bearish (bool) : (bool) True if the candle must to be red. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a shooting star candle, otherwise returns false.
isDoji(wickSize, bodySize, barsBack)
Checks if a specific bar is a doji candle based on a given wick and body size.
Parameters:
wickSize (float) : (float) The maximum top wick size compared to the bottom and vice versa. The default is 1.5.
bodySize (float) : (bool) The maximum body size as a percentage compared to the entire candle size. The default is 5.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a doji candle.
isBullishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bullish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum top wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bullish engulfing candle.
isBearishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bearish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum bottom wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bearish engulfing candle.
Higher-timeframe requests█ OVERVIEW
This publication focuses on enhancing awareness of the best practices for accessing higher-timeframe (HTF) data via the request.security() function. Some "traditional" approaches, such as what we explored in our previous `security()` revisited publication, have shown limitations in their ability to retrieve non-repainting HTF data. The fundamental technique outlined in this script is currently the most effective in preventing repainting when requesting data from a higher timeframe. For detailed information about why it works, see this section in the Pine Script™ User Manual .
█ CONCEPTS
Understanding repainting
Repainting is a behavior that occurs when a script's calculations or outputs behave differently after restarting it. There are several types of repainting behavior, not all of which are inherently useless or misleading. The most prevalent form of repainting occurs when a script's calculations or outputs exhibit different behaviors on historical and realtime bars.
When a script calculates across historical data, it only needs to execute once per bar, as those values are confirmed and not subject to change. After each historical execution, the script commits the states of its calculations for later access.
On a realtime, unconfirmed bar, values are fluid . They are subject to change on each new tick from the data provider until the bar closes. A script's code can execute on each tick in a realtime bar, meaning its calculations and outputs are subject to realtime fluctuations, just like the underlying data it uses. Each time a script executes on an unconfirmed bar, it first reverts applicable values to their last committed states, a process referred to as rollback . It only commits the new values from a realtime bar after the bar closes. See the User Manual's Execution model page to learn more.
In essence, a script can repaint when it calculates on realtime bars due to fluctuations before a bar's confirmation, which it cannot reproduce on historical data. A common strategy to avoid repainting when necessary involves forcing only confirmed values on realtime bars, which remain unchanged until each bar's conclusion.
Repainting in higher-timeframe (HTF) requests
When working with a script that retrieves data from higher timeframes with request.security() , it's crucial to understand the differences in how such requests behave on historical and realtime bars .
The request.security() function executes all code required by its `expression` argument using data from the specified context (symbol, timeframe, or modifiers) rather than on the chart's data. As when executing code in the chart's context, request.security() only returns new historical values when a bar closes in the requested context. However, the values it returns on realtime HTF bars can also update before confirmation, akin to the rollback and recalculation process that scripts perform in the chart's context on the open bar. Similar to how scripts operate in the chart's context, request.security() only confirms new values after a realtime bar closes in its specified context.
Once a script's execution cycle restarts, what were previously realtime bars become historical bars, meaning the request.security() call will only return confirmed values from the HTF on those bars. Therefore, if the requested data fluctuates across an open HTF bar, the script will repaint those values after it restarts.
This behavior is not a bug; it's simply the default behavior of request.security() . In some cases, having the latest information from an unconfirmed HTF bar is precisely what a script needs. However, in many other cases, traders will require confirmed, stable values that do not fluctuate across an open HTF bar. Below, we explain the most reliable approach to achieve such a result.
Achieving consistent timing on all bars
One can retrieve non-fluctuating values with consistent timing across historical and realtime feeds by exclusively using request.security() to fetch the data from confirmed HTF bars. The best way to achieve this result is offsetting the `expression` argument by at least one bar (e.g., `close [1 ]`) and using barmerge.lookahead_on as the `lookahead` argument.
We discourage the use of barmerge.lookahead_on alone since it prompts the function to look toward future values of HTF bars across historical data, which is heavily misleading. However, when paired with a requested `expression` that includes a one-bar historical offset, the "future" data the function retrieves is not from the future. Instead, it represents the last confirmed bar's values at the start of each HTF bar, thus preventing the results on realtime bars from fluctuating before confirmation from the timeframe.
For example, this line of code uses a request.security() call with barmerge.lookahead_on to request the close price from the "1D" timeframe, offset by one bar with the history-referencing operator [ ] . This line will return the daily price with consistent timing across all bars:
float htfClose = request.security(syminfo.tickerid, "1D", close , lookahead = barmerge.lookahead_on)
Note that:
• This technique only works as intended for higher-timeframe requests .
• When designing a script to work specifically with HTFs, we recommend including conditions to prevent request.security() from accessing timeframes equal to or lower than the chart's timeframe, especially if you intend to publish it. In this script, we included an if structure that raises a runtime error when the requested timeframe is too small.
• A necessary trade-off with this approach is that the script must wait for an HTF bar's confirmation to retrieve new data on realtime bars, thus delaying its availability until the open of the subsequent HTF bar. The time elapsed during such a delay varies with each market, but it's typically relatively small.
👉 Failing to offset the function's `expression` argument while using barmerge.lookahead_on will produce historical results with lookahead bias , as it will look to the future states of historical HTF bars, retrieving values before the times at which they're available in the feed. See the `lookahead` and Future leak with `request.security()` sections in the Pine Script™ User Manual for more information.
Evolving practices
The fundamental technique outlined in this publication is currently the only reliable approach to requesting non-repainting HTF data with request.security() . It is the superior approach because it avoids the pitfalls of other methods, such as the one introduced in the `security()` revisited publication. That publication proposed using a custom `f_security()` function, which applied offsets to the `expression` and the requested result based on historical and realtime bar states. At that time, we explored techniques that didn't carry the risk of lookahead bias if misused (i.e., removing the historical offset on the `expression` while using lookahead), as requests that look ahead to the future on historical bars exhibit dangerously misleading behavior.
Despite these efforts, we've unfortunately found that the bar state method employed by `f_security()` can produce inaccurate results with inconsistent timing in some scenarios, undermining its credibility as a universal non-repainting technique. As such, we've deprecated that approach, and the Pine Script™ User Manual no longer recommends it.
█ METHOD VARIANTS
In this script, all non-repainting requests employ the same underlying technique to avoid repainting. However, we've applied variants to cater to specific use cases, as outlined below:
Variant 1
Variant 1, which the script displays using a lime plot, demonstrates a non-repainting HTF request in its simplest form, aligning with the concept explained in the "Achieving consistent timing" section above. It uses barmerge.lookahead_on and offsets the `expression` argument in request.security() by one bar to retrieve the value from the last confirmed HTF bar. For detailed information about why this works, see the Avoiding Repainting section of the User Manual's Other timeframes and data page.
Variant 2
Variant 2 ( fuchsia ) introduces a custom function, `htfSecurity()`, which wraps the request.security() function to facilitate convenient repainting control. By specifying a value for its `repaint` parameter, users can determine whether to allow repainting HTF data. When the `repaint` value is `false`, the function applies lookahead and a one-bar offset to request the last confirmed value from the specified `timeframe`. When the value is `true`, the function requests the `expression` using the default behavior of request.security() , meaning the results can fluctuate across chart bars within realtime HTF bars and repaint when the script restarts.
Note that:
• This function exclusively handles HTF requests. If the requested timeframe is not higher than the chart's, it will raise a runtime error .
• We prefer this approach since it provides optional repainting control. Sometimes, a script's calculations need to respond immediately to realtime HTF changes, which `repaint = true` allows. In other cases, such as when issuing alerts, triggering strategy commands, and more, one will typically need stable values that do not repaint, in which case `repaint = false` will produce the desired behavior.
Variant 3
Variant 3 ( white ) builds upon the same fundamental non-repainting approach used by the first two. The difference in this variant is that it applies repainting control to tuples , which one cannot pass as the `expression` argument in our `htfSecurity()` function. Tuples are handy for consolidating `request.*()` calls when a script requires several values from the same context, as one can request a single tuple from the context rather than executing multiple separate request.security() calls.
This variant applies the internal logic of our `htfSecurity()` function in the script's global scope to request a tuple containing open and `srcInput` values from a higher timeframe with repainting control. Historically, Pine Script™ did not allow the history-referencing operator [ ] when requesting tuples unless the tuple came from a function call, which limited this technique. However, updates to Pine over time have lifted this restriction, allowing us to pass tuples with historical offsets directly as the `expression` in request.security() . By offsetting all items in a tuple `expression` by one bar and using barmerge.lookahead_on , we effectively retrieve a tuple of stable, non-repainting HTF values.
Since we cannot encapsulate this method within the `htfSecurity()` function and must execute the calculations in the global scope, the script's "Repainting" input directly controls the global `offset` and `lookahead` values to ensure it behaves as intended.
Variant 4 (Control)
Variant 4, which the script displays as a translucent orange plot, uses a default request.security() call, providing a reference point to compare the difference between a repainting request and the non-repainting variants outlined above. Whenever the script restarts its execution cycle, realtime bars become historical bars, and the request.security() call here will repaint the results on those bars.
█ Inputs
Repainting
The "Repainting" input (`repaintInput` variable) controls whether Variant 2 and Variant 3 are allowed to use fluctuating values from an unconfirmed HTF bar. If its value is `false` (default), these requests will only retrieve stable values from the last confirmed HTF bar.
Source
The "Source" input (`srcInput` variable) determines the series the script will use in the `expression` for all HTF data requests. Its default value is close .
HTF Selection
This script features two ways to specify the higher timeframe for all its data requests, which users can control with the "HTF Selection" input (`tfTypeInput` variable):
1) If its value is "Fixed TF", the script uses the timeframe value specified by the "Fixed Higher Timeframe" input (`fixedTfInput` variable). The script will raise a runtime error if the selected timeframe is not larger than the chart's.
2) If the input's value is "Multiple of chart TF", the script multiplies the value of the "Timeframe Multiple" input (`tfMultInput` variable) by the chart's timeframe.in_seconds() value, then converts the result to a valid timeframe string via timeframe.from_seconds() .
Timeframe Display
This script features the option to display an "information box", i.e., a single-cell table that shows the higher timeframe the script is currently using. Users can toggle the display and determine the table's size, location, and color scheme via the inputs in the "Timeframe Display" group.
█ Outputs
This script produces the following outputs:
• It plots the results from all four of the above variants for visual comparison.
• It highlights the chart's background gray whenever a new bar starts on the higher timeframe, signifying when confirmations occur in the requested context.
• To demarcate which bars the script considers historical or realtime bars, it plots squares with contrasting colors corresponding to bar states at the bottom of the chart pane.
• It displays the higher timeframe string in a single-cell table with a user-specified size, location, and color scheme.
Look first. Then leap.
LineWrapperLibrary "LineWrapper"
Wrapper Type for Line. Useful when you want to store the line details without drawing them. Can also be used in scnearios where you collect lines to be drawn and draw together towards the end.
draw(this)
draws line as per the wrapper object contents
Parameters:
this : (series Line) Line object.
Returns: current Line object
draw(this)
draws lines as per the wrapper object array
Parameters:
this : (series array) Array of Line object.
Returns: current Array of Line objects
update(this)
updates or redraws line as per the wrapper object contents
Parameters:
this : (series Line) Line object.
Returns: current Line object
update(this)
updates or redraws lines as per the wrapper object array
Parameters:
this : (series array) Array of Line object.
Returns: current Array of Line objects
get_price(this, bar)
get line price based on bar
Parameters:
this : (series Line) Line object.
bar : (series/int) bar at which line price need to be calculated
Returns: line price at given bar.
get_x1(this)
Returns UNIX time or bar index (depending on the last xloc value set) of the first point of the line.
Parameters:
this : (series Line) Line object.
Returns: UNIX timestamp (in milliseconds) or bar index.
get_x2(this)
Returns UNIX time or bar index (depending on the last xloc value set) of the second point of the line.
Parameters:
this : (series Line) Line object.
Returns: UNIX timestamp (in milliseconds) or bar index.
get_y1(this)
Returns price of the first point of the line.
Parameters:
this : (series Line) Line object.
Returns: Price value.
get_y2(this)
Returns price of the second point of the line.
Parameters:
this : (series Line) Line object.
Returns: Price value.
set_x1(this, x, draw, update)
Sets bar index or bar time (depending on the xloc) of the first point.
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_x2(this, x, draw, update)
Sets bar index or bar time (depending on the xloc) of the second point.
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_y1(this, y, draw, update)
Sets price of the first point
Parameters:
this : (series Line) Line object.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_y2(this, y, draw, update)
Sets price of the second point
Parameters:
this : (series Line) Line object.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_color(this, color, draw, update)
Sets the line color
Parameters:
this : (series Line) Line object.
color : (series color) New line color
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_extend(this, extend, draw, update)
Sets extending type of this line object. If extend=extend.none, draws segment starting at point (x1, y1) and ending at point (x2, y2). If extend is equal to extend.right or extend.left, draws a ray starting at point (x1, y1) or (x2, y2), respectively. If extend=extend.both, draws a straight line that goes through these points.
Parameters:
this : (series Line) Line object.
extend : (series string) New extending type.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_style(this, style, draw, update)
Sets the line style
Parameters:
this : (series Line) Line object.
style : (series string) New line style.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_width(this, width, draw, update)
Sets the line width.
Parameters:
this : (series Line) Line object.
width : (series int) New line width in pixels.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_xloc(this, x1, x2, xloc, draw, update)
Sets x-location and new bar index/time values.
Parameters:
this : (series Line) Line object.
x1 : (series int) Bar index or bar time of the first point.
x2 : (series int) Bar index or bar time of the second point.
xloc : (series string) New x-location value.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_xy1(this, x, y, draw, update)
Sets bar index/time and price of the first point.
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_xy2(this, x, y, draw, update)
Sets bar index/time and price of the second point
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
delete(this)
Deletes the underlying line drawing object
Parameters:
this : (series Line) Line object.
Returns: Current Line object
Line
Line Wrapper object
Fields:
x1 : (series int) Bar index (if xloc = xloc.bar_index) or bar UNIX time (if xloc = xloc.bar_time) of the first point of the line. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y1 : (series int/float) Price of the first point of the line.
x2 : (series int) Bar index (if xloc = xloc.bar_index) or bar UNIX time (if xloc = xloc.bar_time) of the second point of the line. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y2 : (series int/float) Price of the second point of the line.
xloc : (series string) See description of x1 argument. Possible values: xloc.bar_index and xloc.bar_time. Default is xloc.bar_index.
extend : (series string) If extend=extend.none, draws segment starting at point (x1, y1) and ending at point (x2, y2). If extend is equal to extend.right or extend.left, draws a ray starting at point (x1, y1) or (x2, y2), respectively. If extend=extend.both, draws a straight line that goes through these points. Default value is extend.none.
color : (series color) Line color.
style : (series string) Line style. Possible values: line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both.
width : (series int) Line width in pixels.
obj : line object
AdxlLibrary "Adxl"
Functions to calculate the Average Directional Index
getDirectionUp(bar, lookback)
Bar high changed from open for bar
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getDirectionDown(bar, lookback)
Bar low changed from open for bar
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getPositiveDirectionalMovement(bar, lookback)
Positive directional movement for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getNegativeDirectionalMovement(bar, lookback)
Negative directional movement for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getTrueRangeMovingAverage(bar, lookback)
True range moving average for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getDirectionUpIndex(bar, lookback)
Direction up index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getDirectionDownIndex(bar, lookback)
Direction down index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getTotalDirectionIndex(bar, lookback)
Total direction index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getAverageDirectionalIndex(bar, lookback)
Average Directional Index (ADX) for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
Delta Volume Candles [LucF]█ OVERVIEW
This indicator plots on-chart volume delta information using candles that can replace your normal candles, tops and bottoms appended to normal candles, optional MAs of those tops and bottoms levels, a divergence channel and a chart background. The indicator calculates volume delta using intrabar analysis, meaning that it uses the lower timeframe bars constituting each chart bar.
█ CONCEPTS
Volume Delta
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which considerably limits the historical depth of charts and the number of symbols for which tick data is available. Furthermore, historical tick data is not yet available on TradingView.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. It is currently the most precise method usable on TradingView charts. TradingView's Volume Profile built-in indicators use it, as do the CVD - Cumulative Volume Delta Candles and CVD - Cumulative Volume Delta (Chart) indicators published from the TradingView account . My Delta Volume Channels and Volume Delta Columns Pro indicators also use intrabar analysis. Other volume delta indicators such as my Realtime 5D Profile use realtime chart updates to calculate volume delta without intrabar analysis, but that type of indicator only works in real time; they cannot calculate on historical bars.
This is the logic I use to determine the polarity of intrabars, which determines the up or down slot where its volume is added:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar, and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added, and the down volumes subtracted. The resulting value is volume delta for that chart bar, which can be used as an estimate of the buying/selling pressure on an instrument. Not all markets have volume information. Without it, this indicator is useless.
Intrabar analysis
Intrabars are chart bars at a lower timeframe than the chart's. The timeframe used to access intrabars determines the number of intrabars accessible for each chart bar. On a 1H chart, each chart bar of an active market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour.
This indicator automatically calculates an appropriate lower timeframe using the chart's timeframe and the settings you use in the script's "Intrabars" section of the inputs. As it can access lower timeframes as small as seconds when available, the indicator can be used on charts at relatively small timeframes such as 1min, provided the market is active enough to produce bars at second timeframes.
The quantity of intrabars analyzed in each chart bar determines:
• The precision of calculations (more intrabars yield more precise results).
• The chart coverage of calculations (there is a 100K limit to the quantity of intrabars that can be analyzed on any chart,
so the more intrabars you analyze per chart bar, the less chart bars can be calculated by the indicator).
The information box displayed at the bottom right of the chart shows the lower timeframe used for intrabars, as well as the average number of intrabars detected for chart bars and statistics on chart coverage.
Balances
This indicator calculates five balances from volume delta values. The balances are oscillators with a zero centerline; positive values are bullish, and negative values are bearish. It is important to understand the balances as they can be used to:
• Color candle bodies.
• Calculate body and top and bottom divergences.
• Color an EMA channel.
• Color the chart's background.
• Configure markers and alerts.
The five balances are:
1 — Bar Balance : This is the only balance using instant values; it is simply the subtraction of the down volume from the up volume on the bar, so the instant volume delta for that bar.
2 — Average Balance : Calculates a distinct EMA for both the up and down volumes, and subtracts the down EMA from the up EMA.
The result is akin to MACD's histogram because it is the subtraction of two moving averages.
3 — Momentum Balance : Starts by calculating, separately for both up and down volumes, the difference between the same EMAs used in "Average Balance" and
an SMA of twice the period used for the "Average Balance" EMAs. The difference for the up side is subtracted from the difference for the down side,
and an RSI of that value is calculated and brought over the −50/+50 scale.
4 — Relative Balance : The reference values used in the calculation are the up and down EMAs used in the "Average Balance".
From those, we calculate two intermediate values using how much the instant up and down volumes on the bar exceed their respective EMA — but with a twist.
If the bar's up volume does not exceed the EMA of up volume, a zero value is used. The same goes for the down volume with the EMA of down volume.
Once we have our two intermediate values for the up and down volumes exceeding their respective MA, we subtract them. The final value is an ALMA of that subtraction.
The rationale behind using zero values when the bar's up/down volume does not exceed its EMA is to only take into account the more significant volume.
If both instant volume values exceed their MA, then the difference between the two is the signal's value.
The signal is called "relative" because the intermediate values are the difference between the instant up/down volumes and their respective MA.
This balance flatlines when the bar's up/down volumes do not exceed their EMAs, which makes it useful to spot areas where trader interest dwindles, such as consolidations.
The smaller the period of the final value's ALMA, the more easily it will flatline. These flat zones should be considered no-trade zones.
5 — Percent Balance : This balance is the ALMA of the ratio of the "Bar Balance" over the total volume for that bar.
From the balances and marker conditions, two more values are calculated:
1 — Marker Bias : This sums the up/down (+1/‒1) occurrences of the markers 1 to 4 over a period you define, so it ranges from −4 to +4, times the period.
Its calculation will depend on the modes used to calculate markers 3 and 4.
2 — Combined Balances : This is the sum of the bull/bear (+1/−1) states of each of the five balances, so it ranges from −5 to +5.
The periods for all of these balances can be configured in the "Periods" section at the bottom of the script's inputs. As you cannot see the balances on the chart, you can use my Volume Delta Columns Pro indicator in a pane; it can plot the same balances, so you will be able to analyze them.
Divergences
In the context of this indicator, a divergence is any bar where the bear/bull state of a balance (above/below its zero centerline) diverges from the polarity of a chart bar. No directional bias is assigned to divergences when they occur. Candle bodies and tops/bottoms can each be colored differently on divergences detected from distinct balances.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's open and close ) saved when divergences occur. When price (by default the close ) has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Prices breaches of the divergence channel will change its state. Divergence channels can be in one of three different states:
• Bull (green): Price has breached the channel to the upside.
• Bear (red): Price has breached the channel to the downside.
• Neutral (gray): The channel has not yet been breached.
█ HOW TO USE THE INDICATOR
I do not make videos to explain how to use my indicators. I do, however, try hard to include in their description everything one needs to understand what they do. From there, it's up to you to explore and figure out if they can be useful in your trading practice. Communicating in videos what this description and the script's tooltips contain would make for very long videos that would likely exceed the attention span of most people who find this description too long. There is no quick way to understand an indicator such as this one because it uses many different concepts and has quite a bit of settings one can use to modify its visuals and behavior — thus how one uses it. I will happily answer questions on the inner workings of the indicator, but I do not answer questions like "How do I trade using this indicator?" A useful answer to that question would require an in-depth analysis of who you are, your trading methodology and objectives, which I do not have time for. I do not teach trading.
Start by loading the indicator on an active chart containing volume information. See here if you need help.
The default configuration displays:
• Normal candles where the bodies are only colored if the bar's volume has increased since the last bar.
If you want to use this indicator's candles, you may want to disable your chart's candles by clicking the eye icon to the right of the symbol's name in the top left of the chart.
• A top or bottom appended to the normal candles. It represents the difference between up and down volume for that bar
and is positioned at the top or bottom, depending on its polarity. If up volume is greater than down volume, a top is displayed. If down volume is greater, a bottom is plotted.
The size of tops and bottoms is determined by calculating a factor which is the proportion of volume delta over the bar's total volume.
That factor is then used to calculate the top or bottom size relative to a baseline of the average candle body size of the last 100 bars.
• An information box in the bottom right displaying intrabar and chart coverage information.
• A light red background when the intrabar volume differs from the chart's volume by more than 1%.
The script's inputs contain tooltips explaining most of the fields. I will not repeat them here. Following is a brief description of each section of the indicator's inputs which will give you an idea of what the indicator can do:
Normal Candles is where you configure the replacement candles plotted by the script. You can choose from different coloring schemes for their bodies and specify a unique color for bodies where a divergence calculated using the method you choose occurs.
Volume Tops & Botttoms is where you configure the display of tops and bottoms, and their EMAs. The EMAs are calculated from the high point of tops and the low point of bottoms. They can act as a channel to evaluate price, and you can choose to color the channel using a gradient reflecting the advances/declines in the balance of your choice.
Divergence Channel is where you set up the appearance and behavior of the divergence channel. These areas represent levels where price and volume delta information do not converge. They can be interpreted as regions with no clear direction from where one will look for breaches. You can configure the channel to take into account one or both types of divergences you have configured for candle bodies and tops/bottoms.
Background allows you to configure a gradient background color that reflects the advances/declines in the balance of your choice. You can use this to provide context to the volume delta values from bars. You can also control the background color displayed on volume discrepancies between the intrabar and the chart's timeframe.
Intrabars is where you choose the calculation mode determining the lower timeframe used to access intrabars. The indicator uses the chart's timeframe and the type of market you are on to calculate the lower timeframe. Your setting there should reflect which compromise you prefer between the precision of calculations and chart coverage. This is also where you control the display of the information box in the lower right corner of the chart.
Markers allows you to control the plotting of chart markers on different conditions. Their configuration determines when alerts generated from the indicator will fire. Note that in order to generate alerts from this script, they must be created from your chart. See this Help Center page to learn how. Only the last 500 markers will be visible on the chart, but this will not affect the generation of alerts.
Periods is where you configure the periods for the balances and the EMAs used in the indicator.
The raw values calculated by this script can be inspected using the Data Window.
█ INTERPRETATION
Rightly or wrongly, volume delta is considered by many a useful complement to the interpretation of price action. I use it extensively in an attempt to find convergence between my read of volume delta and price movement — not so much as a predictor of future price movement. No system or person can predict the future. Accordingly, I consider people who speak or act as if they know the future with certainty to be dangerous to themselves and others; they are charlatans, imprudent or blissfully ignorant.
I try to avoid elaborate volume delta interpretation schemes involving too many variables and prefer to keep things simple:
• Trends that have more chances of continuing should be accompanied by VD of the same polarity.
In trends, I am looking for "slow and steady". I work from the assumption that traders and systems often overreact, which translates into unproductive volatility.
Wild trends are more susceptible to overreactions.
• I prefer steady VD values over wildly increasing ones, as large VD increases often come with increased price volatility, which can backfire.
Large VD values caused by stopping volume will also often occur on trend reversals with abnormally high candles.
• Prices escaping divergence channels may be leading a trend in that direction, although there is no telling how long that trend will last; could be just a few bars or hundreds.
When price is in a channel, shifts in VD balances can sometimes give us an idea of the direction where price has the most chance of breaking.
• Dwindling VD will often indicate trend exhaustion and predate reversals by many bars, but the problem is that mere pauses in a trend will often produce the same behavior in VD.
I think it is too perilous to infer rigidly from VD decreases.
Divergence Channel
Here I have configured the divergence channels to be visible. First, I set the bodies to display divergences on the default Bar Balance. They are indicated by yellow bodies. Then I activated the divergence channels by choosing to draw levels on body divergences and checked the "Fill" checkbox to fill the channel with the same color as the levels. The divergence channel is best understood as a direction-less area from where a breach can be acted on if other variables converge with the breach's direction:
Tops and Bottoms EMAs
I find these EMAs rather interesting. They have no equivalent elsewhere, as they are calculated from the top and bottom values this indicator plots. The only similarity they have with volume-weighted MAs, including VWAP, is that they use price and volume. This indicator's Tops and Bottoms EMAs, however, use the price and volume delta. While the channel differs from other channels in how it is calculated, it can be used like others, as a baseline from which to evaluate price movement or, alternatively, as stop levels. Remember that you can change the period used for the EMAs in the "Periods" section of the inputs.
This chart shows the EMAs in action, filled with a gradient representing the advances/decline from the Momentum balance. Notice the anomaly in the chart's latest bars where the Momentum balance gradient has been indicating a bullish bias for some time, during which price was mostly below the EMAs. Price has just broken above the channel on positive VD. My interpretation of this situation would be that it is a risky opportunity for a long trade in the larger context where the market has been in a downtrend since the 5th. Intrepid traders choosing to enter here could do so with a "make or break" tight stop that will minimize their losses should the market continue its downtrend while hopefully preserving the potential upside of price continuing on the longer-term uptrend prevalent since the 28th:
█ NOTES
Volume
If you use indicators such as this one which depends on volume information, it is important to realize that the volume data they consume comes from data feeds, and that all data feeds are NOT created equally. Those who create the data feeds we use must make decisions concerning the nature of the transactions they tally and the way they are tallied in each feed, and these decisions affect the nature of our volume data. My Volume X-ray publication discusses some of the reasons why volume information from different timeframes, brokers/exchanges or sectors may vary considerably. I encourage you to read it. This indicator's display of a warning through a background color on volume discrepancies between the timeframe used to access intrabars and the chart's timeframe is an attempt to help you realize these variations in feeds. Don't take things for granted, and understand that the quality of a given feed's volume information affects the quality of the results this indicator calculates.
Markets as ecosystems
I believe it is perilous to think that behavioral patterns you discover in one market through the lens of this or any other indicator will necessarily port to other markets. While this may sometimes be the case, it will often not. Why is that? Because each market is its own ecosystem. As cities do, all markets share some common characteristics, but they also all have their idiosyncrasies. A proportion of a city's inhabitants is always composed of outsiders who come and go, but a core population of regulars and systems is usually the force that actually defines most of the city's observable characteristics. I believe markets work somewhat the same way; they may look the same, but if you live there for a while and pay attention, you will notice the idiosyncrasies. Some things that work in some markets will, accordingly, not work in others. Please keep that in mind when you draw conclusions.
On Up/Down or Buy/Sell Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by two different traders. While this does not keep me from using the terms, there is no such thing as “buy only” or “sell only” volume. Trader lingo is riddled with peculiarities. Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure, just as when buy market orders take out limit ask orders in the order book at successively higher levels. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s calculations are more precise because it analyses intrabars to calculate its information, it uses pretty much the same imperfect logic. Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our volume delta calculations will remain a mere proxy.
Repainting
• The values calculated on the realtime bar will update as new information comes from the feed.
• Historical values may recalculate if the historical feed is updated or when calculations start from a new point in history.
• Markers and alerts will not repaint as they only occur on a bar's close. Keep this in mind when viewing markers on historical bars,
where one could understandably and incorrectly assume they appear at the bar's open.
To learn more about repainting, see the Pine Script™ User Manual's page on the subject .
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . This indicator can display a lot of information. The inevitable adaptation period you will need to figure out how to use it should help you eliminate all the visuals you do not need. The more you eliminate, the easier it will be to focus on those that are the most useful to your trading practice. Don't be a fool.
█ THANKS
Thanks to alexgrover for his Dekidaka-Ashi indicator. His volume plots on candles were the inspiration for my top/bottom plots.
Kudos to PineCoders for their libraries. I use two of them in this script: Time and lower_tf .
The first versions of this script used functionality that I would not have known about were it not for these two guys:
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator.
— theheirophant , my partner in the exploration of the sometimes weird abysses of request.security() ’s behavior at lower timeframes.
ULTIMATE ORDER FLOW SYSTEM🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines **Volume Profile**, **Cumulative Delta**, and **Large Order Detection** to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
📊 Core Components & Methodology
🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines Volume Profile, Cumulative Delta, and Large Order Detection to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
________________________________________
📊 Core Components & Methodology
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
• Dividing the price range into configurable rows (default: 20)
• Accumulating volume at each price level over a lookback period (default: 50 bars)
• Separating buy volume (green bars close > open) from sell volume (red bars)
• Identifying three critical levels:
o POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
o VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
o HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
o LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
________________________________________
2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
• Bar Delta: Difference between buy and sell volume per candle
• Cumulative Delta: Sum of all bar deltas - shows net directional pressure
• Delta Moving Average: Smoothed delta (20-period) to identify trend
• Delta Divergences:
o Bullish: Price makes lower low, but delta makes higher low (absorption at bottom)
o Bearish: Price makes higher high, but delta makes lower high (exhaustion at top)
How It Works: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
________________________________________
3. Large Order Detection
Identifies institutional-sized orders in real-time:
• Compares current bar volume to 20-period moving average
• Flags orders exceeding 2.5x average volume (configurable multiplier)
• Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
Rationale: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
________________________________________
🎯 Trading Signal Logic
Combined Setup Criteria
The script generates SHORT and LONG signals when multiple conditions align:
SHORT Signal Requirements:
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
LONG Signal Requirements:
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
________________________________________
🔧 Customization Options
Setting - Purpose - Recommendation
Volume Profile Rows - Granularity of level detection - 20 (balanced)
Lookback Period - Historical data analyzed - 50 bars (intraday), 200 (swing)
Large Order Multiplier - Sensitivity to volume spikes - 2.5x (standard), 3.5x (conservative)
HVN Threshold - Resistance zone detection - 1.3 (default)
LVN Threshold - Target zone identification - 0.6 (default)
Divergence Lookback - Pivot detection period - 5 bars (responsive)
________________________________________
📈 Dashboard Indicators
The real-time panel displays:
• POC: Current Point of Control price
• Location: Whether price is at HVN resistance
• Orders: Current large buy/sell activity
• Cumulative Δ: Net order flow value + trend direction
• Divergence: Active bullish/bearish divergences
• Bar Strength: % of candle volume that's directional (>65% = strong)
• SETUP: Current trade signal (LONG/SHORT/WAIT)
________________________________________
🎨 Visual System
• Yellow POC Line: Highest volume level - primary pivot
• Blue Value Area Box: Fair value zone (VAH to VAL)
• Red HVN Zones: Resistance/support from institutional accumulation
• Green LVN Zones: Low-liquidity targets for quick moves
• Volume Bars: Green (buy pressure) vs Red (sell pressure) distribution
• Triangles: LONG (green up) and SHORT (red down) entry signals
• Diamonds: Divergence warnings (cyan=bullish, fuchsia=bearish)
________________________________________
💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. Synthesizes three complementary methods - volume structure, order flow momentum, and liquidity detection
2. Requires multi-factor confirmation - signals only trigger when price, volume, and delta align at key zones
3. Adapts to market regime - delta filters ensure you're trading with the dominant order flow direction
4. Provides context, not just signals - the dashboard helps you understand why a setup is forming
________________________________________
⚙️ Best Practices
Timeframes:
• 5-15 min: Scalping (use 30-50 bar lookback)
• 1-4 hour: Swing trading (use 100-200 bar lookback)
Risk Management:
• Enter on signal candle close
• Stop loss: Beyond nearest HVN/LVN zone
• Target 1: Next LVN level
• Target 2: Opposite value area boundary
Filters:
• Avoid signals during major news events
• Require bar delta strength >65% for aggressive entries
• Wait for delta MA cross confirmation in ranging markets
________________________________________
🚨 Alerts Available
• Long Setup Trigger
• Short Setup Trigger
• Bullish/Bearish Divergence Detection
• Large Buy/Sell Order Execution
________________________________________
📚 Educational Context
This methodology is based on principles used by professional order flow traders:
• Market Profile Theory: Volume distribution reveals fair value
• Tape Reading: Large orders show institutional intent
• Auction Theory: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
________________________________________
⚠️ Disclaimer
This indicator is a trading tool, not a trading system. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
________________________________________
Version: 6 (Pine Script)
Type: Overlay + Separate Pane (Delta Panel)
Resource Usage: Moderate (500 bars history, 500 lines/boxes)
________________________________________
For questions or support, please comment below. If you find this script valuable, please boost and favorite! 🚀
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
- Dividing the price range into configurable rows (default: 20)
- Accumulating volume at each price level over a lookback period (default: 50 bars)
- Separating buy volume (green bars close > open) from sell volume (red bars)
- Identifying three critical levels:
- POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
- VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
- HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
- LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
---
2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
- **Bar Delta**: Difference between buy and sell volume per candle
- **Cumulative Delta**: Sum of all bar deltas - shows net directional pressure
- **Delta Moving Average**: Smoothed delta (20-period) to identify trend
- **Delta Divergences**:
- **Bullish**: Price makes lower low, but delta makes higher low (absorption at bottom)
- **Bearish**: Price makes higher high, but delta makes lower high (exhaustion at top)
**How It Works**: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
---
### 3. **Large Order Detection**
Identifies **institutional-sized orders** in real-time:
- Compares current bar volume to 20-period moving average
- Flags orders exceeding 2.5x average volume (configurable multiplier)
- Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
**Rationale**: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
---
## 🎯 Trading Signal Logic
### Combined Setup Criteria
The script generates **SHORT** and **LONG** signals when multiple conditions align:
**SHORT Signal Requirements:**
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
**LONG Signal Requirements:**
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
---
## 🔧 Customization Options
| Setting | Purpose | Recommendation |
|---------|---------|----------------|
| **Volume Profile Rows** | Granularity of level detection | 20 (balanced) |
| **Lookback Period** | Historical data analyzed | 50 bars (intraday), 200 (swing) |
| **Large Order Multiplier** | Sensitivity to volume spikes | 2.5x (standard), 3.5x (conservative) |
| **HVN Threshold** | Resistance zone detection | 1.3 (default) |
| **LVN Threshold** | Target zone identification | 0.6 (default) |
| **Divergence Lookback** | Pivot detection period | 5 bars (responsive) |
---
## 📈 Dashboard Indicators
The real-time panel displays:
- **POC**: Current Point of Control price
- **Location**: Whether price is at HVN resistance
- **Orders**: Current large buy/sell activity
- **Cumulative Δ**: Net order flow value + trend direction
- **Divergence**: Active bullish/bearish divergences
- **Bar Strength**: % of candle volume that's directional (>65% = strong)
- **SETUP**: Current trade signal (LONG/SHORT/WAIT)
---
## 🎨 Visual System
- **Yellow POC Line**: Highest volume level - primary pivot
- **Blue Value Area Box**: Fair value zone (VAH to VAL)
- **Red HVN Zones**: Resistance/support from institutional accumulation
- **Green LVN Zones**: Low-liquidity targets for quick moves
- **Volume Bars**: Green (buy pressure) vs Red (sell pressure) distribution
- **Triangles**: LONG (green up) and SHORT (red down) entry signals
- **Diamonds**: Divergence warnings (cyan=bullish, fuchsia=bearish)
---
## 💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. **Synthesizes three complementary methods** - volume structure, order flow momentum, and liquidity detection
2. **Requires multi-factor confirmation** - signals only trigger when price, volume, and delta align at key zones
3. **Adapts to market regime** - delta filters ensure you're trading with the dominant order flow direction
4. **Provides context, not just signals** - the dashboard helps you understand *why* a setup is forming
---
## ⚙️ Best Practices
**Timeframes:**
- 5-15 min: Scalping (use 30-50 bar lookback)
- 1-4 hour: Swing trading (use 100-200 bar lookback)
**Risk Management:**
- Enter on signal candle close
- Stop loss: Beyond nearest HVN/LVN zone
- Target 1: Next LVN level
- Target 2: Opposite value area boundary
**Filters:**
- Avoid signals during major news events
- Require bar delta strength >65% for aggressive entries
- Wait for delta MA cross confirmation in ranging markets
---
## 🚨 Alerts Available
- Long Setup Trigger
- Short Setup Trigger
- Bullish/Bearish Divergence Detection
- Large Buy/Sell Order Execution
---
## 📚 Educational Context
This methodology is based on principles used by professional order flow traders:
- **Market Profile Theory**: Volume distribution reveals fair value
- **Tape Reading**: Large orders show institutional intent
- **Auction Theory**: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
---
## ⚠️ Disclaimer
This indicator is a **trading tool, not a trading system**. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
---
**Version**: 6 (Pine Script)
**Type**: Overlay + Separate Pane (Delta Panel)
**Resource Usage**: Moderate (500 bars history, 500 lines/boxes)
---
*For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Mars Signals - Ultimate Institutional Suite v3.0(Joker)Comprehensive Trading Manual
Mars Signals – Ultimate Institutional Suite v3.0 (Joker)
## Chapter 1 – Philosophy & System Architecture
This script is not a simple “buy/sell” indicator.
Mars Signals – UIS v3.0 (Joker) is designed as an institutional-style analytical assistant that layers several methodologies into a single, coherent framework.
The system is built on four core pillars:
1. Smart Money Concepts (SMC)
- Detection of Order Blocks (professional demand/supply zones).
- Detection of Fair Value Gaps (FVGs) (price imbalances).
2. Smart DCA Strategy
- Combination of RSI and Bollinger Bands
- Identifies statistically discounted zones for scaling into spot positions or exiting shorts.
3. Volume Profile (Visible Range Simulation)
- Distribution of volume by price, not by time.
- Identification of POC (Point of Control) and high-/low-volume areas.
4. Wyckoff Helper – Spring
- Detection of bear traps, liquidity grabs, and sharp bullish reversals.
All four pillars feed into a Confluence Engine (Scoring System).
The final output is presented in the Dashboard, with a clear, human-readable signal:
- STRONG LONG 🚀
- WEAK LONG ↗
- NEUTRAL / WAIT
- WEAK SHORT ↘
- STRONG SHORT 🩸
This allows the trader to see *how many* and *which* layers of the system support a bullish or bearish bias at any given time.
## Chapter 2 – Settings Overview
### 2.1 General & Dashboard Group
- Show Dashboard Panel (`show_dash`)
Turns the dashboard table in the corner of the chart ON/OFF.
- Show Signal Recommendation (`show_rec`)
- If enabled, the textual signal (STRONG LONG, WEAK SHORT, etc.) is displayed.
- If disabled, you only see feature status (ON/OFF) and the current price.
- Dashboard Position (`dash_pos`)
Determines where the dashboard appears on the chart:
- `Top Right`
- `Bottom Right`
- `Top Left`
### 2.2 Smart Money (SMC) Group
- Enable SMC Strategy (`show_smc`)
Globally enables or disables the Order Block and FVG logic.
- Order Block Pivot Lookback (`ob_period`)
Main parameter for detecting key pivot highs/lows (swing points).
- Default value: 5
- Concept:
A bar is considered a pivot low if its low is lower than the lows of the previous 5 and the next 5 bars.
Similarly, a pivot high has a high higher than the previous 5 and the next 5 bars.
These pivots are used as anchors for Order Blocks.
- Increasing `ob_period`:
- Fewer levels.
- But levels tend to be more significant and reliable.
- In highly volatile markets (major news, war events, FOMC, etc.),
using values 7–10 is recommended to filter out weak levels.
- Show Fair Value Gaps (`show_fvg`)
Enables/disables the drawing of FVG zones (imbalances).
- Bullish OB Color (`c_ob_bull`)
- Color of Bullish Order Blocks (Demand Zones).
- Default: semi-transparent green (transparency ≈ 80).
- Bearish OB Color (`c_ob_bear`)
- Color of Bearish Order Blocks (Supply Zones).
- Default: semi-transparent red.
- Bullish FVG Color (`c_fvg_bull`)
- Color of Bullish FVG (upward imbalance), typically yellow.
- Bearish FVG Color (`c_fvg_bear`)
- Color of Bearish FVG (downward imbalance), typically purple.
### 2.3 Smart DCA Strategy Group
- Enable DCA Zones (`show_dca`)
Enables the Smart DCA logic and visual labels.
- RSI Length (`rsi_len`)
Lookback period for RSI (default: 14).
- Shorter → more sensitive, more noise.
- Longer → fewer signals, higher reliability.
- Bollinger Bands Length (`bb_len`)
Moving average period for Bollinger Bands (default: 20).
- BB Multiplier (`bb_mult`)
Standard deviation multiplier for Bollinger Bands (default: 2.0).
- For extremely volatile markets, values like 2.5–3.0 can be used so that only extreme deviations trigger a DCA signal.
### 2.4 Volume Profile (Visible Range Sim) Group
- Show Volume Profile (`show_vp`)
Enables the simulated Volume Profile bars on the right side of the chart.
- Volume Lookback Bars (`vp_lookback`)
Number of bars used to compute the Volume Profile (default: 150).
- Higher values → broader historical context, heavier computation.
- Row Count (`vp_rows`)
Number of vertical price segments (rows) to divide the total price range into (default: 30).
- Width (%) (`vp_width`)
Relative width of each volume bar as a percentage.
In the code, bar widths are scaled relative to the row with the maximum volume.
> Technical note: Volume Profile calculations are executed only on the last bar (`barstate.islast`) to keep the script performant even on higher timeframes.
### 2.5 Wyckoff Helper Group
- Show Wyckoff Events (`show_wyc`)
Enables detection and plotting of Wyckoff Spring events.
- Volume MA Length (`vol_ma_len`)
Length of the moving average on volume.
A bar is considered to have Ultra Volume if its volume is more than 2× the volume MA.
## Chapter 3 – Smart Money Strategy (Order Blocks & FVG)
### 3.1 What Is an Order Block?
An Order Block (OB) represents the footprint of large institutional orders:
- Bullish Order Block (Demand Zone)
The last selling region (bearish candle/cluster) before a strong upward move.
- Bearish Order Block (Supply Zone)
The last buying region (bullish candle/cluster) before a strong downward move.
Institutions and large players place heavy orders in these regions. Typical price behavior:
- Price moves away from the zone.
- Later returns to the same zone to fill unfilled orders.
- Then continues the larger trend.
In the script:
- If `pl` (pivot low) forms → a Bullish OB is created.
- If `ph` (pivot high) forms → a Bearish OB is created.
The box is drawn:
- From `bar_index ` to `bar_index`.
- Between `low ` and `high `.
- `extend=extend.right` extends the OB into the future, so it acts as a dynamic support/resistance zone.
- Only the last 4 OB boxes are kept to avoid clutter.
### 3.2 Order Block Color Guide
- Semi-transparent Green (`c_ob_bull`)
- Represents a Bullish Order Block (Demand Zone).
- Interpretation: a price region with a high probability of bullish reaction.
- Semi-transparent Red (`c_ob_bear`)
- Represents a Bearish Order Block (Supply Zone).
- Interpretation: a price region with a high probability of bearish reaction.
Overlap (Multiple OBs in the Same Area)
When two or more Order Blocks overlap:
- The shared area appears visually denser/stronger.
- This suggests higher order density.
- Such zones can be treated as high-priority levels for entries, exits, and stop-loss placement.
### 3.3 Demand/Supply Logic in the Scoring Engine
is_in_demand = low <= ta.lowest(low, 20)
is_in_supply = high >= ta.highest(high, 20)
- If current price is near the lowest lows of the last 20 bars, it is considered in a Demand Zone → positive impact on score.
- If current price is near the highest highs of the last 20 bars, it is considered in a Supply Zone → negative impact on score.
This logic complements Order Blocks and helps the Dashboard distinguish whether:
- Market is currently in a statistically cheap (long-friendly) area, or
- In a statistically expensive (short-friendly) area.
### 3.4 Fair Value Gaps (FVG)
#### Concept
When the market moves aggressively:
- Some price levels are skipped and never traded.
- A gap between wicks/shadows of consecutive candles appears.
- These regions are called Fair Value Gaps (FVGs) or Imbalances.
The market generally “dislikes” imbalance and often:
- Returns to these zones in the future.
- Fills the gap (rebalance).
- Then resumes its dominant direction.
#### Implementation in the Code
Bullish FVG (Yellow)
fvg_bull_cond = show_smc and show_fvg and low > high and close > high
if fvg_bull_cond
box.new(bar_index , high , bar_index, low, ...)
Core condition:
`low > high ` → the current low is above the high of two bars ago; the space between them is an untraded gap.
Bearish FVG (Purple)
fvg_bear_cond = show_smc and show_fvg and high < low and close < low
if fvg_bear_cond
box.new(bar_index , low , bar_index, high, ...)
Core condition:
`high < low ` → the current high is below the low of two bars ago; again a price gap exists.
#### FVG Color Guide
- Transparent Yellow (`c_fvg_bull`) – Bullish FVG
Often acts like a magnet for price:
- Price tends to retrace into this zone,
- Fill the imbalance,
- And then continue higher.
- Transparent Purple (`c_fvg_bear`) – Bearish FVG
Price tends to:
- Retrace upward into the purple area,
- Fill the imbalance,
- And then resume downward movement.
#### Trading with FVGs
- FVGs are *not* standalone entry signals.
They are best used as:
- Targets (take-profit zones), or
- Reaction areas where you expect a pause or reversal.
Examples:
- If you are long, a bearish FVG above is often an excellent take-profit zone.
- If you are short, a bullish FVG below is often a good cover/exit zone.
### 3.5 Core SMC Trading Templates
#### Reversal Long
1. Price trades down into a green Order Block (Demand Zone).
2. A bullish confirmation candle (Close > Open) forms inside or just above the OB.
3. If this zone is close to or aligned with a bullish FVG (yellow), the signal is reinforced.
4. Entry:
- At the close of the confirmation candle, or
- Using a limit order near the upper boundary of the OB.
5. Stop-loss:
- Slightly below the OB.
- If the OB is broken decisively and price consolidates below it, the zone loses validity.
6. Targets:
- The next FVG,
- Or the next red Order Block (Supply Zone) above.
#### Reversal Short
The mirror scenario:
- Price rallies into a red Order Block (Supply).
- A bearish confirmation candle forms (Close < Open).
- FVG/premium structure above can act as a confluence.
- Stop-loss goes above the OB.
- Targets: lower FVGs or subsequent green OBs below.
## Chapter 4 – Smart DCA Strategy (RSI + Bollinger Bands)
### 4.1 Smart DCA Concept
- Classic DCA = buying at fixed time intervals regardless of price.
- Smart DCA = scaling in only when:
- Price is statistically cheaper than usual, and
- The market is in a clear oversold condition.
Code logic:
rsi_val = ta.rsi(close, rsi_len)
= ta.bb(close, bb_len, bb_mult)
dca_buy = show_dca and rsi_val < 30 and close < bb_lower
dca_sell = show_dca and rsi_val > 70 and close > bb_upper
Conditions:
- DCA Buy – Smart Scale-In Zone
- RSI < 30 → oversold.
- Close < lower Bollinger Band → price has broken below its typical volatility envelope.
- DCA Sell – Overbought/Distribution Zone
- RSI > 70 → overbought.
- Close > upper Bollinger Band → price is extended far above the mean.
### 4.2 Visual Representation on the Chart
- Green “DCA” Label Below Candle
- Shape: `labelup`.
- Color: lime background, white text.
- Meaning: statistically attractive level for laddered spot entries or short exits.
- Red “SELL” Label Above Candle
- Warning that the market is in an extended, overbought condition.
- Suitable for profit-taking on longs or considering short entries (with proper confluence and risk management).
- Light Green Background (`bgcolor`)
- When `dca_buy` is true, the candle background turns very light green (high transparency).
- This helps visually identify DCA Zones across the chart at a glance.
### 4.3 Practical Use in Trading
#### Spot Trading
Used to build a better average entry price:
- Every time a DCA label appears, allocate a fixed portion of capital (e.g., 2–5%).
- Combining DCA signals with:
- Green OBs (Demand Zones), and/or
- The Volume Profile POC
makes the zone structurally more important.
#### Futures Trading
- Longs
- Use DCA Buy signals as low-risk zones for opening or adding to longs when:
- Price is inside a green OB, or
- The Dashboard already leans LONG.
- Shorts
- Use DCA Sell signals as:
- Exit zones for longs, or
- Areas to initiate shorts with stops above structural highs.
## Chapter 5 – Volume Profile (Visible Range Simulation)
### 5.1 Concept
Traditional volume (histogram under the chart) shows volume over time.
Volume Profile shows volume by price level:
- At which prices has the highest trading activity occurred?
- Where did buyers and sellers agree the most (High Volume Nodes – HVNs)?
- Where did price move quickly due to low participation (Low Volume Nodes – LVNs)?
### 5.2 Implementation in the Script
Executed only when `show_vp` is enabled and on the last bar:
1. The last `vp_lookback` bars (default 150) are processed.
2. The minimum low and maximum high over this window define the price range.
3. This price range is divided into `vp_rows` segments (e.g., 30 rows).
4. For each row:
- All bars are scanned.
- If the mid-price `(high + low ) / 2` falls inside a row, that bar’s volume is added to the row total.
5. The row with the greatest volume is stored as `max_vol_idx` (the POC row).
6. For each row, a volume box is drawn on the right side of the chart.
### 5.3 Color Scheme
- Semi-transparent Orange
- The row with the maximum volume – the Point of Control (POC).
- Represents the strongest support/resistance level from a volume perspective.
- Semi-transparent Blue
- Other volume rows.
- The taller the bar → the higher the volume → the stronger the interest at that price band.
### 5.4 Trading Applications
- If price is above POC and retraces back into it:
→ POC often acts as support, suitable for long setups.
- If price is below POC and rallies into it:
→ POC often acts as resistance, suitable for short setups or profit-taking.
HVNs (Tall Blue Bars)
- Represent areas of equilibrium where the market has spent time and traded heavily.
- Price tends to consolidate here before choosing a direction.
LVNs (Short or Nearly Empty Bars)
- Represent low participation zones.
- Price often moves quickly through these areas – useful for targeting fast moves.
## Chapter 6 – Wyckoff Helper – Spring
### 6.1 Spring Concept
In the Wyckoff framework:
- A Spring is a false break of support.
- The market briefly trades below a well-defined support level, triggers stop losses,
then sharply reverses upward as institutional buyers absorb liquidity.
This movement:
- Clears out weak hands (retail sellers).
- Provides large players with liquidity to enter long positions.
- Often initiates a new uptrend.
### 6.2 Code Logic
Conditions for a Spring:
1. The current low is lower than the lowest low of the previous 50 bars
→ apparent break of a long-standing support.
2. The bar closes bullish (Close > Open)
→ the breakdown was rejected.
3. Volume is significantly elevated:
→ `volume > 2 × volume_MA` (Ultra Volume).
When all conditions are met and `show_wyc` is enabled:
- A pink diamond is plotted below the bar,
- With the label “Spring” – one of the strongest long signals in this system.
### 6.3 Trading Use
- After a valid Spring, markets frequently enter a meaningful bullish phase.
- The highest quality setups occur when:
- The Spring forms inside a green Order Block, and
- Near or on the Volume Profile POC.
Entries:
- At the close of the Spring bar, or
- On the first pullback into the mid-range of the Spring candle.
Stop-loss:
- Slightly below the Spring’s lowest point (wick low plus a small buffer).
## Chapter 7 – Confluence Engine & Dashboard
### 7.1 Scoring Logic
For each bar, the script:
1. Resets `score` to 0.
2. Adjusts the score based on different signals.
SMC Contribution
if show_smc
if is_in_demand
score += 1
if is_in_supply
score -= 1
- Being in Demand → `+1`
- Being in Supply → `-1`
DCA Contribution
if show_dca
if dca_buy
score += 2
if dca_sell
score -= 2
- DCA Buy → `+2` (strong, statistically driven long signal)
- DCA Sell → `-2`
Wyckoff Spring Contribution
if show_wyc
if wyc_spring
score += 2
- Spring → `+2` (entry of strong money)
### 7.2 Mapping Score to Dashboard Signal
- score ≥ 2 → STRONG LONG 🚀
Multiple bullish conditions aligned.
- score = 1 → WEAK LONG ↗
Some bullish bias, but only one layer clearly positive.
- score = 0 → NEUTRAL / WAIT
Rough balance between buying and selling forces; staying flat is usually preferable.
- score = -1 → WEAK SHORT ↘
Mild bearish bias, suited for cautious or short-term plays.
- score ≤ -2 → STRONG SHORT 🩸
Convergence of several bearish signals.
### 7.3 Dashboard Structure
The dashboard is a two-column table:
- Row 0
- Column 0: `"Mars Signals"` – black background, white text.
- Column 1: `"UIS v3.0"` – black background, yellow text.
- Row 1
- Column 0: `"Price:"` (light grey background).
- Column 1: current closing price (`close`) with a semi-transparent blue background.
- Row 2
- Column 0: `"SMC:"`
- Column 1:
- `"ON"` (green) if `show_smc = true`
- `"OFF"` (grey) otherwise.
- Row 3
- Column 0: `"DCA:"`
- Column 1:
- `"ON"` (green) if `show_dca = true`
- `"OFF"` (grey) otherwise.
- Row 4
- Column 0: `"Signal:"`
- Column 1: signal text (`status_txt`) with background color `status_col`
(green, red, teal, maroon, etc.)
- If `show_rec = false`, these cells are cleared.
## Chapter 8 – Visual Legend (Colors, Shapes & Actions)
For quick reading inside TradingView, the visual elements are described line by line instead of a table.
Chart Element: Green Box
Color / Shape: Transparent green rectangle
Core Meaning: Bullish Order Block (Demand Zone)
Suggested Trader Response: Look for longs, Smart DCA adds, closing or reducing shorts.
Chart Element: Red Box
Color / Shape: Transparent red rectangle
Core Meaning: Bearish Order Block (Supply Zone)
Suggested Trader Response: Look for shorts, or take profit on existing longs.
Chart Element: Yellow Area
Color / Shape: Transparent yellow zone
Core Meaning: Bullish FVG / upside imbalance
Suggested Trader Response: Short take-profit zone or expected rebalance area.
Chart Element: Purple Area
Color / Shape: Transparent purple zone
Core Meaning: Bearish FVG / downside imbalance
Suggested Trader Response: Long take-profit zone or temporary supply region.
Chart Element: Green "DCA" Label
Color / Shape: Green label with white text, plotted below the candle
Core Meaning: Smart ladder-in buy zone, DCA buy opportunity
Suggested Trader Response: Spot DCA entry, partial short exit.
Chart Element: Red "SELL" Label
Color / Shape: Red label with white text, plotted above the candle
Core Meaning: Overbought / distribution zone
Suggested Trader Response: Take profit on longs, consider initiating shorts.
Chart Element: Light Green Background (bgcolor)
Color / Shape: Very transparent light-green background behind bars
Core Meaning: Active DCA Buy zone
Suggested Trader Response: Treat as a discount zone on the chart.
Chart Element: Orange Bar on Right
Color / Shape: Transparent orange horizontal bar in the volume profile
Core Meaning: POC – price with highest traded volume
Suggested Trader Response: Strong support or resistance; key reference level.
Chart Element: Blue Bars on Right
Color / Shape: Transparent blue horizontal bars in the volume profile
Core Meaning: Other volume levels, showing high-volume and low-volume nodes
Suggested Trader Response: Use to identify balance zones (HVN) and fast-move corridors (LVN).
Chart Element: Pink "Spring" Diamond
Color / Shape: Pink diamond with white text below the candle
Core Meaning: Wyckoff Spring – liquidity grab and potential major bullish reversal
Suggested Trader Response: One of the strongest long signals in the suite; look for high-quality long setups with tight risk.
Chart Element: STRONG LONG in Dashboard
Color / Shape: Green background, white text in the Signal row
Core Meaning: Multiple bullish layers in confluence
Suggested Trader Response: Consider initiating or increasing longs with strict risk management.
Chart Element: STRONG SHORT in Dashboard
Color / Shape: Red background, white text in the Signal row
Core Meaning: Multiple bearish layers in confluence
Suggested Trader Response: Consider initiating or increasing shorts with a logical, well-placed stop.
## Chapter 9 – Timeframe-Based Trading Playbook
### 9.1 Timeframe Selection
- Scalping
- Timeframes: 1M, 5M, 15M
- Objective: fast intraday moves (minutes to a few hours).
- Recommendation: focus on SMC + Wyckoff.
Smart DCA on very low timeframes may introduce excessive noise.
- Day Trading
- Timeframes: 15M, 1H, 4H
- Provides a good balance between signal quality and frequency.
- Recommendation: use the full stack – SMC + DCA + Volume Profile + Wyckoff + Dashboard.
- Swing Trading & Position Investing
- Timeframes: Daily, Weekly
- Emphasis on Smart DCA + Volume Profile.
- SMC and Wyckoff are used mainly to fine-tune swing entries within larger trends.
### 9.2 Scenario A – Scalping Long
Example: 5-Minute Chart
1. Price is declining into a green OB (Bullish Demand).
2. A candle with a long lower wick and bullish close (Pin Bar / Rejection) forms inside the OB.
3. A Spring diamond appears below the same candle → very strong confluence.
4. The Dashboard shows at least WEAK LONG ↗, ideally STRONG LONG 🚀.
5. Entry:
- On the close of the confirmation candle, or
- On the first pullback into the mid-range of that candle.
6. Stop-loss:
- Slightly below the OB.
7. Targets:
- Nearby bearish FVG above, and/or
- The next red OB.
### 9.3 Scenario B – Day-Trading Short
Recommended Timeframes: 1H or 4H
1. The market completes a strong impulsive move upward.
2. Price enters a red Order Block (Supply).
3. In the same zone, a purple FVG appears or remains unfilled.
4. On a lower timeframe (e.g., 15M), RSI enters overbought territory and a DCA Sell signal appears.
5. The main timeframe Dashboard (1H) shows WEAK SHORT ↘ or STRONG SHORT 🩸.
Trade Plan
- Open a short near the upper boundary of the red OB.
- Place the stop above the OB or above the last swing high.
- Targets:
- A yellow FVG lower on the chart, and/or
- The next green OB (Demand) below.
### 9.4 Scenario C – Swing / Investment with Smart DCA
Timeframes: Daily / Weekly
1. On the daily or weekly chart, each time a green “DCA” label appears:
- Allocate a fixed fraction of your capital (e.g., 3–5%) to that asset.
2. Check whether this DCA zone aligns with the orange POC of the Volume Profile:
- If yes → the quality of the entry zone is significantly higher.
3. If the DCA signal sits inside a daily green OB, the probability of a medium-term bottom increases.
4. Always build the position laddered, never all-in at a single price.
Exits for investors:
- Near weekly red OBs or large purple FVG zones.
- Ideally via partial profit-taking rather than closing 100% at once.
### 9.5 Case Study 1 – BTCUSDT (15-Minute)
- Context: Price has sold off down towards 65,000 USD.
- A green OB had previously formed at that level.
- Near the lower boundary of this OB, a partially filled yellow FVG is present.
- As price returns to this region, a Spring appears.
- The Dashboard shifts from NEUTRAL / WAIT to WEAK LONG ↗.
Plan
- Enter a long near the OB low.
- Place stop below the Spring low.
- First target: a purple FVG around 66,200.
- Second (optional) target: the first red OB above that level.
### 9.6 Case Study 2 – Meme Coin (PEPE – 4H)
- After a strong pump, price enters a corrective phase.
- On the 4H chart, RSI drops below 30; price breaks below the lower Bollinger Band → a DCA label prints.
- The Volume Profile shows the POC at approximately the same level.
- The Dashboard displays STRONG LONG 🚀.
Plan
- Execute laddered buys in the combined DCA + POC zone.
- Place a protective stop below the last significant swing low.
- Target: an expected 20–30% upside move towards the next red OB or purple FVG.
## Chapter 10 – Risk Management, Psychology & Advanced Tuning
### 10.1 Risk Management
No signal, regardless of its strength, replaces risk control.
Recommendations:
- In futures, do not expose more than 1–3% of account equity to risk per trade.
- Adjust leverage to the volatility of the instrument (lower leverage for highly volatile altcoins).
- Place stop-losses in zones where the idea is clearly invalidated:
- Below/above the relevant Order Block or Spring, not randomly in the middle of the structure.
### 10.2 Market-Specific Parameter Tuning
- Calmer Markets (e.g., major FX pairs)
- `ob_period`: 3–5.
- `bb_mult`: 2.0 is usually sufficient.
- Highly Volatile Markets (Crypto, news-driven assets)
- `ob_period`: 7–10 to highlight only the most robust OBs.
- `bb_mult`: 2.5–3.0 so that only extreme deviations trigger DCA.
- `vol_ma_len`: increase (e.g., to ~30) so that Spring triggers only on truly exceptional
volume spikes.
### 10.3 Trading Psychology
- STRONG LONG 🚀 does not mean “risk-free”.
It means the probability of a successful long, given the model’s logic, is higher than average.
- Treat Mars Signals as a confirmation and context system, not a full replacement for your own decision-making.
- Example of disciplined thinking:
- The Dashboard prints STRONG LONG,
- But price is simultaneously testing a multi-month macro resistance or a major negative news event is imminent,
- In such cases, trade smaller, widen stops appropriately, or skip the trade.
## Chapter 11 – Technical Notes & FAQ
### 11.1 Does the Script Repaint?
- Order Blocks and Springs are based on completed pivot structures and confirmed candles.
- Until a pivot is confirmed, an OB does not exist; after confirmation, behavior is stable under classic SMC assumptions.
- The script is designed to be structurally consistent rather than repainting signals arbitrarily.
### 11.2 Computational Load of Volume Profile
- On the last bar, the script processes up to `vp_lookback` bars × `vp_rows` rows.
- On very low timeframes with heavy zooming, this can become demanding.
- If you experience performance issues:
- Reduce `vp_lookback` or `vp_rows`, or
- Temporarily disable Volume Profile (`show_vp = false`).
### 11.3 Multi-Timeframe Behavior
- This version of the script is not internally multi-timeframe.
All logic (OB, DCA, Spring, Volume Profile) is computed on the active timeframe only.
- Practical workflow:
- Analyze overall structure and key zones on higher timeframes (4H / Daily).
- Use lower timeframes (15M / 1H) with the same tool for timing entries and exits.
## Conclusion
Mars Signals – Ultimate Institutional Suite v3.0 (Joker) is a multi-layer trading framework that unifies:
- Price structure (Order Blocks & FVG),
- Statistical behavior (Smart DCA via RSI + Bollinger),
- Volume distribution by price (Volume Profile with POC, HVN, LVN),
- Liquidity events (Wyckoff Spring),
into a single, coherent system driven by a transparent Confluence Scoring Engine.
The final output is presented in clear, actionable language:
> STRONG LONG / WEAK LONG / NEUTRAL / WEAK SHORT / STRONG SHORT
The system is designed to support professional decision-making, not to replace it.
Used together with strict risk management and disciplined execution,
Mars Signals – UIS v3.0 (Joker) can serve as a central reference manual and operational guide
for your trading workflow, from scalping to swing and investment positioning.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
lower_tfLibrary "lower_tf"
█ OVERVIEW
This library is an enhanced (opinionated) version of the library originally developed by PineCoders contained in lower_tf .
It is a Pine Script® programming tool for advanced lower-timeframe selection and intra-bar analysis.
█ CONCEPTS
Lower Timeframe Analysis
Lower timeframe analysis refers to the analysis of price action and market microstructure using data from timeframes shorter than the current chart period. This technique allows traders and analysts to gain deeper insights into market dynamics, volume distribution, and the price movements occurring within each bar on the chart. In Pine Script®, the request.security_lower_tf() function allows this analysis by accessing intrabar data.
The library provides a comprehensive set of functions for accurate mapping of lower timeframes, dynamic precision control, and optimized historical coverage using request.security_lower_tf().
█ IMPROVEMENTS
The original library implemented ten precision levels. This enhanced version extends that to twelve levels, adding two ultra-high-precision options:
Coverage-Based Precision (Original 5 levels):
1. "Covering most chart bars (least precise)"
2. "Covering some chart bars (less precise)"
3. "Covering fewer chart bars (more precise)"
4. "Covering few chart bars (very precise)"
5. "Covering the least chart bars (most precise)"
Intrabar-Count-Based Precision (Expanded from 5 to 7 levels):
6. "~12 intrabars per chart bar"
7. "~24 intrabars per chart bar"
8. "~50 intrabars per chart bar"
9. "~100 intrabars per chart bar"
10. "~250 intrabars per chart bar"
11. "~500 intrabars per chart bar" ← NEW
12. "~1000 intrabars per chart bar" ← NEW
The key enhancements in this version include:
1. Extended Precision Range: Adds two ultra-high-precision levels (~500 and ~1000 intrabars) for advanced microstructure analysis requiring maximum granularity.
2. Market-Agnostic Implementation: Eliminates the distinction between crypto/forex and traditional markets, removing the mktFactor variable in favor of a unified, predictable approach across all asset classes.
3. Explicit Precision Mapping: Completely refactors the timeframe selection logic using native Pine Script® timeframe properties ( timeframe.isseconds , timeframe.isminutes , timeframe.isdaily , timeframe.isweekly , timeframe.ismonthly ) and explicit multiplier-based lookup tables. The original library used minute-based calculations with market-dependent conditionals that produced inconsistent results. This version provides deterministic, predictable mappings for every chart timeframe, ensuring consistent precision behavior regardless of asset type or market hours.
An example of the differences can be seen side-by-side in the chart below, where the original library is on the left and the enhanced version is on the right:
█ USAGE EXAMPLE
// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © andre_007
//@version=6
indicator("lower_tf Example")
import andre_007/lower_tf/1 as LTF
import PineCoders/Time/5 as PCtime
//#region ———————————————————— Example code
// ————— Constants
color WHITE = color.white
color GRAY = color.gray
string LTF1 = "Covering most chart bars (least precise)"
string LTF2 = "Covering some chart bars (less precise)"
string LTF3 = "Covering less chart bars (more precise)"
string LTF4 = "Covering few chart bars (very precise)"
string LTF5 = "Covering the least chart bars (most precise)"
string LTF6 = "~12 intrabars per chart bar"
string LTF7 = "~24 intrabars per chart bar"
string LTF8 = "~50 intrabars per chart bar"
string LTF9 = "~100 intrabars per chart bar"
string LTF10 = "~250 intrabars per chart bar"
string LTF11 = "~500 intrabars per chart bar"
string LTF12 = "~1000 intrabars per chart bar"
string TT_LTF = "This selection determines the approximate number of intrabars analyzed per chart bar. Higher numbers of
intrabars produce more granular data at the cost of less historical bar coverage, because the maximum number of
available intrabars is 200K.
\n\nThe first five options set the lower timeframe based on a specified relative level of chart bar coverage.
The last five options set the lower timeframe based on an approximate number of intrabars per chart bar."
string TAB_TXT = "Uses intrabars at the {0} timeframe.\nAvg intrabars per chart bar:
{1,number,#.#}\nChart bars covered: {2} of {3} ({4,number,#.##}%)"
string ERR_TXT = "No intrabar information exists at the {1}{0}{1} timeframe."
// ————— Inputs
string ltfModeInput = input.string(LTF3, "Intrabar precision", options = , tooltip = TT_LTF)
bool showInfoBoxInput = input.bool(true, "Show information box ")
string infoBoxSizeInput = input.string("normal", "Size ", inline = "01", options = )
string infoBoxYPosInput = input.string("bottom", "↕", inline = "01", options = )
string infoBoxXPosInput = input.string("right", "↔", inline = "01", options = )
color infoBoxColorInput = input.color(GRAY, "", inline = "01")
color infoBoxTxtColorInput = input.color(WHITE, "T", inline = "01")
// ————— Calculations
// @variable A "string" representing the lower timeframe for the data request.
// NOTE:
// This line is a good example where using `var` in the declaration can improve a script's performance.
// By using `var` here, the script calls `ltf()` only once, on the dataset's first bar, instead of redundantly
// evaluating unchanging strings on every bar. We only need one evaluation of this function because the selected
// timeframe does not change across bars in this script.
var string ltfString = LTF.ltf(ltfModeInput, LTF1, LTF2, LTF3, LTF4, LTF5, LTF6, LTF7, LTF8, LTF9, LTF10, LTF11, LTF12)
// @variable An array containing all intrabar `close` prices from the `ltfString` timeframe for the current chart bar.
array intrabarCloses = request.security_lower_tf(syminfo.tickerid, ltfString, close)
// Calculate the intrabar stats.
= LTF.ltfStats(intrabarCloses)
int chartBars = bar_index + 1
// ————— Visuals
// Plot the `avgIntrabars` and `intrabars` series in all display locations.
plot(avgIntrabars, "Average intrabars", color.silver, 6)
plot(intrabars, "Intrabars", color.blue, 2)
// Plot the `chartBarsCovered` and `chartBars` values in the Data Window and the script's status line.
plot(chartBarsCovered, "Chart bars covered", display = display.data_window + display.status_line)
plot(chartBars, "Chart bars total", display = display.data_window + display.status_line)
// Information box logic.
if showInfoBoxInput
// @variable A single-cell table that displays intrabar information.
var table infoBox = table.new(infoBoxYPosInput + "_" + infoBoxXPosInput, 1, 1)
// @variable The span of the `ltfString` timeframe formatted as a number of automatically selected time units.
string formattedLtf = PCtime.formattedNoOfPeriods(timeframe.in_seconds(ltfString) * 1000)
// @variable A "string" containing the formatted text to display in the `infoBox`.
string txt = str.format(
TAB_TXT, formattedLtf, avgIntrabars, chartBarsCovered, chartBars, chartBarsCovered / chartBars * 100, "'"
)
// Initialize the `infoBox` cell on the first bar.
if barstate.isfirst
table.cell(
infoBox, 0, 0, txt, text_color = infoBoxTxtColorInput, text_size = infoBoxSizeInput,
bgcolor = infoBoxColorInput
)
// Update the cell's text on the latest bar.
else if barstate.islast
table.cell_set_text(infoBox, 0, 0, txt)
// Raise a runtime error if no intrabar data is available.
if ta.cum(intrabars) == 0 and barstate.islast
runtime.error(str.format(ERR_TXT, ltfString, "'"))
//#endregion
█ EXPORTED FUNCTIONS
ltf(userSelection, choice1, choice2, ...)
Returns the optimal lower timeframe string based on user selection and current chart timeframe. Dynamically calculates precision to balance granularity with historical coverage within the 200K intrabar limit.
ltfStats(intrabarValues)
Analyzes an intrabar array returned by request.security_lower_tf() and returns statistics: number of intrabars in current bar, total chart bars covered, and average intrabars per bar.
█ CREDITS AND LICENSING
Original Concept : PineCoders Team
Original Lower TF Library :
License : Mozilla Public License 2.0
Price Action Brooks ProPrice Action Brooks Pro (PABP) - Professional Trading Indicator
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📊 OVERVIEW
Price Action Brooks Pro (PABP) is a professional-grade TradingView indicator developed based on Al Brooks' Price Action trading methodology. It integrates decades of Al Brooks' trading experience and price action analysis techniques into a comprehensive technical analysis tool, helping traders accurately interpret market structure and identify trading opportunities.
• Applicable Markets: Stocks, Futures, Forex, Cryptocurrencies
• Timeframes: 1-minute to Daily (5-minute chart recommended)
• Theoretical Foundation: Al Brooks Price Action Trading Method
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🎯 CORE FEATURES
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1️⃣ INTELLIGENT GAP DETECTION SYSTEM
Automatically identifies and marks three critical types of gaps in the market.
TRADITIONAL GAP
• Detects complete price gaps between bars
• Upward gap: Current bar's low > Previous bar's high
• Downward gap: Current bar's high < Previous bar's low
• Hollow border design - doesn't obscure price action
• Color coding: Upward gaps (light green), Downward gaps (light pink)
• Adjustable border: 1-5 pixel width options
TAIL GAP
• Detects price gaps between bar wicks/shadows
• Analyzes across 3 bars for precision
• Identifies hidden market structure
BODY GAP
• Focuses only on gaps between bar bodies (open/close)
• Filters out wick noise
• Disabled by default, enable as needed
Trading Significance:
• Gaps signal strong momentum
• Gap fills provide trading opportunities
• Consecutive gaps indicate trend continuation
✓ Independent alert system for all gap types
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2️⃣ RTH BAR COUNT (Trading Session Counter)
Intelligent counting system designed for US stock intraday trading.
FEATURES
• RTH Only Display: Regular Trading Hours (09:30-15:00 EST)
• 5-Minute Chart Optimized: Displays every 3 bars (15-minute intervals)
• Daily Auto-Reset: Counting starts from 1 each trading day
SMART COLOR CODING
• 🔴 Red (Bars 18 & 48): Critical turning moments (1.5h & 4h)
• 🔵 Sky Blue (Multiples of 12): Hourly markers (12, 24, 36...)
• 🟢 Light Green (Bar 6): Half-hour marker (30 minutes)
• ⚫ Gray (Others): Regular 15-minute interval markers
Al Brooks Time Theory:
• Bar 18 (90 min): First 90 minutes determine daily trend
• Bar 48 (4 hours): Important afternoon turning point
• Hourly markers: Track institutional trading rhythm
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
3️⃣ FOUR-LINE EMA SYSTEM
Professional-grade configurable moving average system.
DEFAULT CONFIGURATION
• EMA 20: Short-term trend (Al Brooks' most important MA)
• EMA 50: Medium-short term reference
• EMA 100: Medium-long term confirmation
• EMA 200: Long-term trend and bull/bear dividing line
FLEXIBLE CUSTOMIZATION
Each EMA can be independently configured:
• On/Off toggle
• Data source selection (close/high/low/open, etc.)
• Custom period length
• Offset adjustment
• Color and transparency
COLOR SCHEME
• EMA 20: Dark brown, opaque (most important)
• EMA 50/100/200: Blue-purple gradient, 70% transparent
TRADING APPLICATIONS
• Bullish Alignment: Price > 20 > 50 > 100 > 200
• Bearish Alignment: 200 > 100 > 50 > 20 > Price
• EMA Confluence: All within <1% = major move precursor
Al Brooks Quote:
"The EMA 20 is the most important moving average. Almost all trading decisions should reference it."
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4️⃣ PREVIOUS VALUES (Key Prior Price Levels)
Automatically marks important price levels that often act as support/resistance.
THREE INDEPENDENT CONFIGURATIONS
Each group configurable for:
• Timeframe (1D/60min/15min, etc.)
• Price source (close/high/low/open/CurrentOpen, etc.)
• Line style and color
• Display duration (Today/TimeFrame/All)
SMART OPEN PRICE LABELS ⭐
• Auto-displays "Open" label when CurrentOpen selected
• Label color matches line color
• Customizable label size
TYPICAL SETUP
• 1st Line: Previous close (Support/Resistance)
• 2nd Line: Previous high (Breakout target)
• 3rd Line: Previous low (Support level)
Al Brooks Magnet Price Theory:
• Previous open: Price frequently tests opening price
• Previous high/low: Strongest support/resistance
• Breakout confirmation: Breaking prior levels = trend continuation
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5️⃣ INSIDE & OUTSIDE BAR PATTERN RECOGNITION
Automatically detects core candlestick patterns from Al Brooks' theory.
ii PATTERN (Consecutive Inside Bars)
• Current bar contained within previous bar
• Two or more consecutive
• Labels: ii, iii, iiii (auto-accumulates)
• High-probability breakout setup
• Stop loss: Outside both bars
Trading Significance:
"Inside bars are one of the most reliable breakout setups, especially three or more consecutive inside bars." - Al Brooks
OO PATTERN (Consecutive Outside Bars)
• Current bar engulfs previous bar
• Two or more consecutive
• Labels: oo, ooo (auto-accumulates)
• Indicates indecision or volatility increase
ioi PATTERN (Inside-Outside-Inside)
• Three-bar combination: Inside → Outside → Inside
• Auto-detected and labeled
• Tug-of-war pattern
• Breakout direction often very strong
SMART LABEL SYSTEM
• Auto-accumulation counting
• Dynamic label updates
• Customizable size and color
• Positioned above bars
✓ Independent alerts for all patterns
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💡 USE CASES
INTRADAY TRADING
✓ Bar Count (timing rhythm)
✓ Traditional Gap (strong signals)
✓ EMA 20 + 50 (quick trend)
✓ ii/ioi Patterns (breakout points)
SWING TRADING
✓ Previous Values (key levels)
✓ EMA 20 + 50 + 100 (trend analysis)
✓ Gaps (trend confirmation)
✓ iii Patterns (entry timing)
TREND FOLLOWING
✓ All four EMAs (alignment analysis)
✓ Gaps (continuation signals)
✓ Previous Values (targets)
BREAKOUT TRADING
✓ iii Pattern (high-reliability setup)
✓ Previous Values (targets)
✓ EMA 20 (trend direction)
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🎨 DESIGN FEATURES
PROFESSIONAL COLOR SCHEME
• Gaps: Hollow borders + light colors
• Bar Count: Smart multi-color coding
• EMAs: Gradient colors + transparency hierarchy
• Previous Values: Customizable + smart labels
CLEAR VISUAL HIERARCHY
• Important elements: Opaque (EMA 20, bar count)
• Reference elements: Semi-transparent (other EMAs, gaps)
• Hollow design: Doesn't obscure price action
USER-FRIENDLY INTERFACE
• Clear functional grouping
• Inline layout saves space
• All colors and sizes customizable
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📚 AL BROOKS THEORY CORE
READING PRICE ACTION
"Don't try to predict the market, read what the market is telling you."
PABP converts core concepts into visual tools:
• Trend Assessment: EMA system
• Time Rhythm: Bar Count
• Market Structure: Gap analysis
• Trade Setups: Inside/Outside Bars
• Support/Resistance: Previous Values
PROBABILITY THINKING
• ii pattern: Medium probability
• iii pattern: High probability
• iii + EMA 20 support: Very high probability
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⚙️ TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Maximum Objects: 500 lines, 500 labels, 500 boxes
• Alert Functions: 8 independent alerts
• Supported Timeframes: All (5-min recommended for Bar Count)
• Compatibility: All TradingView plans, Mobile & Desktop
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🚀 RECOMMENDED INITIAL SETTINGS
GAPS
• Traditional Gap: ✓
• Tail Gap: ✓
• Border Width: 2
BAR COUNT
• Use Bar Count: ✓
• Label Size: Normal
EMA
• EMA 20: ✓
• EMA 50: ✓
• EMA 100: ✓
• EMA 200: ✓
PREVIOUS VALUES
• 1st: close (Previous close)
• 2nd: high (Previous high)
• 3rd: low (Previous low)
INSIDE & OUTSIDE BAR
• All patterns: ✓
• Label Size: Large
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🌟 WHY CHOOSE PABP?
✅ Solid Theoretical Foundation
Based on Al Brooks' decades of trading experience
✅ Complete Professional Features
Systematizes complex price action analysis
✅ Highly Customizable
Every feature adjustable to personal style
✅ Excellent Performance
Optimized code ensures smooth experience
✅ Continuous Updates
Constantly improving based on feedback
✅ Suitable for All Levels
Benefits beginners to professionals
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📖 RECOMMENDED LEARNING
Al Brooks Books:
• "Trading Price Action Trends"
• "Trading Price Action Trading Ranges"
• "Trading Price Action Reversals"
Learning Path:
1. Understand basic candlestick patterns
2. Learn EMA applications
3. Master market structure analysis
4. Develop trading system
5. Continuous practice and optimization
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⚠️ RISK DISCLOSURE
IMPORTANT NOTICE:
• For educational and informational purposes only
• Does not constitute investment advice
• Past performance doesn't guarantee future results
• Trading involves risk and may result in capital loss
• Trade according to your risk tolerance
• Test thoroughly in demo account first
RESPONSIBLE TRADING:
• Always use stop losses
• Control position sizes reasonably
• Don't overtrade
• Continuous learning and improvement
• Keep trading journal
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📜 COPYRIGHT
Price Action Brooks Pro (PABP)
Author: © JimmC98
License: Mozilla Public License 2.0
Pine Script Version: v6
Acknowledgments:
Thanks to Dr. Al Brooks for his contributions to price action trading. This indicator is developed based on his theories.
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Experience professional-grade price action analysis now!
"The best traders read price action, not indicators. But when indicators help you read price action better, use them." - Al Brooks
Anchored VWAP Polyline [CHE] Anchored VWAP Polyline — Anchored VWAP drawn as a polyline from a user-defined bar count with last-bar updates and optional labels
Summary
This indicator renders an anchored Volume-Weighted Average Price as a continuous polyline starting from a user-selected anchor point a specified number of bars back. It accumulates price multiplied by volume only from the anchor forward and resets cleanly when the anchor moves. Drawing is object-based (polyline and labels) and updated on the most recent bar only, which reduces flicker and avoids excessive redraws. Optional labels mark the anchor and, conditionally, a delta label when the current close is below the historical close at the anchor offset.
Motivation: Why this design?
Anchored VWAP is often used to track fair value after a specific event such as a swing, breakout, or session start. Traditional plot-based lines can repaint during live updates or incur overhead when frequently redrawn. This implementation focuses on explicit state management, last-bar rendering, and object recycling so the line stays stable while remaining responsive when the anchor changes. The design emphasizes deterministic updates and simple session gating from the anchor.
What’s different vs. standard approaches?
Baseline: Classic VWAP lines plotted from session open or full history.
Architecture differences:
Anchor defined by a fixed bar offset rather than session or day boundaries.
Object-centric drawing via `polyline` with an array of `chart.point` objects.
Last-bar update pattern with deletion and replacement of the polyline to apply all points cleanly.
Conditional labels: an anchor marker and an optional delta label only when the current close is below the historical close at the offset.
Practical effect: You get a visually continuous anchored VWAP that resets when the anchor shifts and remains clean on chart refreshes. The labels act as lightweight diagnostics without clutter.
How it works (technical)
The anchor index is computed as the latest bar index minus the user-defined bar count.
A session flag turns true from the anchor forward; prior bars are excluded.
Two persistent accumulators track the running sum of price multiplied by volume and the running sum of volume; they reset when the session flag turns from false to true.
The anchored VWAP is the running sum divided by the running volume whenever both are valid and the volume is not zero.
Points are appended to an array only when the anchored VWAP is valid. On the most recent bar, any existing polyline is deleted and replaced with a new one built from the point array.
Labels are refreshed on the most recent bar:
A yellow warning label appears when there are not enough bars to compute the reference values.
The anchor label marks the anchor bar.
The delta label appears only when the current close is below the close at the anchor offset; otherwise it is suppressed.
No higher-timeframe requests are used; repaint is limited to normal live-bar behavior.
Parameter Guide
Bars back — Sets the anchor offset in bars; default two hundred thirty-three; minimum one. Larger values extend the anchored period and increase stability but respond more slowly to regime changes.
Labels — Toggles all labels; default enabled. Disable to keep the chart clean when using multiple instances.
Reading & Interpretation
The polyline represents the anchored VWAP from the chosen anchor to the current bar. Price above the line suggests strength relative to the anchored baseline; price below suggests weakness.
The anchor label shows where the accumulation starts.
The delta label appears only when today’s close is below the historical close at the offset; it provides a quick context for negative drift relative to that reference.
A yellow message at the current bar indicates the chart does not have enough history to compute the reference comparison yet.
Practical Workflows & Combinations
Trend following: Anchor after a breakout bar or a swing confirmation. Use the anchored VWAP as dynamic support or resistance; look for clean retests and holds for continuation.
Mean reversion: Anchor at a local extreme and watch for approaches back toward the line; require structure confirmation to avoid early entries.
Session or event studies: Re-set the anchor around earnings, macro releases, or session opens by adjusting the bar offset.
Combinations: Pair with structure tools such as swing highs and lows, or with volatility measures to filter chop. The labels can be disabled when combining multiple instances to maintain chart clarity.
Behavior, Constraints & Performance
Repaint and confirmation: The line is updated on the most recent bar only; historical values do not rely on future bars. Normal live-bar movement applies until the bar closes.
No higher timeframe: There is no `security` call; repaint paths related to higher-timeframe lookahead do not apply here.
Resources: Uses one polyline object that is rebuilt on the most recent bar, plus two labels when conditions are met. `max_bars_back` is two thousand. Arrays store points from the anchor forward; extremely long anchors or very long charts increase memory usage.
Known limits: With very thin volume, the VWAP can be unavailable for some bars. Very large anchors reduce responsiveness. Labels use ATR for vertical placement; extreme gaps can place them close to extremes.
Sensible Defaults & Quick Tuning
Starting point: Bars back two hundred thirty-three with Labels enabled works well on many assets and timeframes.
Too noisy around the line: Increase Bars back to extend the accumulation window.
Too sluggish after regime changes: Decrease Bars back to focus on a shorter anchored period.
Chart clutter with multiple instances: Disable Labels while keeping the polyline visible.
What this indicator is—and isn’t
This is a visualization of an anchored VWAP with optional diagnostics. It is not a full trading system and does not include entries, exits, or position management. Use it alongside clear market structure, risk controls, and a plan for trade management. It does not predict future prices.
Inputs with defaults
Bars back: two hundred thirty-three bars, minimum one.
Labels: enabled or disabled toggle, default enabled.
Pine version: v6
Overlay: true
Primary outputs: one polyline, optional labels (anchor, conditional delta, and a warning when insufficient bars).
Metrics and functions: volume, ATR for label offset, object drawing via polyline and chart points, last-bar update pattern.
Special techniques: session gating from the anchor, persistent state, object recycling, explicit guards against unavailable values and zero volume.
Compatibility and assets: Designed for standard candlestick or bar charts across liquid assets and common timeframes.
Diagnostics: Yellow warning label when history is insufficient.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Custom Buy/Sell Pattern BuilderAre you tired of using trading indicators that only let you follow fixed, pre-designed rules? Do you wish you could build your own “Buy” or “Sell” signals, experiment with your own ideas, or see instantly if your unique pattern works—without learning coding or hiring a developer?
The Custom Buy/Sell Pattern Builder is designed for YOU.
This TradingView indicator lets ANY trader—even a complete beginner—define exactly what kind of price and volume conditions should create a BUY or SELL label on any chart, in any market, at any timeframe.
You don’t need to know programming. You don’t need to know the definition of a hammer, doji, volume spike, or Engulfing pattern.
With a few clicks and easy dropdown choices, you can:
Make your own rules for buying or selling
Choose how many candles your pattern should look at
Decide if you want the biggest body, the lowest volume, the biggest movement, or any combination you can imagine
The result?
You’ll see clear “BUY” or “SELL” labels automatically show up on your chart whenever the exact rule YOU built matches current price action.
No more guessing. No more forced strategies. Just pure control and visual feedback!
Why Is This Powerful?
Traditional indicators (like MACD, RSI, or even classic candlestick scanners) work the same for everyone—and only as their inventors defined.
But every trader, and every market, is unique.
What if you could say:
“Show me a ‘SELL’ every time the newest candle is bigger than the one before, but with LESS volume, while the bar before that had an even smaller body—but more volume than all others?”
With this tool, it’s EASY!
You simply pick which candle you want to compare (most recent, previous, etc), what to compare (body or volume—body means the candle’s “thickness”, from open to close), choose “greater than”, “less than”, or “equal to”, and set a multiplier if you want (like “half as much”, “twice as big”, etc).
After this, if any bar on the chart fits all your rules, it will mark it as a BUY or SELL, depending on your selection.
This means—
Beginners can start experimenting with their intuition or small ideas, without tech hurdles
Experienced traders can visualize and fine-tune any possible logic, before they commit to backtesting or automating a real strategy
Every “what if” or “I wonder” setup is just 2–3 clicks away
How Does It Work? Simple Steps
1. Choose Your Signal Type
“Buy” or “Sell”
This tells the indicator whether to mark the qualifying bars with a green “BUY” or red “SELL” label
2. Pick How Many Candles To Use
“Pattern Candle Count” input (2, 3, or 4)
Example: If you use 4, the pattern will be applied to the most recent 4 candles at every step
3. Define Your Pattern With Inputs
For each candle (from newest “0” to oldest “3”), you can set:
Body Condition (example: “is this candle’s body bigger/smaller/equal to another?”)
Pick which candle to compare against
Pick “>”, “<”, “>=”, “<=”, or “=”
Set a multiplier if needed (like “0.5” to mean “half as big as” or “2” for “twice as big as”)
Volume Condition (exact same choices, but based on trading volume—not the candle’s price body)
For example:
“Candle0 Body > Candle2 Body”
means “the latest candle’s real-body (open–close) is bigger than the one two bars ago.”
“Candle1 Volume <= Candle2 Volume”
means “the previous candle’s volume is less than or equal to the volume of the bar two periods ago.”
You can leave a comparison blank if you don’t want to use it for a particular candle.
What Happens After You Set Your Rules?
Every bar on your chart is checked for your logic:
If ALL body AND volume conditions are true (for each candle you specified),
AND
The signal side (“Buy” or “Sell”) matches your dropdown,
Then a green “BUY” or red “SELL” label will show right on the bar, so you can visually spot exactly where your logic works!
Practical Example:
Suppose you want an entry setup that is:
“Sell whenever the newest candle’s body is bigger than two bars ago, body before that is bigger than three bars ago, AND the newest candle’s volume is less than or equal to two bars ago, AND the candle three bars ago’s volume is less than or equal to half the candle two bars ago’s volume.”
You’d set:
Pattern Candle Count: 4
Side: Sell
Candle0 Body Ref#: 2, Op: >, Mult: 1
Candle1 Body Ref#: 3, Op: >, Mult: 1
Candle0 Vol Ref#: 2, Op: <=, Mult: 1
Candle3 Vol Ref#: 2, Op: <=, Mult: 0.5
And the script will find all “SELL” bars on your chart matching these conditions.
Inputs Section: What Does Each Setting Do?
Let’s break down each input in the indicator’s Settings one by one, so even if you’re new, you’ll understand exactly how to use it!
1. Pattern Candle Count (2–4)
What is it?
This sets how many candles in a row you want your rule to look at.
Example:
“4” means your rules are based on the most recent candle and the 3 before it.
“2” means you are only comparing the current and previous candles.
Tip:
Beginners often use 4 to spot stronger patterns, but you can experiment!
2. Signal Side
What is it?
Choose “Buy” or “Sell”. The word you pick here decides which colored label (green for Buy, red for Sell) appears if your pattern matches.
Example:
Want to spot where “Sell” is likely? Pick “Sell”.
Change to “Buy” if you want bullish signals instead.
3. Body & Volume Comparison Settings (per Candle)
For each candle (#0 is newest/current, #3 is oldest in your pattern window):
Body Comparison
Candle# Body Ref#
Choose which other candle you want to compare this one’s body to.
“0” = newest, “1” = previous, “2” = two bars ago, “3” = three bars ago
Candle# Body Op (Operator; >, <, >=, <=, =)
How do you want to compare?
“>” means “greater than” (is bigger than)
“<” means “less than” (is smaller than)
“=” means “equal to”
Candle# Body Mult (Multiplier)
If you want relative comparisons. For example, with Mult=1:
“Candle0 body > Candle2 body x 1” means just “0 is larger than 2.”
“Candle0 body > Candle2 body x 2” means “0 is more than double 2.”
Volume Comparison
Candle# Vol Ref# / Op / Mult
Exact same logic as body, but works on the “Volume” of each candle (how much was traded during that bar).
How to Set Up a Rule (Step by Step Example)
Say you want to mark a Sell every time:
The most recent candle’s real body is BIGGER than the candle 2 bars ago;
The previous candle’s body is also BIGGER than the candle 3 bars ago;
The current candle’s volume is LESS than or equal to the volume of candle 2;
The previous candle’s volume is LESS than or equal to candle 2’s volume;
The candle 3 bars ago’s volume is LESS than or equal to HALF candle 2’s volume.
You’d set:
Pattern Candle Count: 4
Side: "Sell"
Candle0 Body Ref#: 2, Op: “>”, Mult: 1
Candle1 Body Ref#: 3, Op: “>”, Mult: 1
Candle0 Vol Ref#: 2, Op: “<=”, Mult: 1
Candle1 Vol Ref#: 2, Op: “<=”, Mult: 1
Candle3 Vol Ref#: 2, Op: “<=”, Mult: 0.5
All other comparisons (operators) can be left blank if you don’t want to use them!
When these rules are met, a bright red “SELL” label will appear right above the bar matching all your conditions.
Practical Tips & FAQ for Beginners
What does “body” mean?
It’s the “true range” of the candle: the difference between open and close. This ignores wicks for simple setups.
What does “volume” mean?
This is the total trading activity during that candle/bar. Many traders believe that patterns with different volume “meaning” (such as low-volume up bars, or high-volume down bars) signal a meaningful change.
What if nothing shows on chart?
It just means your current rules are rarely or never matched! Try making your comparisons simpler (maybe just 2-body and 2-volume conditions to start).
You can always hit “Reset Settings” to go back to default.
Can I use this for both buying and selling?
YES! You can detect both bullish (Buy) and bearish (Sell) custom conditions; just switch “Signal Side.”
Do I need to know coding?
Not at all! Everything is in simple input panels.
Creative Use Cases, Example Recipes & Troubleshooting
Creative Ways to Use
Spotting Reversals
Example:
Buy when: the newest candle body is LARGER than the previous 3 bars, but ALL volumes are lower than their neighbors.
Why? Sometimes, a big candle with surprisingly low volume after a sequence of small bars can signal a reversal.
Finding Exhaustion Moves
Example:
Sell when: the current bar body is twice as big as two bars ago, but volume is half.
Why? A very big candle with very little volume compared to similar bars may show the move is “running out of steam.”
Custom “Breakout + Confirmation” Patterns
Example:
Buy when:
Candle 0’s body is greater than Candle 2’s by at least 1.5x,
Candle 0’s volume is greater than Candle 1 and Candle 2,
Candle 1’s volume is less than Candle 0.
Why? This could catch strong breakouts but filter out noisy moves.
Multi-bar Bias/Squeeze Filter
Use “Pattern Candle Count: 4”
Set all 4 volume conditions to “<” and each reference to the previous candle.
Now, a BUY or SELL only marks when each bar is “dryer”/less active than the last — a classic squeeze or low-volatility buildup.
Troubleshooting Guide
“I don’t see any Buy/Sell label; is something broken?”
Most likely, your rules are too strict or rare! Try using only two comparisons and leave other “Op” inputs blank as a test.
Double-check you have enough candles on the chart: you need at least as many bars as your pattern count.
“Why does a label appear but not where I expect?”
Remember, the script checks your rules for every NEW candle. The candle “0” is always the most recent, then “1” is one bar back, etc.
Check the color and type chosen: “Signal Side” must be “Buy” for green, “Sell” for red.
“What if I want a more complex pattern?”
Stack conditions! You can demand the body/volume of each candle in your window meet a different rule or all follow the same rule in sequence.
Mini Glossary — For Newcomers
Candle/Bar: Each bar on the chart, shows price movement during a fixed time (e.g., one minute, one hour, one day).
Body: The colored (or filled) part of the candle — the open-to-close price range.
Volume: How much of the asset was actually traded that candle/bar.
Reference Index: When you pick “2” as a reference, it means “the candle two bars ago in the pattern window.”
Operator (“Op”): The math symbol used to compare (>, <, =, etc).
Signal Side: Whether you want to highlight bullish (“Buy”) or bearish (“Sell”) bars.
Tips for Getting More Value
Start Simple—try just one or two conditions at first. See what lights up. Slowly add more logic as you get comfortable.
Watch the chart live as you change settings. The labels update instantly—this makes strategy design fast and visual!
Try flipping your ideas: If a certain pattern doesn’t work for buys, try reversing the direction for possible “sell” setups.
Remember: There is NO wrong idea. This indicator is only limited by your creativity—it’s a “strategy playground.”
Example Quick-Start Recipes
Classic Sell:
4 candles, side = Sell
Candle0 Body > Candle2; Candle1 Body > Candle3
Candle0 Vol <= Candle2; Candle1 Vol <= Candle2; Candle3 Vol <= Candle2 × 0.5
Simple Buy After Pause:
3 candles, side = Buy
Candle0 Body > Candle1; Candle0 Vol > Candle1
All other Ops blank
Low-Volume Pullback for Entry:
4 candles, side = Buy
Candle0 Body > Candle2
Candle0 Vol < Candle1; Candle1 Vol < Candle2; Candle2 Vol < Candle3
Final Words
Think of this as your “pattern lab.” No code, no guesswork—just experiment, see what the market actually gives, and design your own visual rulebook.
If you’re stuck, reset the script to defaults—it’s always safe to start again!
If you want more ready-made “recipes” for different strategies/styles, just ask and I’ll send some more setups for you.
Happy building—and may your edge always be YOUR edge!
MSFA_LibraryLibrary "MSFA_library"
TODO: add library description here
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current decimal places on the market quote price
getPipSize(multiplier)
Calculates the pip size of the current market
Parameters:
multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)
Returns: The pip size for the current market
truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places
Parameters:
number (float) : The number to truncate
decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to
Returns: The given number truncated to the given decimalPlaces
toWhole(number)
Converts pips into whole numbers
Parameters:
number (float) : The pip number to convert into a whole number
Returns: The converted number
toPips(number)
Converts whole numbers back into pips
Parameters:
number (float) : The whole number to convert into pips
Returns: The converted number
getPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period
Parameters:
value1 (float) : The first value to reference
value2 (float) : The second value to reference
lookback (int) : The lookback period to analyze
Returns: The percent change over the two values and lookback period
random(minRange, maxRange)
Wichmann–Hill Pseudo-Random Number Generator
Parameters:
minRange (float) : The smallest possible number (default: 0)
maxRange (float) : The largest possible number (default: 1)
Returns: A random number between minRange and maxRange
bullFib(priceLow, priceHigh, fibRatio)
Calculates a bullish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
bearFib(priceLow, priceHigh, fibRatio)
Calculates a bearish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
getMA(length, maType)
Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)
Parameters:
length (simple int) : The MA period
maType (string) : The type of MA
Returns: A moving average with the given parameters
barsAboveMA(lookback, ma)
Counts how many candles are above the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to check
Returns: The bar count of how many recent bars are above the MA
barsBelowMA(lookback, ma)
Counts how many candles are below the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many recent bars are below the EMA
barsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently (based on closing prices)
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many times price recently crossed the EMA (based on closing prices)
getPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count)
Parameters:
lookback (int) : The lookback period to look back over
direction (int) : The color of the bar to count (1 = Green, -1 = Red)
Returns: The bar count of how many candles have retraced over the given lookback & direction
getBodySize()
Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getBottomWickSize()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBodyPercent()
Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage
isHammer(fib, colorMatch)
Checks if the current bar is a hammer candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(fib, colorMatch)
Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isDoji(wickSize, bodySize)
Checks if the current bar is a doji candle based on the given parameters
Parameters:
wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)
bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isBullishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bullish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle
isBearishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bearish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle
isInsideBar()
Detects inside bars
Returns: Returns true if the current bar is an inside bar
isOutsideBar()
Detects outside bars
Returns: Returns true if the current bar is an outside bar
barInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls within the given time session
barOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls outside the given time session
dateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range
Parameters:
startTime (int) : The UNIX date timestamp to begin searching from
endTime (int) : the UNIX date timestamp to stop searching from
Returns: A boolean - true if the current bar falls within the given dates
dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze
Parameters:
monday (bool) : Should the script analyze this day? (true/false)
tuesday (bool) : Should the script analyze this day? (true/false)
wednesday (bool) : Should the script analyze this day? (true/false)
thursday (bool) : Should the script analyze this day? (true/false)
friday (bool) : Should the script analyze this day? (true/false)
saturday (bool) : Should the script analyze this day? (true/false)
sunday (bool) : Should the script analyze this day? (true/false)
Returns: A boolean - true if the current bar's day is one of the given days
atrFilter(atrValue, maxSize)
Parameters:
atrValue (float)
maxSize (float)
tradeCount()
Calculate total trade count
Returns: Total closed trade count
isLong()
Check if we're currently in a long trade
Returns: True if our position size is positive
isShort()
Check if we're currently in a short trade
Returns: True if our position size is negative
isFlat()
Check if we're currentlyflat
Returns: True if our position size is zero
wonTrade()
Check if this bar falls after a winning trade
Returns: True if we just won a trade
lostTrade()
Check if this bar falls after a losing trade
Returns: True if we just lost a trade
maxDrawdownRealized()
Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
totalPipReturn()
Gets the total amount of pips won/lost (as a whole number)
Returns: Total amount of pips won/lost (as a whole number)
longWinCount()
Count how many winning long trades we've had
Returns: Long win count
shortWinCount()
Count how many winning short trades we've had
Returns: Short win count
longLossCount()
Count how many losing long trades we've had
Returns: Long loss count
shortLossCount()
Count how many losing short trades we've had
Returns: Short loss count
breakEvenCount(allowanceTicks)
Count how many break-even trades we've had
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even count
longCount()
Count how many long trades we've taken
Returns: Long trade count
shortCount()
Count how many short trades we've taken
Returns: Short trade count
longWinPercent()
Calculate win rate of long trades
Returns: Long win rate (0-100)
shortWinPercent()
Calculate win rate of short trades
Returns: Short win rate (0-100)
breakEvenPercent(allowanceTicks)
Calculate break even rate of all trades
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even win rate (0-100)
averageRR()
Calculate average risk:reward
Returns: Average winning trade divided by average losing trade
unitsToLots(units)
(Forex) Convert the given unit count to lots (multiples of 100,000)
Parameters:
units (float) : The units to convert into lots
Returns: Units converted to nearest lot size (as float)
skipTradeMonteCarlo(chance, debug)
Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation
Parameters:
chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)
debug (bool) : Whether or not to display a label informing of the trade skip
Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks)
fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)
This updates the given table's cell with the given values
Parameters:
tableID (table) : The table ID to update
column (int) : The column to update
row (int) : The row to update
title (string) : The title of this cell
value (string) : The value of this cell
bgcolor (color) : The background color of this cell
txtcolor (color) : The text color of this cell
tooltip (string)
Returns: Nothing.
GEEKSDOBYTE IFVG w/ Buy/Sell Signals1. Inputs & Configuration
Swing Lookback (swingLen)
Controls how many bars on each side are checked to mark a swing high or swing low (default = 5).
Booleans to Toggle Plotting
showSwings – Show small triangle markers at swing highs/lows
showFVG – Show Fair Value Gap zones
showSignals – Show “BUY”/“SELL” labels when price inverts an FVG
showDDLine – Show a yellow “DD” line at the close of the inversion bar
showCE – Show an orange dashed “CE” line at the midpoint of the gap area
2. Swing High / Low Detection
isSwingHigh = ta.pivothigh(high, swingLen, swingLen)
Marks a bar as a swing high if its high is higher than the highs of the previous swingLen bars and the next swingLen bars.
isSwingLow = ta.pivotlow(low, swingLen, swingLen)
Marks a bar as a swing low if its low is lower than the lows of the previous and next swingLen bars.
Plotting
If showSwings is true, small red downward triangles appear above swing highs, and green upward triangles below swing lows.
3. Fair Value Gap (3‐Bar) Identification
A Fair Value Gap (FVG) is defined here using a simple three‐bar logic (sometimes called an “inefficiency” in price):
Bullish FVG (bullFVG)
Checks if, two bars ago, the low of that bar (low ) is strictly greater than the current bar’s high (high).
In other words:
bullFVG = low > high
Bearish FVG (bearFVG)
Checks if, two bars ago, the high of that bar (high ) is strictly less than the current bar’s low (low).
In other words:
bearFVG = high < low
When either condition is true, it identifies a three‐bar “gap” or unfilled imbalance in the market.
4. Drawing FVG Zones
If showFVG is enabled, each time a bullish or bearish FVG is detected:
Bullish FVG Zone
Draws a semi‐transparent green box from the bar two bars ago (where the gap began) at low up to the current bar’s high.
Bearish FVG Zone
Draws a semi‐transparent red box from the bar two bars ago at high down to the current bar’s low.
These colored boxes visually highlight the “fair value imbalance” area on the chart.
5. Inversion (Fill) Detection & Entry Signals
An inversion is defined as the price “closing through” that previously drawn FVG:
Bullish Inversion (bullInversion)
Occurs when a bullish FVG was identified on bar-2 (bullFVG), and on the current bar the close is greater than that old bar-2 low:
bullInversion = bullFVG and close > low
Bearish Inversion (bearInversion)
Occurs when a bearish FVG was identified on bar-2 (bearFVG), and on the current bar the close is lower than that old bar-2 high:
bearInversion = bearFVG and close < high
When an inversion is true, the indicator optionally draws two lines and a label (depending on input toggles):
Draw “DD” Line (yellow, solid)
Plots a horizontal yellow line from the current bar’s close price extending five bars forward (bar_index + 5). This is often referred to as a “Demand/Daily Demand” line, marking where price inverted the gap.
Draw “CE” Line (orange, dashed)
Calculates the midpoint (ce) of the original FVG zone.
For a bullish inversion:
ce = (low + high) / 2
For a bearish inversion:
ce = (high + low) / 2
Plots a horizontal dashed orange line at that midpoint for five bars forward.
Plot Label (“BUY” / “SELL”)
If showSignals is true, a green “BUY” label is placed at the low of the current bar when a bullish inversion occurs.
Likewise, a red “SELL” label at the high of the current bar when a bearish inversion happens.
6. Putting It All Together
Swing Markers (Optional):
Visually confirm recent swing highs and swing lows with small triangles.
FVG Zones (Optional):
Highlight areas where price left a 3-bar gap (bullish in green, bearish in red).
Inversion Confirmation:
Wait for price to close beyond the old FVG boundary.
Once that happens, draw the yellow “DD” line at the close, the orange dashed “CE” line at the zone’s midpoint, and place a “BUY” or “SELL” label exactly on that bar.
User Controls:
All of the above elements can be individually toggled on/off (showSwings, showFVG, showSignals, showDDLine, showCE).
In Practice
A bullish FVG forms whenever a strong drop leaves a gap in liquidity (three bars ago low > current high).
When price later “fills” that gap by closing above the old low, the script signals a potential long entry (BUY), draws a demand line at the closing price, and marks the midpoint of that gap.
Conversely, a bearish FVG marks a potential short zone (three bars ago high < current low). When price closes below that gap’s high, it signals a SELL, with similar lines drawn.
By combining these elements, the indicator helps users visually identify inefficiencies (FVGs), confirm when price inverts/fills them, and place straightforward buy/sell labels alongside reference lines for trade management.
MirPapa_Library_ICTLibrary "MirPapa_Library_ICT"
GetHTFoffsetToLTFoffset(_offset, _chartTf, _htfTf)
GetHTFoffsetToLTFoffset
@description Adjust an HTF offset to an LTF offset by calculating the ratio of timeframes.
Parameters:
_offset (int) : int The HTF bar offset (0 means current HTF bar).
_chartTf (string) : string The current chart’s timeframe (e.g., "5", "15", "1D").
_htfTf (string) : string The High Time Frame string (e.g., "60", "1D").
@return int The corresponding LTF bar index. Returns 0 if the result is negative.
IsConditionState(_type, _isBull, _level, _open, _close, _open1, _close1, _low1, _low2, _low3, _low4, _high1, _high2, _high3, _high4)
IsConditionState
@description Evaluate a condition state based on type for COB, FVG, or FOB.
Overloaded: first signature handles COB, second handles FVG/FOB.
Parameters:
_type (string) : string Condition type ("cob", "fvg", "fob").
_isBull (bool) : bool Direction flag: true for bullish, false for bearish.
_level (int) : int Swing level (only used for COB).
_open (float) : float Current bar open price (only for COB).
_close (float) : float Current bar close price (only for COB).
_open1 (float) : float Previous bar open price (only for COB).
_close1 (float) : float Previous bar close price (only for COB).
_low1 (float) : float Low 1 bar ago (only for COB).
_low2 (float) : float Low 2 bars ago (only for COB).
_low3 (float) : float Low 3 bars ago (only for COB).
_low4 (float) : float Low 4 bars ago (only for COB).
_high1 (float) : float High 1 bar ago (only for COB).
_high2 (float) : float High 2 bars ago (only for COB).
_high3 (float) : float High 3 bars ago (only for COB).
_high4 (float) : float High 4 bars ago (only for COB).
@return bool True if the specified condition is met, false otherwise.
IsConditionState(_type, _isBull, _pricePrev, _priceNow)
IsConditionState
@description Evaluate FVG or FOB condition based on price movement.
Parameters:
_type (string) : string Condition type ("fvg", "fob").
_isBull (bool) : bool Direction flag: true for bullish, false for bearish.
_pricePrev (float) : float Previous price (for FVG/FOB).
_priceNow (float) : float Current price (for FVG/FOB).
@return bool True if the specified condition is met, false otherwise.
IsSwingHighLow(_isBull, _level, _open, _close, _open1, _close1, _low1, _low2, _low3, _low4, _high1, _high2, _high3, _high4)
IsSwingHighLow
@description Public wrapper for isSwingHighLow.
Parameters:
_isBull (bool) : bool Direction flag: true for bullish, false for bearish.
_level (int) : int Swing level (1 or 2).
_open (float) : float Current bar open price.
_close (float) : float Current bar close price.
_open1 (float) : float Previous bar open price.
_close1 (float) : float Previous bar close price.
_low1 (float) : float Low 1 bar ago.
_low2 (float) : float Low 2 bars ago.
_low3 (float) : float Low 3 bars ago.
_low4 (float) : float Low 4 bars ago.
_high1 (float) : float High 1 bar ago.
_high2 (float) : float High 2 bars ago.
_high3 (float) : float High 3 bars ago.
_high4 (float) : float High 4 bars ago.
@return bool True if swing condition is met, false otherwise.
AddBox(_left, _right, _top, _bot, _xloc, _colorBG, _colorBD)
AddBox
@description Draw a rectangular box on the chart with specified coordinates and colors.
Parameters:
_left (int) : int Left bar index for the box.
_right (int) : int Right bar index for the box.
_top (float) : float Top price coordinate for the box.
_bot (float) : float Bottom price coordinate for the box.
_xloc (string) : string X-axis location type (e.g., xloc.bar_index).
_colorBG (color) : color Background color for the box.
_colorBD (color) : color Border color for the box.
@return box Returns the created box object.
Addline(_x, _y, _xloc, _color, _width)
Addline
@description Draw a vertical or horizontal line at specified coordinates.
Parameters:
_x (int) : int X-coordinate for start (bar index).
_y (int) : float Y-coordinate for start (price).
_xloc (string) : string X-axis location type (e.g., xloc.bar_index).
_color (color) : color Line color.
_width (int) : int Line width.
@return line Returns the created line object.
Addline(_x, _y, _xloc, _color, _width)
Parameters:
_x (int)
_y (float)
_xloc (string)
_color (color)
_width (int)
Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)
Parameters:
_x1 (int)
_y1 (int)
_x2 (int)
_y2 (int)
_xloc (string)
_color (color)
_width (int)
Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)
Parameters:
_x1 (int)
_y1 (int)
_x2 (int)
_y2 (float)
_xloc (string)
_color (color)
_width (int)
Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)
Parameters:
_x1 (int)
_y1 (float)
_x2 (int)
_y2 (int)
_xloc (string)
_color (color)
_width (int)
Addline(_x1, _y1, _x2, _y2, _xloc, _color, _width)
Parameters:
_x1 (int)
_y1 (float)
_x2 (int)
_y2 (float)
_xloc (string)
_color (color)
_width (int)
AddlineMid(_type, _left, _right, _top, _bot, _xloc, _color, _width)
AddlineMid
@description Draw a midline between top and bottom for FVG or FOB types.
Parameters:
_type (string) : string Type identifier: "fvg" or "fob".
_left (int) : int Left bar index for midline start.
_right (int) : int Right bar index for midline end.
_top (float) : float Top price of the region.
_bot (float) : float Bottom price of the region.
_xloc (string) : string X-axis location type (e.g., xloc.bar_index).
_color (color) : color Line color.
_width (int) : int Line width.
@return line or na Returns the created line or na if type is not recognized.
GetHtfFromLabel(_label)
GetHtfFromLabel
@description Convert a Korean HTF label into a Pine Script timeframe string via handler library.
Parameters:
_label (string) : string The Korean label (e.g., "5분", "1시간").
@return string Returns the corresponding Pine Script timeframe (e.g., "5", "60").
IsChartTFcomparisonHTF(_chartTf, _htfTf)
IsChartTFcomparisonHTF
@description Determine whether a given HTF is greater than or equal to the current chart timeframe.
Parameters:
_chartTf (string) : string Current chart timeframe (e.g., "5", "15", "1D").
_htfTf (string) : string HTF timeframe (e.g., "60", "1D").
@return bool True if HTF ≥ chartTF, false otherwise.
CreateBoxData(_type, _isBull, _useLine, _top, _bot, _xloc, _colorBG, _colorBD, _offset, _htfTf, htfBarIdx, _basePoint)
CreateBoxData
@description Create and draw a box and optional midline for given type and parameters. Returns success flag and BoxData.
Parameters:
_type (string) : string Type identifier: "fvg", "fob", "cob", or "sweep".
_isBull (bool) : bool Direction flag: true for bullish, false for bearish.
_useLine (bool) : bool Whether to draw a midline inside the box.
_top (float) : float Top price of the box region.
_bot (float) : float Bottom price of the box region.
_xloc (string) : string X-axis location type (e.g., xloc.bar_index).
_colorBG (color) : color Background color for the box.
_colorBD (color) : color Border color for the box.
_offset (int) : int HTF bar offset (0 means current HTF bar).
_htfTf (string) : string HTF timeframe string (e.g., "60", "1D").
htfBarIdx (int) : int HTF bar_index (passed from HTF request).
_basePoint (float) : float Base point for breakout checks.
@return tuple(bool, BoxData) Returns a boolean indicating success and the created BoxData struct.
ProcessBoxDatas(_datas, _useMidLine, _closeCount, _colorClose)
ProcessBoxDatas
@description Process an array of BoxData structs: extend, record volume, update stage, and finalize boxes.
Parameters:
_datas (array) : array Array of BoxData objects to process.
_useMidLine (bool) : bool Whether to update the midline endpoint.
_closeCount (int) : int Number of touches required to close the box.
_colorClose (color) : color Color to apply when a box closes.
@return void No return value; updates are in-place.
BoxData
Fields:
_isActive (series bool)
_isBull (series bool)
_box (series box)
_line (series line)
_basePoint (series float)
_boxTop (series float)
_boxBot (series float)
_stage (series int)
_isStay (series bool)
_volBuy (series float)
_volSell (series float)
_result (series string)
LineData
Fields:
_isActive (series bool)
_isBull (series bool)
_line (series line)
_basePoint (series float)
_stage (series int)
_isStay (series bool)
_result (series string)
LinearRegressionLibrary "LinearRegression"
Calculates a variety of linear regression and deviation types, with optional emphasis weighting. Additionally, multiple of slope and Pearson’s R calculations.
calcSlope(_src, _len, _condition)
Calculates the slope of a linear regression over the specified length.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period for the linear regression.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The slope of the linear regression.
calcReg(_src, _len, _condition)
Calculates a basic linear regression, returning y1, y2, slope, and average.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) An array of 4 values: .
calcRegStandard(_src, _len, _emphasis, _condition)
Calculates an Standard linear regression with optional emphasis.
Parameters:
_src (float) : (series float) The source data series.
_len (int) : (int) The length of the lookback period.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegRidge(_src, _len, lambda, _emphasis, _condition)
Calculates a ridge regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda (float) : (float) The ridge regularization parameter.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegLasso(_src, _len, lambda, _emphasis, _condition)
Calculates a Lasso regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda (float) : (float) The Lasso regularization parameter.
_emphasis (float) : (float) The emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcElasticNetLinReg(_src, _len, lambda1, lambda2, _emphasis, _condition)
Calculates an Elastic Net regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
lambda1 (float) : (float) L1 regularization parameter (Lasso).
lambda2 (float) : (float) L2 regularization parameter (Ridge).
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegHuber(_src, _len, delta, iterations, _emphasis, _condition)
Calculates a Huber regression using Iteratively Reweighted Least Squares (IRLS).
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
delta (float) : (float) Huber threshold parameter.
iterations (int) : (int) Number of IRLS iterations.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegLAD(_src, _len, iterations, _emphasis, _condition)
Calculates a Least Absolute Deviations (LAD) regression via IRLS.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
iterations (int) : (int) Number of IRLS iterations for LAD.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRegBayesian(_src, _len, priorMean, priorSpan, sigma, _emphasis, _condition)
Calculates a Bayesian linear regression with optional emphasis.
Parameters:
_src (float) : (float) The source data series.
_len (int) : (int) The length of the lookback period.
priorMean (float) : (float) The prior mean for the slope.
priorSpan (float) : (float) The prior variance (or span) for the slope.
sigma (float) : (float) The assumed standard deviation of residuals.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: (float ) .
calcRFromLinReg(_src, _len, _slope, _average, _y1, _condition)
Calculates the Pearson correlation coefficient (R) based on linear regression parameters.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_average (float) : (float) The average value of the source data series.
_y1 (float) : (float) The starting point (y-intercept of the oldest bar) for the linear regression.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The Pearson correlation coefficient (R) adjusted for the direction of the slope.
calcRFromSource(_src, _len, _condition)
Calculates the correlation coefficient (R) using a specified length and source data.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast for efficiency.
Returns: (float) The correlation coefficient (R).
calcSlopeLengthZero(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is flattest (closest to zero).
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length to consider (minimum of 2).
_minLen (int) : (int) The minimum length to start from (cannot exceed the max length).
_step (int) : (int) The increment step for lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is flattest.
calcSlopeLengthHighest(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is highest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is highest.
calcSlopeLengthLowest(_src, _len, _minLen, _step, _condition)
Identifies the length at which the slope is lowest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the slope is lowest.
calcSlopeLengthAbsolute(_src, _len, _minLen, _step, _condition)
Identifies the length at which the absolute slope value is highest.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length at which the absolute slope value is highest.
calcRLengthZero(_src, _len, _minLen, _step, _condition)
Identifies the length with the lowest absolute R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the lowest absolute R value.
calcRLengthHighest(_src, _len, _minLen, _step, _condition)
Identifies the length with the highest R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the highest R value.
calcRLengthLowest(_src, _len, _minLen, _step, _condition)
Identifies the length with the lowest R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the lowest R value.
calcRLengthAbsolute(_src, _len, _minLen, _step, _condition)
Identifies the length with the highest absolute R value.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The maximum lookback length (minimum of 2).
_minLen (int) : (int) The minimum length to start from.
_step (int) : (int) The step for incrementing lengths.
_condition (bool) : (bool) Flag to enable calculation. Set to true to calculate on every bar; otherwise, set to barstate.islast.
Returns: (int) The length with the highest absolute R value.
calcDevReverse(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the regressive linear deviation in reverse order, with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevForward(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the progressive linear deviation in forward order (oldest to most recent bar), with optional emphasis.
Parameters:
_src (float) : (float) The source data array, where _src is oldest and _src is most recent.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept of the linear regression (value at the most recent bar, adjusted by slope).
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevBalanced(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the balanced linear deviation with optional emphasis on recent or older data.
Parameters:
_src (float) : (float) Source data array, where _src is the most recent and _src is the oldest.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept of the linear regression (value at the oldest bar).
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevMean(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the mean absolute deviation from a forward-applied linear trend (oldest to most recent), with optional emphasis.
Parameters:
_src (float) : (float) The source data array, where _src is the most recent and _src is the oldest.
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevMedian(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates the median absolute deviation with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data array (index 0 = oldest, index _len - 1 = most recent).
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns:
calcDevPercent(_y1, _inputDev, _condition)
Calculates the percent deviation from a given value and a specified percentage.
Parameters:
_y1 (float) : (float) The base value from which to calculate deviation.
_inputDev (float) : (float) The deviation percentage.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevFitted(_len, _slope, _y1, _emphasis, _condition)
Calculates the weighted fitted deviation based on high and low series data, showing max deviation, with optional emphasis.
Parameters:
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcDevATR(_src, _len, _slope, _y1, _inputDev, _emphasis, _condition)
Calculates an ATR-style deviation with optional emphasis on recent data.
Parameters:
_src (float) : (float) The source data (typically close).
_len (int) : (int) The length of the lookback period.
_slope (float) : (float) The slope of the linear regression.
_y1 (float) : (float) The Y-intercept (oldest bar) of the linear regression.
_inputDev (float) : (float) The input deviation multiplier.
_emphasis (float) : (float) Emphasis factor: 0 for equal weight; >0 emphasizes recent bars; <0 emphasizes older bars.
_condition (bool) : (bool) Flag to enable calculation (true = calculate).
Returns: A 2-element tuple: .
calcPricePositionPercent(_top, _bot, _src)
Calculates the percent position of a price within a linear regression channel. Top=100%, Bottom=0%.
Parameters:
_top (float) : (float) The top (positive) deviation, corresponding to 100%.
_bot (float) : (float) The bottom (negative) deviation, corresponding to 0%.
_src (float) : (float) The source price.
Returns: (float) The percent position within the channel.
plotLinReg(_len, _y1, _y2, _slope, _devTop, _devBot, _scaleTypeLog, _lineWidth, _extendLines, _channelStyle, _colorFill, _colUpLine, _colDnLine, _colUpFill, _colDnFill)
Plots the linear regression line and its deviations, with configurable styles and fill.
Parameters:
_len (int) : (int) The lookback period for the linear regression.
_y1 (float) : (float) The starting y-value of the regression line.
_y2 (float) : (float) The ending y-value of the regression line.
_slope (float) : (float) The slope of the regression line (used to determine line color).
_devTop (float) : (float) The top deviation to add to the line.
_devBot (float) : (float) The bottom deviation to subtract from the line.
_scaleTypeLog (bool) : (bool) Use a log scale if true; otherwise, linear scale.
_lineWidth (int) : (int) The width of the plotted lines.
_extendLines (string) : (string) How lines should extend (none, left, right, both).
_channelStyle (string) : (string) The style of the channel lines (solid, dashed, dotted).
_colorFill (bool) : (bool) Whether to fill the space between the top and bottom deviation lines.
_colUpLine (color) : (color) Line color when slope is positive.
_colDnLine (color) : (color) Line color when slope is negative.
_colUpFill (color) : (color) Fill color when slope is positive.
_colDnFill (color) : (color) Fill color when slope is negative.
Exposure Oscillator (Cumulative 0 to ±100%)
Exposure Oscillator (Cumulative 0 to ±100%)
This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies.
Buy Signals (Increase Exposure Score by +10%)
Buy Signal 1 (Cross Above 21 EMA):
This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend.
buySignal1 = ta.crossover(close, ema21)
Buy Signal 2 (Trending Above 21 EMA):
This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period.
buySignal2 = ta.barssince(close <= ema21) > 5
Buy Signal 3 (Living Above 21 EMA):
This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend.
buySignal3 = ta.barssince(close <= ema21) > 15
Buy Signal 4 (Cross Above 50 SMA):
This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum.
buySignal4 = ta.crossover(close, sma50)
Buy Signal 5 (Cross Above 200 SMA):
This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend.
buySignal5 = ta.crossover(close, sma200)
Buy Signal 6 (Low Above 50 SMA):
This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average.
buySignal6 = low > sma50
Buy Signal 7 (Accumulation Day):
An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation.
buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume
Buy Signal 8 (Higher High):
This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum.
buySignal8 = high > ta.highest(high, 14)
Buy Signal 9 (Key Reversal Bar):
This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish.
buySignal9 = open < low and close > high
Buy Signal 10 (Distribution Day Fall Off):
This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure.
buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25
Sell Signals (Decrease Exposure Score by -10%)
Sell Signal 1 (Cross Below 21 EMA):
This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend.
sellSignal1 = ta.crossunder(close, ema21)
Sell Signal 2 (Trending Below 21 EMA):
This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend.
sellSignal2 = ta.barssince(close >= ema21) > 5
Sell Signal 3 (Living Below 21 EMA):
This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend.
sellSignal3 = ta.barssince(close >= ema21) > 15
Sell Signal 4 (Cross Below 50 SMA):
This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend.
sellSignal4 = ta.crossunder(close, sma50)
Sell Signal 5 (Cross Below 200 SMA):
This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend.
sellSignal5 = ta.crossunder(close, sma200)
Sell Signal 6 (High Below 50 SMA):
This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal.
sellSignal6 = high < sma50
Sell Signal 7 (Distribution Day):
A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing.
sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume
Sell Signal 8 (Lower Low):
This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum.
sellSignal8 = low < ta.lowest(low, 14)
Sell Signal 9 (Downside Reversal Bar):
A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish.
sellSignal9 = open > high and close < low
Sell Signal 10 (Distribution Cluster):
This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure.
sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3
Theme Mode:
Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance.
Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals.
Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%.
Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis.
Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%.
Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral."
Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels.
Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value.
Inputs:
Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light."
Usage:
This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis.
The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure.
Important Considerations:
Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions.
Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe.
Disclaimer:
This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
JordanSwindenLibraryLibrary "JordanSwindenLibrary"
TODO: add library description here
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current decimal places on the market quote price
getPipSize(multiplier)
Calculates the pip size of the current market
Parameters:
multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)
Returns: The pip size for the current market
truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places
Parameters:
number (float) : The number to truncate
decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to
Returns: The given number truncated to the given decimalPlaces
toWhole(number)
Converts pips into whole numbers
Parameters:
number (float) : The pip number to convert into a whole number
Returns: The converted number
toPips(number)
Converts whole numbers back into pips
Parameters:
number (float) : The whole number to convert into pips
Returns: The converted number
getPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period
Parameters:
value1 (float) : The first value to reference
value2 (float) : The second value to reference
lookback (int) : The lookback period to analyze
Returns: The percent change over the two values and lookback period
random(minRange, maxRange)
Wichmann–Hill Pseudo-Random Number Generator
Parameters:
minRange (float) : The smallest possible number (default: 0)
maxRange (float) : The largest possible number (default: 1)
Returns: A random number between minRange and maxRange
bullFib(priceLow, priceHigh, fibRatio)
Calculates a bullish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
bearFib(priceLow, priceHigh, fibRatio)
Calculates a bearish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
getMA(length, maType)
Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)
Parameters:
length (simple int) : The MA period
maType (string) : The type of MA
Returns: A moving average with the given parameters
barsAboveMA(lookback, ma)
Counts how many candles are above the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to check
Returns: The bar count of how many recent bars are above the MA
barsBelowMA(lookback, ma)
Counts how many candles are below the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many recent bars are below the EMA
barsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently (based on closing prices)
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many times price recently crossed the EMA (based on closing prices)
getPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count)
Parameters:
lookback (int) : The lookback period to look back over
direction (int) : The color of the bar to count (1 = Green, -1 = Red)
Returns: The bar count of how many candles have retraced over the given lookback & direction
getBodySize()
Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getBottomWickSize()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBodyPercent()
Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage
isHammer(fib, colorMatch)
Checks if the current bar is a hammer candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(fib, colorMatch)
Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isDoji(wickSize, bodySize)
Checks if the current bar is a doji candle based on the given parameters
Parameters:
wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)
bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isBullishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bullish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle
isBearishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bearish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle
isInsideBar()
Detects inside bars
Returns: Returns true if the current bar is an inside bar
isOutsideBar()
Detects outside bars
Returns: Returns true if the current bar is an outside bar
barInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls within the given time session
barOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls outside the given time session
dateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range
Parameters:
startTime (int) : The UNIX date timestamp to begin searching from
endTime (int) : the UNIX date timestamp to stop searching from
Returns: A boolean - true if the current bar falls within the given dates
dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze
Parameters:
monday (bool) : Should the script analyze this day? (true/false)
tuesday (bool) : Should the script analyze this day? (true/false)
wednesday (bool) : Should the script analyze this day? (true/false)
thursday (bool) : Should the script analyze this day? (true/false)
friday (bool) : Should the script analyze this day? (true/false)
saturday (bool) : Should the script analyze this day? (true/false)
sunday (bool) : Should the script analyze this day? (true/false)
Returns: A boolean - true if the current bar's day is one of the given days
atrFilter(atrValue, maxSize)
Parameters:
atrValue (float)
maxSize (float)
tradeCount()
Calculate total trade count
Returns: Total closed trade count
isLong()
Check if we're currently in a long trade
Returns: True if our position size is positive
isShort()
Check if we're currently in a short trade
Returns: True if our position size is negative
isFlat()
Check if we're currentlyflat
Returns: True if our position size is zero
wonTrade()
Check if this bar falls after a winning trade
Returns: True if we just won a trade
lostTrade()
Check if this bar falls after a losing trade
Returns: True if we just lost a trade
maxDrawdownRealized()
Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
totalPipReturn()
Gets the total amount of pips won/lost (as a whole number)
Returns: Total amount of pips won/lost (as a whole number)
longWinCount()
Count how many winning long trades we've had
Returns: Long win count
shortWinCount()
Count how many winning short trades we've had
Returns: Short win count
longLossCount()
Count how many losing long trades we've had
Returns: Long loss count
shortLossCount()
Count how many losing short trades we've had
Returns: Short loss count
breakEvenCount(allowanceTicks)
Count how many break-even trades we've had
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even count
longCount()
Count how many long trades we've taken
Returns: Long trade count
shortCount()
Count how many short trades we've taken
Returns: Short trade count
longWinPercent()
Calculate win rate of long trades
Returns: Long win rate (0-100)
shortWinPercent()
Calculate win rate of short trades
Returns: Short win rate (0-100)
breakEvenPercent(allowanceTicks)
Calculate break even rate of all trades
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even win rate (0-100)
averageRR()
Calculate average risk:reward
Returns: Average winning trade divided by average losing trade
unitsToLots(units)
(Forex) Convert the given unit count to lots (multiples of 100,000)
Parameters:
units (float) : The units to convert into lots
Returns: Units converted to nearest lot size (as float)
getFxPositionSize(balance, risk, stopLossPips, fxRate, lots)
(Forex) Calculate fixed-fractional position size based on given parameters
Parameters:
balance (float) : The account balance
risk (float) : The % risk (whole number)
stopLossPips (float) : Pip distance to base risk on
fxRate (float) : The conversion currency rate (more info below in library documentation)
lots (bool) : Whether or not to return the position size in lots rather than units (true by default)
Returns: Units/lots to enter into "qty=" parameter of strategy entry function
EXAMPLE USAGE:
string conversionCurrencyPair = (strategy.account_currency == syminfo.currency ? syminfo.tickerid : strategy.account_currency + syminfo.currency)
float fx_rate = request.security(conversionCurrencyPair, timeframe.period, close )
if (longCondition)
strategy.entry("Long", strategy.long, qty=zen.getFxPositionSize(strategy.equity, 1, stopLossPipsWholeNumber, fx_rate, true))
skipTradeMonteCarlo(chance, debug)
Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation
Parameters:
chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)
debug (bool) : Whether or not to display a label informing of the trade skip
Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks)
fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)
This updates the given table's cell with the given values
Parameters:
tableID (table) : The table ID to update
column (int) : The column to update
row (int) : The row to update
title (string) : The title of this cell
value (string) : The value of this cell
bgcolor (color) : The background color of this cell
txtcolor (color) : The text color of this cell
tooltip (string)
Returns: Nothing.
Volume Spread Analysis [TANHEF]Volume Spread Analysis: Understanding Market Intentions through the Interpretation of Volume and Price Movements.
█ Simple Explanation:
The Volume Spread Analysis (VSA) indicator is a comprehensive tool that helps traders identify key market patterns and trends based on volume and spread data. This indicator highlights significant VSA patterns and provides insights into market behavior through color-coded volume/spread bars and identification of bars indicating strength, weakness, and neutrality between buyers and sellers. It also includes powerful volume and spread forecasting capabilities.
█ Laws of Volume Spread Analysis (VSA):
The origin of VSA begins with Richard Wyckoff, a pivotal figure in its development. Wyckoff made significant contributions to trading theory, including the formulation of three basic laws:
The Law of Supply and Demand: This fundamental law states that supply and demand balance each other over time. High demand and low supply lead to rising prices until demand falls to a level where supply can meet it. Conversely, low demand and high supply cause prices to fall until demand increases enough to absorb the excess supply.
The Law of Cause and Effect: This law assumes that a 'cause' will result in an 'effect' proportional to the 'cause'. A strong 'cause' will lead to a strong trend (effect), while a weak 'cause' will lead to a weak trend.
The Law of Effort vs. Result: This law asserts that the result should reflect the effort exerted. In trading terms, a large volume should result in a significant price move (spread). If the spread is small, the volume should also be small. Any deviation from this pattern is considered an anomaly.
█ Volume and Spread Analysis Bars:
Display: Volume and/or spread bars that consist of color coded levels. If both of these are displayed, the number of spread bars can be limited for visual appeal and understanding, with the spread bars scaled to match the volume bars. While automatic calculation of the number of visual bars for auto scaling is possible, it is avoided to prevent the indicator from reloading whenever the number of visual price bars on the chart is adjusted, ensuring uninterrupted analysis. A displayable table (Legend) of bar colors and levels can give context and clarify to each volume/spread bar.
Calculation: Levels are calculated using multipliers applied to moving averages to represent key levels based on historical data: low, normal, high, ultra. This method smooths out short-term fluctuations and focuses on longer-term trends.
Low Level: Indicates reduced volatility and market interest.
Normal Level: Reflects typical market activity and volatility.
High Level: Indicates increased activity and volatility.
Ultra Level: Identifies extreme levels of activity and volatility.
This illustrates the appearance of Volume and Spread bars when scaled and plotted together:
█ Forecasting Capabilities:
Display: Forecasted volume and spread levels using predictive models.
Calculation: Volume and Spread prediction calculations differ as volume is linear and spread is non-linear.
Volume Forecast (Linear Forecasting): Predicts future volume based on current volume rate and bar time till close.
Spread Forecast (Non-Linear Dynamic Forecasting): Predicts future spread using a dynamic multiplier, less near midpoint (consolidation) and more near low or high (trending), reflecting non-linear expansion.
Moving Averages: In forecasting, moving averages utilize forecasted levels instead of actual levels to ensure the correct level is forecasted (low, normal, high, or ultra).
The following compares forecasted volume with actual resulting volume, highlighting the power of early identifying increased volume through forecasted levels:
█ VSA Patterns:
Criteria and descriptions for each VSA pattern are available as tooltips beside them within the indicator’s settings. These tooltips provide explanations of potential developments based on the volume and spread data.
Signs of Strength (🟢): Patterns indicating strong buying pressure and potential market upturns.
Down Thrust
Selling Climax
No Effort → Bearish Result
Bearish Effort → No Result
Inverse Down Thrust
Failed Selling Climax
Bull Outside Reversal
End of Falling Market (Bag Holder)
Pseudo Down Thrust
No Supply
Signs of Weakness (🔴): Patterns indicating strong selling pressure and potential market downturns.
Up Thrust
Buying Climax
No Effort → Bullish Result
Bullish Effort → No Result
Inverse Up Thrust
Failed Buying Climax
Bear Outside Reversal
End of Rising Market (Bag Seller)
Pseudo Up Thrust
No Demand
Neutral Patterns (🔵): Patterns indicating market indecision and potential for continuation or reversal.
Quiet Doji
Balanced Doji
Strong Doji
Quiet Spinning Top
Balanced Spinning Top
Strong Spinning Top
Quiet High Wave
Balanced High Wave
Strong High Wave
Consolidation
Bar Patterns (🟡): Common candlestick patterns that offer insights into market sentiment. These are required in some VSA patterns and can also be displayed independently.
Bull Pin Bar
Bear Pin Bar
Doji
Spinning Top
High Wave
Consolidation
This demonstrates the acronym and descriptive options for displaying bar patterns, with the ability to hover over text to reveal the descriptive text along with what type of pattern:
█ Alerts:
VSA Pattern Alerts: Notifications for identified VSA patterns at bar close.
Volume and Spread Alerts: Alerts for confirmed and forecasted volume/spread levels (Low, High, Ultra).
Forecasted Volume and Spread Alerts: Alerts for forecasted volume/spread levels (High, Ultra) include a minimum percent time elapsed input to reduce false early signals by ensuring sufficient bar time has passed.
█ Inputs and Settings:
Display Volume and/or Spread: Choose between displaying volume bars, spread bars, or both with different lookback periods.
Indicator Bar Color: Select color schemes for bars (Normal, Detail, Levels).
Indicator Moving Average Color: Select schemes for bars (Fill, Lines, None).
Price Bar Colors: Options to color price bars based on VSA patterns and volume levels.
Legend: Display a table of bar colors and levels for context and clarity of volume/spread bars.
Forecast: Configure forecast display and prediction details for volume and spread.
Average Multipliers: Define multipliers for different levels (Low, High, Ultra) to refine the analysis.
Moving Average: Set volume and spread moving average settings.
VSA: Select the VSA patterns to be calculated and displayed (Strength, Weakness, Neutral).
Bar Patterns: Criteria for bar patterns used in VSA (Doji, Bull Pin Bar, Bear Pin Bar, Spinning Top, Consolidation, High Wave).
Colors: Set exact colors used for indicator bars, indicator moving averages, and price bars.
More Display Options: Specify how VSA pattern text is displayed (Acronym, Descriptive), positioning, and sizes.
Alerts: Configure alerts for VSA patterns, volume, and spread levels, including forecasted levels.
█ Usage:
The Volume Spread Analysis indicator is a helpful tool for leveraging volume spread analysis to make informed trading decisions. It offers comprehensive visual and textual cues on the chart, making it easier to identify market conditions, potential reversals, and continuations. Whether analyzing historical data or forecasting future trends, this indicator provides insights into the underlying factors driving market movements.
