DD RatioThe DD Ratio (“Directional Distribution Ratio”) is a breadth indicator that shows, in real time, how many of the selected stocks (e.g., S&P 500 components) are bullish vs. bearish relative to today’s open.
The DD Ratio tells you what’s really happening under the hood of the index:
Futures may mislead: An index future (like ES or NQ) can rise on a few heavy-weighted stocks even while most components fall.
The DD Ratio exposes that divergence.
Breadth confirmation: When the futures are up and DD Ratio ≥ 0.5 → healthy rally.
When futures are up but DD Ratio < 0.5 → weak, narrow advance.
Intraday sentiment gauge: It updates live with each bar, reflecting “who’s winning” since the open.
스크립트에서 "做空标普500"에 대해 찾기
Volume Area 80 Rule Pro - Adaptive RTHSummary in one paragraph
Adaptive value area 80 percent rule for index futures large cap equities liquid crypto and major FX on intraday timeframes. It focuses activity only when multiple context gates align. It is original because the classic prior day value area traverse is fused with a daily regime classifier that remaps the operating parameters in real time.
Scope and intent
• Markets. ES NQ SPY QQQ large cap equities BTC ETH major FX pairs and other liquid RTH instruments
• Timeframes. One minute to one hour with daily regime context
• Default demo used in the publication. ES1 on five minutes
• Purpose. Trade only the balanced days where the 80 percent traverse has edge while standing aside or tightening rules during trend or shock
Originality and usefulness
• Unique fusion. Prior day value area logic plus a rolling daily regime classifier using percentile ranks of realized volatility and ADX. The regime remaps hold time end of window stop buffer and value area coverage on each session
• Failure mode addressed. False starts during strong trend or shock sessions and weak traverses during quiet grind
• Testability. All gates are visible in Inputs and debug flags can be plotted so users can verify why a suggestion appears
• Portable yardstick. The regime uses ATR divided by close and ADX percent ranks which behave consistently across symbols
Method overview in plain language
The script builds the prior session profile during regular trading hours. At the first regular bar it freezes yesterday value area low value area high and point of control. It then evaluates the current session open location the first thirty minute volume rank the open gap rank and an opening drive test. In parallel a daily series classifies context into Calm Balance Trend or Shock from rolling percentile ranks of realized volatility and ADX. The classifier scales the rules. Calm uses longer holds and a slightly wider value area. Trend and Shock shorten the window reduce holds and enlarge stop buffers.
Base measures
• Range basis. True Range smoothed over a configurable length on both the daily and intraday series
• Return basis. Not required. ATR over close is the unit for regime strength
Components
• Prior Value Area Engine. Builds yesterday value area low value area high and point of control from a binned volume profile with automatic TPO fallback and minimum integrity guards
• Opening Location. Detects whether the session opens above the prior value area or below it
• Inside Hold Counter. Counts consecutive bars that hold inside the value area after a re entry
• Volume Gate. Percentile of the first thirty minutes volume over a rolling sample
• Gap Gate. Percentile rank of the regular session open gap over a rolling sample
• Drive Gate. Opening drive check using a multiple of intraday ATR
• Regime Classifier. Percentile ranks of daily ATR over close and daily ADX classify Calm Balance Trend Shock and remap parameters
• Session windows optional. Windows follow the chart exchange time
Fusion rule
Minimum satisfied gates approach. A re entry must hold inside the value area for a regime scaled number of bars while the volume gap and drive gates allow the setup. The regime simultaneously scales value area coverage end minute time stop and stop buffer.
Signal rule
• Long suggestion appears when price opens below yesterday value area then re enters and holds for the required bars while all gates allow the setup
• Short suggestion appears when price opens above yesterday value area then re enters and holds for the required bars while all gates allow the setup
• WAIT shows implicitly when any required gate is missing
• Exit labels mark target touch stop touch or a time based close
Inputs with guidance
Setup
• Signal timeframe. Uses the chart by default
• Session windows optional. Start and end minutes inside regular trading hours
• Invert direction is not used. The logic is symmetric
Logic
• Hold bars inside value area. Typical range 3 to 12. Raising it reduces trades and favors better traverses. Lowering it increases frequency and risk of false starts
• Earliest minute since RTH open and Latest minute since RTH open. Typical range 0 to 390. Reducing the latest minute cuts late session trades
• Time stop bars after entry. Typical range 6 to 30. Larger values give setups more room
Filters
• Value area coverage. Typical range 0.70 to 0.85. Higher coverage narrows the traverse but accepts fewer days
• Bin size in ticks. Typical range 1 to 8. Larger bins stabilize noisy profiles
• Stop buffer ticks beyond edge. Typical range 2 to 20. Larger buffers survive noise
• First thirty minute volume percentile. Typical range 0.30 to 0.70. Higher values require more active opens
• Gap filter percentile. Typical range 0.70 to 0.95. Lower values block more gap days
• Opening drive multiple and bars. Higher multiple or longer bars block strong directional opens
Adaptivity
• Lookback days for regime ranks. Typical 150 to 500
• Calm RV percentile. Typical 25 to 45
• Trend ADX percentile. Typical 55 to 75
• Shock RV percentile. Typical 75 to 90
• End minute ratio in Trend and Shock. Typical 0.5 to 0.8
• Hold and Time stop scales per regime. Use values near one to keep behavior close to static settings
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Sessions use the chart exchange time
Honest limitations and failure modes
• Economic releases and thin liquidity can break the balance premise
• Gap heavy symbols may work better with stronger gap filters and a True Range focus
• Very quiet regimes reduce signal contrast. Consider longer windows or higher thresholds
Legal
Education and research only. Not investment advice. Test in simulation before any live use.
VIX/VVIX Spike RiskVIX/VVIX Spike Risk Analyzer
The VIX/VVIX Spike Risk Analyzer analyzes historical VIX behavior under similar market conditions to forecast future VIX spike risk.
By combining current VIX and VVIX levels as dual filters, it identifies historical precedents and calculates the probability and magnitude of VIX spikes over the next 1, 5, and 10 trading days.
IMPORTANT: This indicator must be applied to the VIX chart (CBOE:VIX) to function correctly.
Methodology
1. Dual-Filter Pattern Matching
The indicator uses both VIX and VVIX as simultaneous filters to identify historically analogous market conditions:
By requiring BOTH metrics to match historical levels, the indicator creates more precise market condition filters than using VIX alone. This dual-filter approach significantly improves predictive accuracy because:
VIX alone might be at 15, but VVIX can tell us if that 15 is stable (low VVIX) or explosive (high VVIX)
High VVIX + Low VIX often precedes major spikes
Low VVIX + Low VIX suggests sustained calm
2. Tolerance Settings
VIX Matching (Default: ±10% Relative)
Uses relative percentage matching for consistency across different VIX regimes
Example: VIX at 15 matches 13.5-16.5 (±10%)
Can switch to absolute tolerance (±5 points) if preferred
VVIX Matching (Default: ±10 Points Absolute)
Uses absolute point matching as VVIX scales differently
Example: VVIX at 100 matches 90-110
Can switch to relative percentage if preferred
3. Historical Analysis Window
The indicator scans up to 500 bars backward (limited by VVIX data availability) to find all historical periods where both VIX and VVIX were at similar levels. Each match becomes a "sample" for statistical analysis.
4. Forward-Looking Spike Analysis
For each historical match, the indicator measures VIX behavior over the next 1, 5, and 10 days
Display Metrics Explained
Average Highest Spike
Shows the average of the maximum VIX spikes observed.
Highest Single Spike
Shows the single largest spike ever recorded
Probability No 10% Spike
Shows what percentage of historical cases stayed BELOW a 10% spike:
Probability No 20% Spike
Shows what percentage of historical cases stayed BELOW a 20% spike:
Note : You'll see many more shaded bars than the sample count because each match creates up to 5 consecutive shaded bars (bars 1-5 after the match all "look back" and see it).
Short Volatility Strategies:
Enter when there's a LOW probability of big vol spikes based on today's metrics
Long Volatility Strategies
Enter when there's a HIGH probability of big vol spikes based on today's metrics
3D Institutional Battlefield [SurgeGuru]Professional Presentation: 3D Institutional Flow Terrain Indicator
Overview
The 3D Institutional Flow Terrain is an advanced trading visualization tool that transforms complex market structure into an intuitive 3D landscape. This indicator synthesizes multiple institutional data points—volume profiles, order blocks, liquidity zones, and voids—into a single comprehensive view, helping you identify high-probability trading opportunities.
Key Features
🎥 Camera & Projection Controls
Yaw & Pitch: Adjust viewing angles (0-90°) for optimal perspective
Scale Controls: Fine-tune X (width), Y (depth), and Z (height) dimensions
Pro Tip: Increase Z-scale to amplify terrain features for better visibility
🌐 Grid & Surface Configuration
Resolution: Adjust X (16-64) and Y (12-48) grid density
Visual Elements: Toggle surface fill, wireframe, and node markers
Optimization: Higher resolution provides more detail but requires more processing power
📊 Data Integration
Lookback Period: 50-500 bars of historical analysis
Multi-Source Data: Combine volume profile, order blocks, liquidity zones, and voids
Weighted Analysis: Each data source contributes proportionally to the terrain height
How to Use the Frontend
💛 Price Line Tracking (Your Primary Focus)
The yellow price line is your most important guide:
Monitor Price Movement: Track how the yellow line interacts with the 3D terrain
Identify Key Levels: Watch for these critical interactions:
Order Blocks (Green/Red Zones):
When yellow price line enters green zones = Bullish order block
When yellow price line enters red zones = Bearish order block
These represent institutional accumulation/distribution areas
Liquidity Voids (Yellow Zones):
When yellow price line enters yellow void areas = Potential acceleration zones
Voids indicate price gaps where minimal trading occurred
Price often moves rapidly through voids toward next liquidity pool
Terrain Reading:
High Terrain Peaks: High volume/interest areas (support/resistance)
Low Terrain Valleys: Low volume areas (potential breakout zones)
Color Coding:
Green terrain = Bullish volume dominance
Red terrain = Bearish volume dominance
Purple = Neutral/transition areas
📈 Volume Profile Integration
POC (Point of Control): Automatically marks highest volume level
Volume Bins: Adjust granularity (10-50 bins)
Height Weight: Control how much volume affects terrain elevation
🏛️ Order Block Detection
Detection Length: 5-50 bar lookback for block identification
Strength Weighting: Recent blocks have greater impact on terrain
Candle Body Option: Use full candles or body-only for block definition
💧 Liquidity Zone Tracking
Multiple Levels: Track 3-10 key liquidity zones
Buy/Sell Side: Different colors for bid/ask liquidity
Strength Decay: Older zones have diminishing terrain impact
🌊 Liquidity Void Identification
Threshold Multiplier: Adjust sensitivity (0.5-2.0)
Height Amplification: Voids create significant terrain depressions
Acceleration Zones: Price typically moves quickly through void areas
Practical Trading Application
Bullish Scenario:
Yellow price line approaches green order block terrain
Price finds support in elevated bullish volume areas
Terrain shows consistent elevation through key levels
Bearish Scenario:
Yellow price line struggles at red order block resistance
Price falls through liquidity voids toward lower terrain
Bearish volume peaks dominate the landscape
Breakout Setup:
Yellow price line consolidates in flat terrain
Minimal resistance (low terrain) in projected direction
Clear path toward distant liquidity zones
Pro Tips
Start Simple: Begin with default settings, then gradually customize
Focus on Yellow Line: Your primary indicator of current price position
Combine Timeframes: Use the same terrain across multiple timeframes for confluence
Volume Confirmation: Ensure terrain peaks align with actual volume spikes
Void Anticipation: When price enters voids, prepare for potential rapid movement
Order Blocks & Voids Architecture
Order Blocks Calculation
Trigger: Price breaks fractal swing points
Bullish OB: When close > swing high → find lowest low in lookback period
Bearish OB: When close < swing low → find highest high in lookback period
Strength: Based on price distance from block extremes
Storage: Global array maintains last 50 blocks with FIFO management
Liquidity Voids Detection
Trigger: Price gaps exceeding ATR threshold
Bull Void: Low - high > (ATR200 × multiplier)
Bear Void: Low - high > (ATR200 × multiplier)
Validation: Close confirms gap direction
Storage: Global array maintains last 30 voids
Key Design Features
Real-time Updates: Calculated every bar, not just on last bar
Global Persistence: Arrays maintain state across executions
FIFO Management: Automatic cleanup of oldest entries
Configurable Sensitivity: Adjustable lookback periods and thresholds
Scientific Testing Framework
Hypothesis Testing
Primary Hypothesis: 3D terrain visualization improves detection of institutional order flow vs traditional 2D charts
Testable Metrics:
Prediction Accuracy: Does terrain structure predict future support/resistance?
Reaction Time: Faster identification of key levels vs conventional methods
False Positive Reduction: Lower rate of failed breakouts/breakdowns
Control Variables
Market Regime: Trending vs ranging conditions
Asset Classes: Forex, equities, cryptocurrencies
Timeframes: M5 to H4 for intraday, D1 for swing
Volume Conditions: High vs low volume environments
Data Collection Protocol
Terrain Features to Quantify:
Slope gradient changes at price inflection points
Volume peak clustering density
Order block terrain elevation vs subsequent price action
Void depth correlation with momentum acceleration
Control Group: Traditional support/resistance + volume profile
Experimental Group: 3D Institutional Flow Terrain
Statistical Measures
Signal-to-Noise Ratio: Terrain features vs random price movements
Lead Time: Terrain formation ahead of price confirmation
Effect Size: Performance difference between groups (Cohen's d)
Statistical Power: Sample size requirements for significance
Validation Methodology
Blind Testing:
Remove price labels from terrain screenshots
Have traders identify key levels from terrain alone
Measure accuracy vs actual price action
Backtesting Framework:
Automated terrain feature extraction
Correlation with future price reversals/breakouts
Monte Carlo simulation for significance testing
Expected Outcomes
If hypothesis valid:
Significant improvement in level prediction accuracy (p < 0.05)
Reduced latency in institutional level identification
Higher risk-reward ratios on terrain-confirmed trades
Research Questions:
Does terrain elevation reliably indicate institutional interest zones?
Are liquidity voids statistically significant momentum predictors?
Does multi-timeframe terrain analysis improve signal quality?
How does terrain persistence correlate with level strength?
LuxAlgo BigBeluga hapharmonic
Dual FUT/Spot price with next monthly expiryThis Pine Script dashboard indicator is specifically designed for pair trading strategies in Indian futures markets (NSE). Let me break down how it facilitates pair trading:
Core Pair Trading Concept
The script monitors two correlated stocks simultaneously (Symbol A and Symbol B), comparing their:
Spot prices vs Futures prices
Current month futures vs Next month futures
Premium/discount relationships
Key Pair Trading Features
1. Dual Symbol Monitoring
symbolA = "NSE:TCS" (Default)
symbolB = "NSE:INFY" (Default)
Allows traders to watch two stocks in the same sector (like TCS and Infosys in IT) to identify relative value opportunities.
2. Basis Analysis for Each Stock
The indicator calculates the basis (difference between futures and spot):
Price Difference: FUT - SPOT
Premium/Discount %: ((FUT - SPOT) / SPOT) × 100
This helps identify when one stock's futures are relatively more expensive than the other's.
3. Multi-Expiry View
Near Month Futures (1!): Current active contract
Next Month Futures (2!): Upcoming contract
This enables calendar spread analysis within each stock and helps anticipate rollover effects.
4. Comparative Table
The detailed table displays side-by-side:
Symbol Spot Price Near Future Near Diff (%)Next Monthly Next Diff (%)Lot SizeTCS₹3,500₹3,520+20 (+0.57%)₹3,535+35 (+1.00%)125INFY₹1,450₹1,455+5 (+0.34%)₹1,460+10 (+0.69%)600
5. Lot Size Integration
Critical for position sizing in pair trades - the indicator fetches actual contract lot sizes, enabling proper hedge ratio calculations.
Pair Trading Strategies Enabled
Strategy 1: Basis Divergence Trading
When TCS futures trade at +0.8% premium and INFY at +0.2%
Trade: Short TCS futures, Long INFY futures (betting on convergence)
The indicator highlights these differences with color-coded cells
Strategy 2: Calendar Spread Arbitrage
Compare near month vs next month premium for each stock
If TCS shows wider calendar spread than INFY, potential arbitrage exists
Trade the relative calendar spread difference
Strategy 3: Premium/Discount Reversal
Monitor which stock moves from premium to discount (or vice versa)
Color indicators (green/red) make this immediately visible
Enter pairs when relative premium relationships normalize
Strategy 4: Lot-Adjusted Pair Trading
Use lot size data to create market-neutral positions
Example: If TCS lot = 125 and INFY lot = 600
Ratio = 600/125 = 4.8:1 for rupee-neutral positioning
Visual Trading Cues
Green cells: Futures at premium (contango)
Red cells: Futures at discount (backwardation)
Purple values: Next month contracts
Yellow highlights: Spot prices
Practical Pair Trading Example
Scenario: Both stocks in same sector, historically correlated
Normal state: Both show +0.5% premium
Divergence: TCS jumps to +1.2%, INFY stays at +0.5%
Trade Signal:
Short TCS futures (expensive)
Long INFY futures (relatively cheap)
Exit: When premiums converge back to similar levels
Hedge ratio: Use lot sizes to maintain proper exposure balance
Advantages for Pair Traders
✓ Single-screen monitoring of both legs
✓ Real-time basis calculations eliminate manual math
✓ Multi-timeframe view (near + next month)
✓ Automatic lot size fetching for position sizing
✓ Visual alerts through color coding
✓ Percentage normalization for easy comparison
This indicator essentially transforms raw price data into actionable pair trading intelligence by highlighting relative value discrepancies between correlated assets in the futures market.
Enjoy!!
[Parth🇮🇳] Wall Street US30 Pro - Prop Firm Edition....Yo perfect! Here's the COMPLETE strategy in simple words:
***
## WALL STREET US30 TRADING STRATEGY - SIMPLE VERSION
### WHAT YOU'RE TRADING:
US30 (Dow Jones Index) on 1-hour chart using a professional indicator with smart money concepts.
---
### WHEN TO TRADE:
**6:30 PM - 10:00 PM IST every day** (London-NY overlap = highest volume)
***
### THE INDICATOR SHOWS YOU:
A table in top-right corner with 5 things:
1. **Signal Strength** - How confident (need 70%+)
2. **RSI** - Momentum (need OK status)
3. **MACD** - Trend direction (need UP for buys, DOWN for sells)
4. **Volume** - Real or fake move (need HIGH)
5. **Trend** - Overall direction (need UP for buys, DOWN for sells)
Plus **green arrows** (buy signals) and **red arrows** (sell signals).
---
### THE RULES:
**When GREEN ▲ arrow appears:**
- Wait for 1-hour candle to close (don't rush in)
- Check the table:
- Signal Strength 70%+ ? ✅
- Volume HIGH? ✅
- RSI okay? ✅
- MACD up? ✅
- Trend up? ✅
- If all yes = ENTER LONG (BUY)
- Set stop loss 40-50 pips below entry
- Set take profit 2x the risk (2:1 ratio)
**When RED ▼ arrow appears:**
- Wait for 1-hour candle to close (don't rush in)
- Check the table:
- Signal Strength 70%+ ? ✅
- Volume HIGH? ✅
- RSI okay? ✅
- MACD down? ✅
- Trend down? ✅
- If all yes = ENTER SHORT (SELL)
- Set stop loss 40-50 pips above entry
- Set take profit 2x the risk (2:1 ratio)
***
### REAL EXAMPLE:
**7:45 PM IST - Green arrow appears**
Table shows:
- Signal Strength: 88% 🔥
- RSI: 55 OK
- MACD: ▲ UP
- Volume: 1.8x HIGH
- Trend: 🟢 UP
All checks pass ✅
**8:00 PM - Candle closes, signal confirmed**
I check table again - still strong ✓
**I enter on prop firm:**
- BUY 0.1 lot
- Entry: 38,450
- Stop Loss: 38,400 (50 pips below)
- Take Profit: 38,550 (100 pips above)
- Risk: $50
- Reward: $100
- Ratio: 1:2 ✅
**9:30 PM - Price hits 38,550**
- Take profit triggered ✓
- +$100 profit
- Trade closes
**Done for that signal!**
***
### YOUR DAILY ROUTINE:
**6:30 PM IST** - Open TradingView + prop firm
**6:30 PM - 10 PM IST** - Watch for signals
**When signal fires** - Check table, enter if strong
**10:00 PM IST** - Close all trades, done
**Expected daily** - 1-3 signals, +$100-300 profit
***
### EXPECTED RESULTS:
**Win Rate:** 65-75% (most trades win)
**Signals per day:** 1-3
**Profit per trade:** $50-200
**Daily profit:** $100-300
**Monthly profit:** $2,000-6,000
**Monthly return:** 20-30% (on $10K account)
---
### WHAT MAKES THIS WORK:
✅ Uses 7+ professional filters (not just 1 indicator)
✅ Checks volume (real moves only)
✅ Filters overbought/oversold (avoids tops/bottoms)
✅ Aligns with 4-hour trend (higher timeframe)
✅ Only trades peak volume hours (6:30-10 PM IST)
✅ Uses support/resistance (institutional levels)
✅ Risk/reward 2:1 minimum (math works out)
***
### KEY DISCIPLINE RULES:
**DO:**
- ✅ Only trade 6:30-10 PM IST
- ✅ Wait for candle to close
- ✅ Check ALL 5 table items
- ✅ Only take 70%+ strength signals
- ✅ Always use stop loss
- ✅ Always 2:1 reward ratio
- ✅ Risk 1-2% per trade
- ✅ Close all trades by 10 PM
- ✅ Journal every trade
- ✅ Follow the plan
**DON'T:**
- ❌ Trade outside 6:30-10 PM IST
- ❌ Enter before candle closes
- ❌ Take weak signals (below 70%)
- ❌ Trade without stop loss
- ❌ Move stop loss (lock in loss)
- ❌ Hold overnight
- ❌ Revenge trade after losses
- ❌ Overleverge (more than 0.1 lot start)
- ❌ Skip journaling
- ❌ Deviate from plan
***
### THE 5-STEP ENTRY PROCESS:
**Step 1:** Arrow appears on chart ➜
**Step 2:** Wait for candle to close ➜
**Step 3:** Check table (all 5 items) ➜
**Step 4:** If all good = go to prop firm ➜
**Step 5:** Enter trade with SL & TP
Takes 30 seconds once you practice!
***
### MONEY MATH (Starting with $5,000):
**If you take 20 signals per month:**
- Win 15, Lose 5 (75% rate)
- Wins: 15 × $100 = $1,500
- Losses: 5 × $50 = -$250
- Net: +$1,250/month = 25% return
**Month 2:** $5,000 + $1,250 = $6,250 account
**Month 3:** $6,250 + $1,562 = $7,812 account
**Month 4:** $7,812 + $1,953 = $9,765 account
**Month 5:** $9,765 + $2,441 = $12,206 account
**Month 6:** $12,206 + $3,051 = $15,257 account
**In 6 months = $10,000 account → $15,000+ (50% growth)**
That's COMPOUNDING, baby! 💰
***
### START TODAY:
1. Copy indicator code
2. Add to 1-hour US30 chart on TradingView
3. Wait until 6:30 PM IST tonight (or tomorrow if late)
4. Watch for signals
5. Follow the rules
6. Trade your prop firm
**That's it! Simple as that!**
***
### FINAL WORDS:
This isn't get-rich-quick. This is build-wealth-steadily.
You follow the plan, take quality signals only, manage risk properly, you WILL make money. Not every trade wins, but the winners are bigger than losers (2:1 ratio).
Most traders fail because they:
- Trade too much (overtrading)
- Don't follow their plan (emotions)
- Risk too much per trade (blown account)
- Chase signals (FOMO)
- Don't journal (repeat mistakes)
You avoid those 5 things = you'll be ahead of 95% of traders.
**Start trading 6:30 PM IST. Let's go! 🚀**
TLP Swing Chart V2// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// Sửa đổi trên code gốc của © meomeo105
// © meomeo105
//@version=5
indicator('TLP Swing Chart V2', shorttitle='TLP Swing V2', overlay=true, max_lines_count=500)
//-----Input-------
customTF = input.timeframe(defval="",title = "Show Other TimeFrame")
showTLP = input.bool(false, 'Show TLP', inline = "TLP1")
colorTLP = input.color(color.aqua, '', inline = "TLP1")
showSTLP = input.bool(true, 'Show TLP Swing', inline = "Swing1")
colorSTLP = input.color(color.aqua, '', inline = "Swing1")
showLabel = input.bool(true, 'Show Label TimeFrame')
lineSTLP = input.string(title="",options= ,defval="(─)", inline = "Swing1")
lineStyleSTLP = lineSTLP == "(┈)" ? line.style_dotted : lineSTLP == "(╌)" ? line.style_dashed : line.style_solid
//IOSB
IOSB = "TLPInOutSideBarSetting"
ISB = input(true,group =IOSB, title="showISB")
colorISB = input.color(color.rgb(250, 171, 0), inline = "ISB")
OSB = input(true,group =IOSB, title="showOSB")
colorOSB = input.color(color.rgb(56, 219, 255), inline = "OSB")
ZoneColor = input(defval = color.new(color.orange, 90),group =IOSB, title = "Background Color")
BorderColor = input(defval = color.new(color.orange, 100),group =IOSB, title = "Border Color")
/////////////////
var aCZ = array.new_float(0)
float highest = high
float lowest = low
if (array.size(aCZ) > 0)
highest := array.get(aCZ, 0)
lowest := array.get(aCZ, 1)
insideBarCondtion = low >= lowest and low <= highest and high >= lowest and high <= highest
if ( insideBarCondtion == true )
array.push(aCZ, high )
array.push(aCZ, low )
if( array.size(aCZ) >= 2 and insideBarCondtion == false )
float maxCZ = array.max(aCZ)
float minCZ = array.min(aCZ)
box.new(bar_index - (array.size(aCZ) / 2) - 1, maxCZ, bar_index - 1, minCZ, bgcolor = ZoneColor, border_color = BorderColor)
array.clear(aCZ)
//////////////////////////Global//////////////////////////
var arrayLineTemp = array.new_line()
// Funtion
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1. / 60. :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 1440. :
timeframe.isweekly ? 10080. :
timeframe.ismonthly ? 43800. : na)
// Converts a resolution expressed in minutes into a string usable by "security()"
f_resFromMinutes(_minutes) =>
_minutes < 1 ? str.tostring(math.round(_minutes*60)) + "S" :
_minutes < 60 ? str.tostring(math.round(_minutes)) + "m" :
_minutes < 1440 ? str.tostring(math.round(_minutes/60)) + "H" :
_minutes < 10080 ? str.tostring(math.round(math.min(_minutes / 1440, 7))) + "D" :
_minutes < 43800 ? str.tostring(math.round(math.min(_minutes / 10080, 4))) + "W" :
str.tostring(math.round(math.min(_minutes / 43800, 12))) + "M"
f_tfRes(_res,_exp) =>
request.security(syminfo.tickerid,_res,_exp,lookahead=barmerge.lookahead_on)
var label labelError = label.new(bar_index, high, text = "", color = #00000000, textcolor = color.white,textalign = text.align_left)
sendError(_mmessage) =>
label.set_xy(labelError, bar_index + 3, close )
label.set_text(labelError, _mmessage)
var arrayLineChoCh = array.new_line()
var label labelTF = label.new(time, close, text = "",color = color.new(showSTLP ? colorSTLP : colorTLP,95), textcolor = showSTLP ? colorSTLP : colorTLP,xloc = xloc.bar_time, textalign = text.align_left)
//////////////////////////TLP//////////////////////////
var arrayXTLP = array.new_int(5,time)
var arrayYTLP = array.new_float(5,close)
var arrayLineTLP = array.new_line()
int drawLineTLP = 0
_high = high
_low = low
_close = close
_open = open
if(customTF != timeframe.period)
_high := f_tfRes(customTF,high)
_low := f_tfRes(customTF,low)
_close := f_tfRes(customTF,close)
_open := f_tfRes(customTF,open)
highPrev = _high
lowPrev = _low
// drawLineTLP => 2:Tiếp tục 1:Đảo chiều; // Outsidebar 2:Tiếp tục 3:Tiếp tục và Đảo chiều 4 : Đảo chiều 2 lần
drawLineTLP := 0
if(_high > highPrev and _low > lowPrev )
if(array.get(arrayYTLP,0) > array.get(arrayYTLP,1))
if(_high <= high)
array.set(arrayXTLP, 0, time)
array.set(arrayYTLP, 0, _high )
drawLineTLP := 2
else
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_high )
drawLineTLP := 1
else if(_high < highPrev and _low < lowPrev )
if(array.get(arrayYTLP,0) > array.get(arrayYTLP,1))
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_low )
drawLineTLP := 1
else
if(_low >= low)
array.set(arrayXTLP, 0, time)
array.set(arrayYTLP, 0, _low )
drawLineTLP := 2
else if(_high >= highPrev and _low < lowPrev or _high > highPrev and _low <= lowPrev )
if(array.get(arrayYTLP,0) > array.get(arrayYTLP,1))
if(_high >= array.get(arrayYTLP,0) and array.get(arrayYTLP,1) < _low )
if(_high <= high)
array.set(arrayXTLP, 0, time)
array.set(arrayYTLP, 0, _high )
drawLineTLP := 2
else if(_high >= array.get(arrayYTLP,0) and array.get(arrayYTLP,1) > _low )
if(_close < _open)
if(_high <= high)
array.set(arrayXTLP, 0, time)
array.set(arrayYTLP, 0, _high )
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_low )
drawLineTLP := 3
else
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_low )
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_high )
drawLineTLP := 4
else if(array.get(arrayYTLP,0) < array.get(arrayYTLP,1))
if(_low <= array.get(arrayYTLP,0) and _high < array.get(arrayYTLP,1))
if(_low >= low)
array.set(arrayXTLP, 0, time)
array.set(arrayYTLP, 0, _low )
drawLineTLP := 2
else if(_low <= array.get(arrayYTLP,0) and _high > array.get(arrayYTLP,1))
if(_close > _open)
if(_low >= low)
array.set(arrayXTLP, 0, time)
array.set(arrayYTLP, 0, _low )
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_high )
drawLineTLP := 3
else
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_high )
array.unshift(arrayXTLP,time)
array.unshift(arrayYTLP,_low )
drawLineTLP := 4
else if((_high <= highPrev and _low >= lowPrev ))
highPrev := highPrev
lowPrev := lowPrev
if(f_resInMinutes() < f_tfRes(customTF,f_resInMinutes()) and drawLineTLP == 0)
if(array.get(arrayYTLP,0) > array.get(arrayYTLP,1))
if(array.get(arrayYTLP,0) <= high)
array.set(arrayXTLP, 0, time)
drawLineTLP := 2
else
if(array.get(arrayYTLP,0) >= low)
array.set(arrayXTLP, 0, time)
drawLineTLP := 2
if((showSTLP or showTLP) and f_resInMinutes() <= f_tfRes(customTF,f_resInMinutes()))
if(drawLineTLP == 2)
if(array.size(arrayLineTLP) >0)
line.set_xy2(array.get(arrayLineTLP,0),array.get(arrayXTLP,0),array.get(arrayYTLP,0))
else
array.unshift(arrayLineTLP,line.new(array.get(arrayXTLP,1),array.get(arrayYTLP,1),array.get(arrayXTLP,0),array.get(arrayYTLP,0), color = colorTLP,xloc = xloc.bar_time, style = lineStyleSTLP))
else if(drawLineTLP == 1)
array.unshift(arrayLineTLP,line.new(array.get(arrayXTLP,1),array.get(arrayYTLP,1),array.get(arrayXTLP,0),array.get(arrayYTLP,0), color = colorTLP,xloc = xloc.bar_time, style = lineStyleSTLP))
else if(drawLineTLP == 3)
if(array.size(arrayLineTLP) >0)
line.set_xy2(array.get(arrayLineTLP,0),array.get(arrayXTLP,1),array.get(arrayYTLP,1))
else
array.unshift(arrayLineTLP,line.new(array.get(arrayXTLP,2),array.get(arrayYTLP,2),array.get(arrayXTLP,1),array.get(arrayYTLP,1), color = colorTLP,xloc = xloc.bar_time, style = lineStyleSTLP))
array.unshift(arrayLineTLP,line.new(array.get(arrayXTLP,1),array.get(arrayYTLP,1),array.get(arrayXTLP,0),array.get(arrayYTLP,0), color = colorTLP,xloc = xloc.bar_time, style = lineStyleSTLP))
else if(drawLineTLP == 4)
array.unshift(arrayLineTLP,line.new(array.get(arrayXTLP,2),array.get(arrayYTLP,2),array.get(arrayXTLP,1),array.get(arrayYTLP,1), color = colorTLP,xloc = xloc.bar_time, style = lineStyleSTLP))
array.unshift(arrayLineTLP,line.new(array.get(arrayXTLP,1),array.get(arrayYTLP,1),array.get(arrayXTLP,0),array.get(arrayYTLP,0), color = colorTLP,xloc = xloc.bar_time, style = lineStyleSTLP))
//////////////////////////Swing TLP//////////////////////////
var arrayXSTLP = array.new_int(5,time)
var arrayYSTLP = array.new_float(5,close)
var arrayLineSTLP = array.new_line()
int drawLineSTLP = 0
int drawLineSTLP1 = 0
if(showSTLP)
if(math.max(array.get(arrayYSTLP,0),array.get(arrayYSTLP,1)) < math.min(array.get(arrayYTLP,0),array.get(arrayYTLP,1)) or math.min(array.get(arrayYSTLP,0),array.get(arrayYSTLP,1)) > math.max(array.get(arrayYTLP,0),array.get(arrayYTLP,1)))
//Khởi tạo bắt đầu
drawLineSTLP1 := 5
array.set(arrayXSTLP, 0, array.get(arrayXTLP,1))
array.set(arrayYSTLP, 0, array.get(arrayYTLP,1))
array.unshift(arrayXSTLP,array.get(arrayXTLP,0))
array.unshift(arrayYSTLP,array.get(arrayYTLP,0))
// drawLineSTLP kiểm tra điểm 1 => 13:Tiếp tục có sóng hồi // 12|19(reDraw):Tiếp tục không có sóng hồi // 14:Đảo chiều
if(array.get(arrayXTLP,0) == array.get(arrayXTLP,1))
if(array.get(arrayXSTLP,0) >= array.get(arrayXTLP,2) and array.get(arrayYSTLP,0) != array.get(arrayYTLP,1) and ((array.get(arrayYTLP,1) > array.get(arrayYTLP,2) and array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1)) or (array.get(arrayYTLP,1) < array.get(arrayYTLP,2) and array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1))))
drawLineSTLP1 := 12
array.set(arrayXSTLP, 0, array.get(arrayXTLP,1))
array.set(arrayYSTLP, 0, array.get(arrayYTLP,1))
else if(array.get(arrayXSTLP,0) <= array.get(arrayXTLP,2))
if((array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1) and array.get(arrayYTLP,1) < array.get(arrayYSTLP,1)) or (array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1) and array.get(arrayYTLP,1) > array.get(arrayYSTLP,1)))
drawLineSTLP1 := 14
array.unshift(arrayXSTLP,array.get(arrayXTLP,1))
array.unshift(arrayYSTLP,array.get(arrayYTLP,1))
else if((array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1) and array.get(arrayYTLP,1) > array.get(arrayYSTLP,0)) or (array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1) and array.get(arrayYTLP,1) < array.get(arrayYSTLP,0)))
drawLineSTLP1 := 13
_max = math.min(array.get(arrayYSTLP,0),array.get(arrayYSTLP,1))
_min = math.max(array.get(arrayYSTLP,0),array.get(arrayYSTLP,1))
_max_idx = 0
_min_idx = 0
for i = 2 to array.size(arrayXTLP)
if(array.get(arrayXSTLP,0) >= array.get(arrayXTLP,i))
break
if(_min > array.get(arrayYTLP,i))
_min := array.get(arrayYTLP,i)
_min_idx := array.get(arrayXTLP,i)
if(_max < array.get(arrayYTLP,i))
_max := array.get(arrayYTLP,i)
_max_idx := array.get(arrayXTLP,i)
if(array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1))
array.unshift(arrayXSTLP,_min_idx)
array.unshift(arrayYSTLP,_min)
else if(array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1))
array.unshift(arrayXSTLP,_max_idx)
array.unshift(arrayYSTLP,_max)
array.unshift(arrayXSTLP,array.get(arrayXTLP,1))
array.unshift(arrayYSTLP,array.get(arrayYTLP,1))
if(f_resInMinutes() < f_tfRes(customTF,f_resInMinutes()))
if(array.get(arrayYSTLP,0) == array.get(arrayYTLP,1) and array.get(arrayXSTLP,0) != array.get(arrayXTLP,1))
array.set(arrayXSTLP, 0, array.get(arrayXTLP,1))
drawLineSTLP1 := 19
if(f_resInMinutes() <= f_tfRes(customTF,f_resInMinutes()))
if(drawLineSTLP1 == 12 or drawLineSTLP1 == 19)
if(array.size(arrayLineSTLP) >0)
line.set_xy2(array.get(arrayLineSTLP,0),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0))
else
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
else if(drawLineSTLP1 == 14)
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
else if(drawLineSTLP1 == 13)
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,2),array.get(arrayYSTLP,2),array.get(arrayXSTLP,1),array.get(arrayYSTLP,1), color = colorSTLP,xloc = xloc.bar_time))
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
else if(drawLineSTLP1 == 15)
if(array.size(arrayLineSTLP) >0)
line.set_xy2(array.get(arrayLineSTLP,0),array.get(arrayXSTLP,1),array.get(arrayYSTLP,1))
else
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,2),array.get(arrayYSTLP,2),array.get(arrayXSTLP,1),array.get(arrayYSTLP,1), color = colorSTLP,xloc = xloc.bar_time))
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
// drawLineSTLP kiểm tra điểm 0 => 3:Tiếp tục có sóng hồi // 2|9(reDraw):Tiếp tục không có sóng hồi // 4:Đảo chiều
if(array.get(arrayXSTLP,0) >= array.get(arrayXTLP,1) and array.get(arrayYSTLP,0) != array.get(arrayYTLP,0) and ((array.get(arrayYTLP,0) > array.get(arrayYTLP,1) and array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1)) or (array.get(arrayYTLP,0) < array.get(arrayYTLP,1) and array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1))))
drawLineSTLP := 2
array.set(arrayXSTLP, 0, array.get(arrayXTLP,0))
array.set(arrayYSTLP, 0, array.get(arrayYTLP,0))
else if(array.get(arrayXSTLP,0) <= array.get(arrayXTLP,1))
if((array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1) and array.get(arrayYTLP,0) < array.get(arrayYSTLP,1)) or (array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1) and array.get(arrayYTLP,0) > array.get(arrayYSTLP,1)))
drawLineSTLP := 4
array.unshift(arrayXSTLP,array.get(arrayXTLP,0))
array.unshift(arrayYSTLP,array.get(arrayYTLP,0))
else if((array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1) and array.get(arrayYTLP,0) > array.get(arrayYSTLP,0)) or (array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1) and array.get(arrayYTLP,0) < array.get(arrayYSTLP,0)))
drawLineSTLP := 3
_max = math.min(array.get(arrayYSTLP,0),array.get(arrayYSTLP,1))
_min = math.max(array.get(arrayYSTLP,0),array.get(arrayYSTLP,1))
_max_idx = 0
_min_idx = 0
for i = 1 to array.size(arrayXTLP)
if(array.get(arrayXSTLP,0) >= array.get(arrayXTLP,i))
break
if(_min > array.get(arrayYTLP,i))
_min := array.get(arrayYTLP,i)
_min_idx := array.get(arrayXTLP,i)
if(_max < array.get(arrayYTLP,i))
_max := array.get(arrayYTLP,i)
_max_idx := array.get(arrayXTLP,i)
if(array.get(arrayYSTLP,0) > array.get(arrayYSTLP,1))
array.unshift(arrayXSTLP,_min_idx)
array.unshift(arrayYSTLP,_min)
else if(array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1))
array.unshift(arrayXSTLP,_max_idx)
array.unshift(arrayYSTLP,_max)
array.unshift(arrayXSTLP,array.get(arrayXTLP,0))
array.unshift(arrayYSTLP,array.get(arrayYTLP,0))
if(f_resInMinutes() < f_tfRes(customTF,f_resInMinutes()))
if(array.get(arrayYSTLP,0) == array.get(arrayYTLP,0) and array.get(arrayXSTLP,0) != array.get(arrayXTLP,0))
array.set(arrayXSTLP, 0, array.get(arrayXTLP,0))
drawLineSTLP := 9
if(f_resInMinutes() <= f_tfRes(customTF,f_resInMinutes()))
if(drawLineSTLP == 2 or drawLineSTLP == 9)
if(array.size(arrayLineSTLP) >0)
line.set_xy2(array.get(arrayLineSTLP,0),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0))
else
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
else if(drawLineSTLP == 4)
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
else if(drawLineSTLP == 3)
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,2),array.get(arrayYSTLP,2),array.get(arrayXSTLP,1),array.get(arrayYSTLP,1), color = colorSTLP,xloc = xloc.bar_time))
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
else if(drawLineSTLP == 5)
if(array.size(arrayLineSTLP) >0)
line.set_xy2(array.get(arrayLineSTLP,0),array.get(arrayXSTLP,1),array.get(arrayYSTLP,1))
else
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,2),array.get(arrayYSTLP,2),array.get(arrayXSTLP,1),array.get(arrayYSTLP,1), color = colorSTLP,xloc = xloc.bar_time))
array.unshift(arrayLineSTLP,line.new(array.get(arrayXSTLP,1),array.get(arrayYSTLP,1),array.get(arrayXSTLP,0),array.get(arrayYSTLP,0), color = colorSTLP,xloc = xloc.bar_time))
///////////////////////Other//////////////////////////////////
if(f_resInMinutes() <= f_tfRes(customTF,f_resInMinutes()))
if(showSTLP)
if(showLabel and (barstate.islast or barstate.islastconfirmedhistory))
texLabel = f_resInMinutes() == f_tfRes(customTF,f_resInMinutes()) ? f_resFromMinutes(f_resInMinutes()) : f_resFromMinutes(f_tfRes(customTF,f_resInMinutes()))
label.set_xy(labelTF,array.get(arrayXSTLP,0),array.get(arrayYSTLP,0))
label.set_text(labelTF,texLabel)
label.set_style(labelTF,array.get(arrayYSTLP,0) < array.get(arrayYSTLP,1) ? label.style_label_upper_right : label.style_label_lower_right)
if(not showTLP)
arrayLineTemp := array.copy(arrayLineTLP)
for itemArray in arrayLineTemp
if(line.get_x1(itemArray) < array.get(arrayXSTLP,0))
line.delete(itemArray)
array.remove(arrayLineTLP,array.indexof(arrayLineTLP, itemArray))
//Inside Bars - Outside Bars
insideBar() => ISB and high <= high and low >= low ? 1 : 0
outsideBar() => OSB and (high > high and low < low ) ? 1 : 0
//Inside and Outside Bars
barcolor(insideBar() ? color.new(colorISB,0) : na )
barcolor(outsideBar() ? color.new(colorOSB,0) : na )
Multi-TF Gates (Labels + Alerts)//@version=6
indicator("PO9 – Multi-TF Gates (Labels + Alerts)", overlay=true, max_lines_count=500)
iYear=input.int(2024,"Anchor Year",minval=1970)
iMonth=input.int(11,"Anchor Month",minval=1,maxval=12)
iDay=input.int(6,"Anchor Day",minval=1,maxval=31)
useSymbolTZ=input.bool(true,"Use symbol's exchange timezone (syminfo.timezone)")
tzChoice=input.string("Etc/UTC","Custom timezone (if not using symbol TZ)",options= )
anchorType=input.string("FX NY 17:00","Anchor at",options= )
showEvery=input.int(9,"Mark every Nth candle",minval=1)
showD=input.bool(true,"Show Daily")
show3H=input.bool(true,"Show 3H")
show1H=input.bool(true,"Show 1H")
show15=input.bool(true,"Show 15M")
show5=input.bool(false,"Show 5M (optional)")
colD=input.color(color.new(color.red,0),"Daily color")
col3H=input.color(color.new(color.orange,0),"3H color")
col1H=input.color(color.new(color.yellow,0),"1H color")
col15=input.color(color.new(color.teal,0),"15M color")
col5=input.color(color.new(color.gray,0),"5M color")
styStr=input.string("dashed","Line style",options= )
lnW=input.int(2,"Line width",minval=1,maxval=4)
extendTop=input.float(1.5,"ATR multiples above high",minval=0.1)
extendBottom=input.float(1.5,"ATR multiples below low",minval=0.1)
showLabels=input.bool(true,"Show labels")
enableAlerts=input.bool(true,"Enable alerts")
f_style(s)=>s=="solid"?line.style_solid:s=="dashed"?line.style_dashed:line.style_dotted
var lines=array.new_line()
f_prune(maxKeep)=>
if array.size(lines)>maxKeep
old=array.shift(lines)
line.delete(old)
tzEff=useSymbolTZ?syminfo.timezone:tzChoice
anchorTs=anchorType=="FX NY 17:00"?timestamp("America/New_York",iYear,iMonth,iDay,17,0):timestamp(tzEff,iYear,iMonth,iDay,0,0)
atr=ta.atr(14)
f_vline(_color,_tf,_idx)=>
y1=low-atr*extendBottom
y2=high+atr*extendTop
lid=line.new(x1=bar_index,y1=y1,x2=bar_index,y2=y2,xloc=xloc.bar_index,extend=extend.none,color=_color,style=f_style(styStr),width=lnW)
if showLabels
label.new(x=bar_index,y=high+(atr*2),text=_tf+" #"+str.tostring(_idx),xloc=xloc.bar_index,style=label.style_label_down,color=_color,textcolor=color.black)
array.push(lines,lid)
is_tf_open(tf)=> time==request.security(syminfo.tickerid,tf,time,barmerge.gaps_off,barmerge.lookahead_off)
f_tf(_tf,_show,_color,_name)=>
var bool started=false
var int idx=0
isOpen=_show and is_tf_open(_tf)
firstBar=isOpen and (time>=anchorTs) and (nz(time ,time)
Best Time Slots — Auto-Adapt (v6, TF-safe) + Range AlertsTime & binning
Auto-adapt to timeframe
Makes all time windows scale to your chart’s bar size (so it “just works” on 1m, 15m, 4H, Daily).
• On = recommended. • Off = fixed default lengths.
Minimum Bin (minutes)
The size of each daily time slot we track (e.g., 5-min bins). The script uses the larger of this and your bar size.
• Higher = fewer, broader slots; smoother stats. • Lower = more, narrower slots; needs more history.
• Try: 5–15 on intraday, 60–240 on higher TFs.
Lookback windows (used when Auto-adapt = ON)
Target ER Window (minutes)
How far back we look to judge Efficiency Ratio (how “straight” the move was).
• Higher = stricter/smoother; fewer bars qualify as “movement”. • Lower = more sensitive.
• Try: 60–120 min intraday; 240–600 min for higher TFs.
Target ATR Window (minutes)
How far back we compute ATR (typical range).
• Higher = steadier ATR baseline. • Lower = reacts faster.
• Try: 30–120 min intraday; 240–600 min higher TFs.
Target Normalization Window (minutes)
How far back for the average ATR (the baseline we compare to).
• Higher = stricter “above average range” check. • Lower = easier to pass.
• Try: ~500–1500 min.
What counts as “movement”
ER Threshold (0–1)
Minimum efficiency a bar must have to count as movement.
• Higher = only very “clean, one-direction” bars count. • Lower = more bars count.
• Try: 0.55–0.65. (0.60 = balanced.)
ATR Floor vs SMA(ATR)
Requires range to be at least this many × average ATR.
• Higher (e.g., 1.2) = demand bigger-than-usual ranges. • Lower (e.g., 0.9) = allow smaller ranges.
• Try: 1.0 (above average).
How history is averaged
Recent Days Weight (per-day decay)
Gives more weight to recent days. Example: 0.97 ≈ each day old counts ~3% less.
• Higher (0.99) = slower fade (older days matter more). • Lower (0.95) = faster fade.
• Try: 0.97–0.99.
Laplace Prior Seen / Laplace Prior Hit
“Starter counts” so early stats aren’t crazy when you have little data.
• Higher priors = probabilities start closer to average; need more real data to move.
• Try: Seen=3, Hit=1 (defaults).
Min Samples (effective)
Don’t highlight a slot unless it has at least this many effective samples (after decay + priors).
• Higher = safer, but fewer highlights early.
• Try: 3–10.
When to highlight on the chart
Min Probability to Highlight
We shade/mark bars only if their slot’s historical movement probability is ≥ this.
• Higher = pickier, fewer highlights. • Lower = more highlights.
• Try: 0.45–0.60.
Show Markers on Good Bins
Draws a small square on bars that fall in a “good” slot (in addition to the soft background).
Limit to market hours (optional)
Restrict to Session + Session
Only learn/score inside this time window (e.g., “0930-1600”). Uses the chart/exchange timezone.
• Turn on if you only care about RTH.
Range (chop) alerts
Range START if ER ≤
Triggers range when efficiency drops below this level (price starts zig-zagging).
• Higher = easier to call “range”. • Lower = stricter.
Range START if ATR ≤ this × SMA(ATR)
Also triggers range when ATR shrinks below this fraction of its average (volatility contraction).
• Higher (e.g., 1.0) = stricter (must be at/under average). • Lower (e.g., 0.9) = easier to call range.
Alerts on bar close
If ON, alerts fire once per bar close (cleaner). If OFF, they can trigger intrabar (faster, noisier).
Quick “what happens if I change X?”
Want more highlighted times? ↓ Min Probability, ↓ ER Threshold, or ↓ ATR Floor (e.g., 0.9).
Want stricter highlights? ↑ Min Probability, ↑ ER Threshold, or ↑ ATR Floor (e.g., 1.2).
Want recent days to matter more? ↑ Recent Days Weight toward 0.99.
On 4H/Daily, widen Minimum Bin (e.g., 60–240) and maybe lower Min Probability a bit.
OPADA//@version=5
indicator("Buy/Sell Zones – TV Style", overlay=true, timeframe="", timeframe_gaps=true)
//=====================
// الإعدادات
//=====================
len = input.int(100, "Length", minval=10)
useATR = input.bool(true, "Use ATR (بدل الانحراف المعياري)")
mult = input.float(2.0, "Band Multiplier", step=0.1)
useRSI = input.bool(true, "تفعيل فلتر RSI")
rsiOB = input.int(70, "RSI Overbought", minval=50, maxval=90)
rsiOS = input.int(30, "RSI Oversold", minval=10, maxval=50)
//=====================
// القناة: أساس + انحراف
//=====================
basis = ta.linreg(close, len, 0)
off = useATR ? ta.atr(len) * mult : ta.stdev(close, len) * mult
upper = basis + off
lower = basis - off
// نطاق علوي/سفلي بعيد لعمل تعبئة المناطق
lookback = math.min(bar_index, 500)
topBand = ta.highest(high, lookback) + 50 * syminfo.mintick
bottomBand = ta.lowest(low, lookback) - 50 * syminfo.mintick
//=====================
// الرسم
//=====================
pUpper = plot(upper, "Upper", color=color.new(color.blue, 0), linewidth=1)
pLower = plot(lower, "Lower", color=color.new(color.red, 0), linewidth=1)
pBasis = plot(basis, "Basis", color=color.new(color.gray, 60), linewidth=2)
// تعبئة المناطق: فوق القناة (أزرق)، تحت القناة (أحمر)
pTop = plot(topBand, display=display.none)
pBottom = plot(bottomBand, display=display.none)
fill(pUpper, pTop, color=color.new(color.blue, 80)) // منطقة مقاومة/بيع
fill(pBottom, pLower, color=color.new(color.red, 80)) // منطقة دعم/شراء
//=====================
// خط أفقي من قمّة قريبة (يمثل مقاومة) – قريب من الخط المنقّط في الصورة
//=====================
resLen = math.round(len * 0.6)
dynRes = ta.highest(high, resLen)
plot(dynRes, "Recent Resistance", color=color.new(color.white, 0), linewidth=1)
//=====================
// إشارات BUY / SELL + فلتر RSI (اختياري)
//=====================
rsi = ta.rsi(close, 14)
touchLower = ta.crossover(close, lower) or close <= lower
touchUpper = ta.crossunder(close, upper) or close >= upper
buyOK = useRSI ? (touchLower and rsi <= rsiOS) : touchLower
sellOK = useRSI ? (touchUpper and rsi >= rsiOB) : touchUpper
plotshape(buyOK, title="BUY", location=location.belowbar, style=shape.labelup,
text="BUY", color=color.new(color.green, 0), textcolor=color.white, size=size.tiny, offset=0)
plotshape(sellOK, title="SELL", location=location.abovebar, style=shape.labeldown,
text="SELL", color=color.new(color.red, 0), textcolor=color.white, size=size.tiny, offset=0)
// تنبيهات
alertcondition(buyOK, title="BUY", message="BUY signal: price touched/closed below lower band (RSI filter may apply).")
alertcondition(sellOK, title="SELL", message="SELL signal: price touched/closed above upper band (RSI filter may apply).")
Buy/Sell Zones – TV Style//@version=5
indicator("Buy/Sell Zones – TV Style", overlay=true, timeframe="", timeframe_gaps=true)
//=====================
// الإعدادات
//=====================
len = input.int(100, "Length", minval=10)
useATR = input.bool(true, "Use ATR (بدل الانحراف المعياري)")
mult = input.float(2.0, "Band Multiplier", step=0.1)
useRSI = input.bool(true, "تفعيل فلتر RSI")
rsiOB = input.int(70, "RSI Overbought", minval=50, maxval=90)
rsiOS = input.int(30, "RSI Oversold", minval=10, maxval=50)
//=====================
// القناة: أساس + انحراف
//=====================
basis = ta.linreg(close, len, 0)
off = useATR ? ta.atr(len) * mult : ta.stdev(close, len) * mult
upper = basis + off
lower = basis - off
// نطاق علوي/سفلي بعيد لعمل تعبئة المناطق
lookback = math.min(bar_index, 500)
topBand = ta.highest(high, lookback) + 50 * syminfo.mintick
bottomBand = ta.lowest(low, lookback) - 50 * syminfo.mintick
//=====================
// الرسم
//=====================
pUpper = plot(upper, "Upper", color=color.new(color.blue, 0), linewidth=1)
pLower = plot(lower, "Lower", color=color.new(color.red, 0), linewidth=1)
pBasis = plot(basis, "Basis", color=color.new(color.gray, 60), linewidth=2)
// تعبئة المناطق: فوق القناة (أزرق)، تحت القناة (أحمر)
pTop = plot(topBand, display=display.none)
pBottom = plot(bottomBand, display=display.none)
fill(pUpper, pTop, color=color.new(color.blue, 80)) // منطقة مقاومة/بيع
fill(pBottom, pLower, color=color.new(color.red, 80)) // منطقة دعم/شراء
//=====================
// خط أفقي من قمّة قريبة (يمثل مقاومة) – قريب من الخط المنقّط في الصورة
//=====================
resLen = math.round(len * 0.6)
dynRes = ta.highest(high, resLen)
plot(dynRes, "Recent Resistance", color=color.new(color.white, 0), linewidth=1)
//=====================
// إشارات BUY / SELL + فلتر RSI (اختياري)
//=====================
rsi = ta.rsi(close, 14)
touchLower = ta.crossover(close, lower) or close <= lower
touchUpper = ta.crossunder(close, upper) or close >= upper
buyOK = useRSI ? (touchLower and rsi <= rsiOS) : touchLower
sellOK = useRSI ? (touchUpper and rsi >= rsiOB) : touchUpper
plotshape(buyOK, title="BUY", location=location.belowbar, style=shape.labelup,
text="BUY", color=color.new(color.green, 0), textcolor=color.white, size=size.tiny, offset=0)
plotshape(sellOK, title="SELL", location=location.abovebar, style=shape.labeldown,
text="SELL", color=color.new(color.red, 0), textcolor=color.white, size=size.tiny, offset=0)
// تنبيهات
alertcondition(buyOK, title="BUY", message="BUY signal: price touched/closed below lower band (RSI filter may apply).")
alertcondition(sellOK, title="SELL", message="SELL signal: price touched/closed above upper band (RSI filter may apply).")
HalfTrend Adaptive Pro v3half trend version 3.1//@version=6
indicator("Candlestick Recognizer v1 (Praveen Edition)", overlay=true, max_labels_count=500)
// ──────────────────────────────
// Inputs: toggles & thresholds
// ──────────────────────────────
grpUse = "Enable Patterns"
useEngulf = input.bool(true, "Engulfing (Bull/Bear)", group=grpUse)
usePiercing = input.bool(true, "Piercing Line / Dark Cloud", group=grpUse)
useMarubozu = input.bool(true, "Marubozu (Bull/Bear)", group=grpUse)
useHammers = input.bool(true, "Hammer / Hanging Man", group=grpUse)
useInverted = input.bool(true, "Inverted Hammer / Shooting Star", group=grpUse)
useDoji = input.bool(true, "Doji", group=grpUse)
useStars = input.bool(true, "Morning/Evening Star", group=grpUse)
useThree = input.bool(true, "Three Soldiers / Three Crows", group=grpUse)
grpThr = "Thresholds"
minBodyPct = input.float(0.6, "Min Body vs Range (0-1) for 'strong body'", step=0.05, group=grpThr)
maxDojiBodyPct = input.float(0.1, "Max Body vs Range (0-1) for Doji", step=0.02, group=grpThr)
minEngulfFactor = input.float(1.02, "Engulf body size factor", step=0.01, group=grpThr)
wickRatioHammer = input.float(2.0, "Hammer lower wick ≥ body ×", step=0.1, group=grpThr)
wickRatioShooting = input.float(2.0, "Shooting Star upper wick ≥ body ×", step=0.1, group=grpThr)
gapTolerance = input.float(0.15, "Star gap tolerance as % of ATR", step=0.01, group=grpThr)
grpVis = "Visuals"
showLabels = input.bool(true, "Show Labels", group=grpVis)
labelSize = input.string("normal", "Label Size", options= , group=grpVis)
onlyConfirmed = input.bool(true, "Only on bar close (confirmed)", group=grpVis)
// Colors
bullCol = color.new(color.green, 0)
bearCol = color.new(color.red, 0)
warnCol = color.new(color.yellow, 0)
textCol = color.black
// Helper to gate by confirmation
confirmed = onlyConfirmed ? barstate.isconfirmed : true
// ──────────────────────────────
// Candle math helpers
// ──────────────────────────────
body(o, c) => math.abs(c - o)
range(h, l) => h - l
isBull(o, c) => c > o
isBear(o, c) => c < o
upperW(h, o, c) => h - math.max(o, c)
lowerW(l, o, c) => math.min(o, c) - l
safeDiv(x, y) => y == 0.0 ? 0.0 : x / y
// Current and previous (p1, p2)
o = open, c = close, h = high, l = low
o1 = open , c1 = close , h1 = high , l1 = low
o2 = open , c2 = close , h2 = high , l2 = low
b = body(o, c)
r = range(h, l)
ub = upperW(h, o, c)
lb = lowerW(l, o, c)
b1 = body(o1, c1)
r1 = range(h1, l1)
b2 = body(o2, c2)
r2 = range(h2, l2)
bull = isBull(o, c)
bear = isBear(o, c)
bull1 = isBull(o1, c1)
bear1 = isBear(o1, c1)
bull2 = isBull(o2, c2)
bear2 = isBear(o2, c2)
bodyVsRange = safeDiv(b, r)
bodyVsRange1 = safeDiv(b1, r1)
bodyVsRange2 = safeDiv(b2, r2)
atr = ta.atr(14)
// ──────────────────────────────
/* Pattern logic */
// ──────────────────────────────
// 1) Engulfing
bullEngulf = useEngulf and confirmed and bear1 and bull and (b >= b1 * minEngulfFactor) and (o <= c1) and (c >= o1)
bearEngulf = useEngulf and confirmed and bull1 and bear and (b >= b1 * minEngulfFactor) and (o >= c1) and (c <= o1)
// 2) Piercing Line / Dark Cloud Cover
piercing = usePiercing and confirmed and bear1 and bull and c > (o1 + c1)/2 and o <= l1 + (h1 - l1)*0.25 // open near/below prior low, close into upper half
darkCloud = usePiercing and confirmed and bull1 and bear and c < (o1 + c1)/2 and o >= h1 - (h1 - l1)*0.25 // open near/above prior high, close into lower half
// 3) Marubozu (strong body, tiny wicks)
maruBull = useMarubozu and confirmed and bull and bodyVsRange >= minBodyPct and ub <= b * 0.1 and lb <= b * 0.1
maruBear = useMarubozu and confirmed and bear and bodyVsRange >= minBodyPct and ub <= b * 0.1 and lb <= b * 0.1
// 4) Hammer / Hanging Man (small body, long lower wick)
hammer = useHammers and confirmed and bull and lb >= b * wickRatioHammer and ub <= b * 0.5
hangingMan = useHammers and confirmed and bear and lb >= b * wickRatioHammer and ub <= b * 0.5
// 5) Inverted Hammer / Shooting Star (small body, long upper wick)
invHammer = useInverted and confirmed and bull and ub >= b * wickRatioShooting and lb <= b * 0.5
shootingStar = useInverted and confirmed and bear and ub >= b * wickRatioShooting and lb <= b * 0.5
// 6) Doji
doji = useDoji and confirmed and bodyVsRange <= maxDojiBodyPct
// 7) Morning Star
TFRSI & RSI Analog Dial [CHE] TFRSI & RSI Analog Dial — Interactive analog visualization for TFRSI or RSI with gradient zones, radial markers, and a trailing hand pointer.
Summary
This indicator renders an interactive analog dial for either TFRSI or standard RSI, providing a visual gauge with gradient-filled zones for oversold, neutral, and overbought regions. The hand pointer tracks the current value, with optional trailing dots at recent positions to show momentum direction. Radial lines mark key thresholds, and a digital readout displays the exact value. This design enhances readability over linear plots by leveraging familiar clock-like intuition, reducing cognitive load during quick scans. Signals are robust due to clamping to safe bounds and mode-specific scaling, ensuring consistent display across different volatility regimes.
Motivation: Why this design?
Traditional linear RSI or momentum indicators often feel abstract, especially in fast-paced screening where users scan multiple assets. Sharp swings can make thresholds hard to gauge at a glance, leading to missed nuances in overbought or oversold conditions. This dial addresses that by mapping values to a curved scale with color gradients, making extremes visually pop while the hand's trail hints at recent path without cluttering the chart. The dual-mode support allows seamless switching between advanced momentum (TFRSI) and classic RSI, fitting diverse strategies without reloading scripts.
What’s different vs. standard approaches?
- Baseline reference: Diverges from linear plotlines like the built-in RSI oscillator, which stacks values vertically and relies on horizontal lines for thresholds.
- Architecture differences:
- Curved projection with perspective tilt for depth illusion, using polyline arcs instead of straight plots.
- Mode-aware clamping and scaling to handle TFRSI's extended range versus RSI's standard bounds.
- Persistent trail array for hand history, capped at three points to avoid performance drag.
- Gradient segmentation for smooth zone transitions, rendered via multiple thin polylines.
- Practical effect: Charts show a compact, rotatable dial that fits in pane corners, with colors intuitively signaling bias (lime for buy zones, red for sell). The trail adds qualitative flow without numerical overload, helping spot divergences faster than static bars.
How it works (technical)
The indicator first computes the selected metric: for TFRSI, it processes price accelerations through a multi-step filter involving differencing, exponential damping, and normalization to a centered scale; for RSI, it uses the standard gain-loss ratio over the specified period. The value is then clamped between mode-specific minimum and maximum bounds to prevent display overflow.
This clamped value drives the hand angle on a 300-degree arc, projected from a 3D-like model rotated for perspective. Arcs for zones are built as segmented polylines, with colors interpolated linearly across the gradient. Key levels are drawn as radial lines from inner to outer radius, colored by zone. The trail maintains up to three prior angles in an array, updated only on confirmed bars to avoid repainting, and rendered as sized dots fading from small to large.
Initialization seeds filter states to zero on first bar, with persistent variables holding smoothing history. Data flows from price to metric computation, clamping, angle mapping, and projection—all executed globally on the last bar for redraw efficiency.
Parameter Guide
Mode — Switches between TFRSI (extended momentum gauge) and RSI (classic oscillator); affects bounds, zones, and labels. Default: "TFRSI". Trade-offs: TFRSI adds sensitivity to accelerations but may amplify noise; RSI is more stable for trend confirmation.
Dial Size — Sets radius in pixels, scaling all elements proportionally. Default: 200. Bounds: 50–500. Tips: Larger for detailed views, smaller for multi-pane layouts; auto-scales hand length to match.
Dial Vertical Offset — Shifts entire dial up/down in pixels. Default: 0. Bounds: -200–200. Trade-offs: Negative pulls toward price action; positive spaces below—use to avoid overlap.
Camera Angle — Tilts view from top-down (0) to side (90) for 3D effect. Default: 45. Bounds: 0–90. Tips: Steeper angles emphasize depth but compress horizontally; flat for precision.
Resolution — Polygon sides for smooth arcs. Default: 64. Bounds: 4–64. Trade-offs: Higher reduces jaggedness but increases draw calls—balance with pane zoom.
TFRSI Hand Length — Base pointer length at 200px dial, auto-scaled. Default: 170. Bounds: 10–200. Tips: Longer for emphasis in large dials; shorter avoids edge clipping.
Show TFRSI Hand — Toggles pointer visibility. Default: true. Trade-offs: Off for clean zones only; on for value tracking.
Show Hand Trail Dots — Displays 3 fading dots at recent tips. Default: true. Trade-offs: Adds motion context but may clutter static views—disable in alerts.
TFRSI Hand Color — Pointer hue, used for trail dots too. Default: 7E57C2. Tips: Match strategy theme; gradients auto-blend to zones.
Dial Base Color — Arc outline/fill tint. Default: blue. Trade-offs: Opaque for contrast; transparent blends with background.
Neutral Color (50) — Mid-zone shade. Default: gray. Tips: Neutral tones reduce bias in balanced markets.
Oversold Color — Low-zone fill. Default: lime. Trade-offs: Bright for alerts; muted for subtlety.
Overbought Color — High-zone fill. Default: red. Trade-offs: As above—pair with hand blending.
Label Size — Text scaling for thresholds. Default: "normal". Options: tiny/small/normal/large/huge. Tips: Smaller for dense charts; larger for presentations.
Digital TFRSI Size — Readout font. Default: "large". Options: as above. Trade-offs: Balances visibility without dominating dial.
Digital Vertical Offset — Readout position shift. Default: -50. Bounds: -200–200. Tips: Negative centers above dial; adjust for multi-indicators.
TFRSI Length — Core lookback for accelerations. Default: 6. Min: 1. Trade-offs: Shorter heightens reactivity, risks whipsaws; longer smooths extremes.
TFRSI Trigger Length — Final smoothing passes. Default: 2. Min: 1. Tips: Increase for fewer false crosses; decrease for quicker pivots.
RSI Length — Period for gain-loss averaging. Default: 14. Min: 1. Trade-offs: Classic 14 balances; shorter for scalps, longer for swings.
Reading & Interpretation
The dial arcs sweep from overbought (right, red) through neutral (top, gray) to oversold (left, lime), with the hand pointing to the current value—clockwise for rising, counterclockwise for falling. Trail dots grow larger toward the present, colored to match hand zones, indicating recent direction without numbers. Threshold lines thicken at center (50) for quick zeroing; labels confirm levels. Digital readout below shows precise value prefixed by mode. Hand color gradients from neutral to extremes signal building pressure verbally: deepening red warns of potential pullbacks, brightening lime suggests bounces.
Practical Workflows & Combinations
Trend following: Enter long when hand crosses above 50 from oversold trail; confirm with higher highs in price structure. Filter shorts below 50 in downtrends using volume spikes.
Exits/Stops: Trail stops to recent dot positions in overbought; tighten on red gradients exceeding thresholds. Conservative: Exit at neutral; aggressive: Hold to extremes if trail aligns with momentum.
Multi-asset/Multi-TF: Defaults suit forex/stocks on 1H–4H; for crypto, shorten lengths by 20% for volatility. Stack with HTF security calls (e.g., daily mode on 15m chart) for confluence—watch for alignment across dials.
Behavior, Constraints & Performance
Closed-bar updates ensure no repainting; live bars show provisional hand/trail, confirmed on close. No security or HTF calls, so zero lookahead bias. Resources: Caps at 500 lines/labels/polylines, rebuilds only on last bar; max_bars_back=2000 handles history without lag. Known limits: Trail may stutter in flat markets; gradients approximate smooth fills via segments, visible at low resolution.
Sensible Defaults & Quick Tuning
Start with TFRSI mode, length=6, trigger=2 for responsive momentum on daily charts. Too choppy? Bump trigger to 4 for stability. Lagging entries? Drop length to 4, watch for overreactions. For RSI trend filter, set length=21; combine with MA cross for entries when dial nears 30/70.
What this indicator is—and isn’t
This is a visualization layer for momentum gauges, aiding quick bias assessment and threshold spotting. Pair it with price action, volume, and risk rules for decisions. It’s not a standalone signal generator or predictive tool—values reflect past data, prone to whipsaws in ranging conditions.
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
3D Session Clock | Live Time with Sessions [CHE] 3D Session Clock | Live Time with Sessions — Projects a perspective clock face onto the chart to display current time and market session periods for enhanced situational awareness during trading hours.
Summary
This indicator renders a three-dimensional clock projection directly on the price chart, showing analog hands for hours, minutes, and seconds alongside a digital time readout. It overlays session arcs for major markets like New York, London, Tokyo, and Sydney, highlighting the active one with thicker lines and contrasting labels. By centralizing time and session visibility, it reduces the need to reference external clocks, allowing traders to maintain focus on price action while noting overlaps or transitions that influence volatility.
The design uses perspective projection to simulate depth, making the clock appear tilted for better readability on varying chart scales. Sessions are positioned radially outward from the main clock, with the current time marker pulsing on the relevant arc. This setup provides a static yet live-updating view, confirmed on bar close to avoid intrabar shifts.
Motivation: Why this design?
Traders often miss subtle session shifts amid fast-moving charts, leading to entries during low-liquidity periods or exits before peak activity. Standard chart tools lack integrated time visualization, forcing constant tab-switching. This indicator addresses that by embedding a customizable clock with session rings, ensuring time context is always in view without disrupting workflow.
What’s different vs. standard approaches?
- Reference baseline: Traditional session highlighters use simple background fills or vertical lines, which clutter the chart and ignore global time zones.
- Architecture differences:
- Perspective projection rotates and scales points to mimic 3D depth, unlike flat 2D drawings.
- Nested radial arcs for sessions, with dynamic radius assignment to avoid overlap.
- Live time calculation adjusted for user-selected time zones, including optional daylight savings offset.
- Practical effect: The tilted view prevents labels from bunching at chart edges, and active session emphasis draws the eye to liquidity hotspots, making multi-session overlaps immediately apparent for better timing.
How it works (technical)
The indicator calculates current time in the selected time zone by adjusting the system timestamp with a fixed offset, plus an optional one-hour bump for daylight savings. This yields hour, minute, and second values that drive hand positions: the hour hand advances slowly with fractional minute input, the minute hand ticks per 60 seconds, and the second hand sweeps fully each minute.
Points for the clock face and arcs are generated as arrays of coordinates, transformed via rotation around the x-axis to apply tilt, then projected onto chart space using a scaling factor based on depth. Radial lines mark every hour from zero to 23, extending to the outermost session ring. Session arcs span user-defined hour ranges, drawn as open polylines with step interpolation for smoothness.
On the last bar, all prior drawings are cleared, and new elements are added: filled clock circles, hand lines from center to tip, a small orbiting circle at the current time position, and centered labels for hours, sessions, and time. The active session is identified by checking if the current time falls within its range, then its arc thickens and label inverts colors. Initialization populates a timezone array once, with persistent bar time tracking for horizontal positioning.
Parameter Guide
Clock Size — Controls overall radius in pixels, affecting visibility on dense charts — Default: 200 — Larger values suit wide screens but may crowd small views; start smaller for mobile.
Camera Angle — Sets tilt from top-down (zero) to side (90 degrees), altering projection depth — Default: 45 — Steeper angles enhance readability on sloped trends but flatten at extremes.
Resolution — Defines polygon sides for circles and arcs, balancing smoothness and draw calls — Default: 64 — Higher improves curves on large clocks; lower aids performance on slow devices.
Hour/Minute/Second Hand Length — Scales each hand from center, with seconds longest for precision — Defaults: 100/150/180 — Proportional sizing prevents overlap; shorten for compact layouts.
Clock Base Color — Tints face and frame — Default: blue — Neutral shades reduce eye strain; match chart theme.
Hand Colors — Assigns distinct hues to each hand — Defaults: red/green/yellow — High contrast aids quick scans; avoid chart-matching to stand out.
Hour Label Size — Text scale for 1-12 markers — Default: normal — Larger for distant views, but risks clutter.
Digital Time Size — Scale for HH:MM:SS readout — Default: large — Matches clock for balance; tiny for minimalism.
Digital Time Vertical Offset — Shifts readout up (negative) or down — Default: -50 — Positions above clock to avoid hand interference.
Timezone — Selects reference city/offset — Default: New York (UTC-05) — Matches trading locale; verify offsets manually.
Summer Time (DST) — Adds one hour if active — Default: false — Enable for regions observing it; test transitions.
Show/Label/Session/Color for Each Market — Toggles arc, sets name, time window, and hue per session (New York/London/Tokyo/Sydney) — Defaults: true/"New York"/1300-2200/orange, etc. — Customize windows to local exchange hours; colors differentiate overlaps.
Reading & Interpretation
The analog face shows a blue-tinted circle with white 1-12 labels and gray hour ticks; hands extend from center in assigned colors, pointing to current positions. A white dot with orbiting ring marks exact time on the session arc. Digital readout below displays padded HH:MM:SS in white on black.
Active sessions glow with bold arcs and white labels on colored backgrounds; inactive ones use thin lines and colored text on light fills. Overlaps stack outward, with the innermost (New York) closest to the clock. If no session is active, the marker sits on the base ring.
Practical Workflows & Combinations
- Trend following: Enter longs during London-New York overlap (thicker dual arcs) confirmed by higher highs; filter with volume spikes.
- Exits/Stops: Tighten stops pre-Tokyo open if arc thickens, signaling volatility ramp; trail during Sydney for overnight holds.
- Multi-asset/Multi-TF: Defaults work across forex/stocks; on higher timeframes, enlarge clock size to counter bar spacing. Pair with session volume oscillators for confirmation.
Behavior, Constraints & Performance
Rendering occurs only on the last bar, using confirmed history for stable display; live bars update hands and marker without repainting prior elements. No security calls or higher timeframe fetches, so no lookahead bias.
Resource limits include 2000 bars back for positioning, 500 each for lines, labels, and boxes—sufficient for full sessions without overflow. Arrays hold timezone data statically. On very wide charts, projection may skew slightly due to fixed scale.
Known limits: Visual positioning drifts on extreme zooms; daylight savings assumes manual toggle, risking one-hour errors during changes.
Sensible Defaults & Quick Tuning
Start with New York timezone, 45-degree tilt, and all sessions enabled—these balance global coverage without clutter. For too-small visibility, bump clock size to 300 and resolution to 48. If labels overlap on narrow views, reduce hand lengths proportionally. To emphasize one session (e.g., London), disable others and widen its color contrast. For minimalism, set digital size to small and offset to -100.
What this indicator is—and isn’t
This is a visual time and session overlay to contextualize trading windows, not a signal generator or predictive tool. It complements price analysis and risk rules but requires manual interpretation. Use alongside order flow or momentum indicators for decisions.
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
Acknowledgments
This indicator draws inspiration from the open-source contributions of the TradingView community, whose advanced programming techniques have greatly influenced its development. Special thanks to LonesomeTheBlue for the innovative polyline handling and midpoint centering techniques in RSI Radar Multi Time Frame:
Gratitude also extends to LuxAlgo for the precise timezone calculations in Sessions:
Finally, appreciation to TradingView for their comprehensive documentation on polyline features, including the support article at www.tradingview.com and the blog post at www.tradingview.com These resources were instrumental in implementing smooth, dynamic drawings.
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
ProScalper📊 ProScalper - Professional 1-Minute Scalping System
🎯 Overview
ProScalper is a sophisticated, multi-confluence scalping indicator designed specifically for 1-minute chart trading. Combining advanced technical analysis with intelligent signal filtering, it provides high-probability trade setups with clear entry, stop loss, and take profit levels.
✨ Key Features
🔺 Smart Signal Detection
Range Filter Technology: Fast-responding trend detection (25-period) optimized for 1-minute timeframe
Medium-sized triangles appear above/below candles for clear buy/sell signals
Only most recent signal shown - no chart clutter
Automatically deletes old signals when new ones appear
📋 Real-Time Signal Table
Top-center display shows complete trade breakdown
Grade system: A+, A, B+, B, C+ ratings for every setup
All confluence reasons listed with checkmarks
Score and R:R displayed for instant trade quality assessment
Color-coded: Green for LONG, Red for SHORT
📐 Multi-Confluence Analysis
ProScalper combines 10+ technical factors:
✅ EMA Trend: 4 EMAs (200, 48, 13, 8) for multi-timeframe alignment
✅ VWAP: Dynamic support/resistance
✅ Fibonacci Retracement: Golden ratio (61.8%), 50%, 38.2%, 78.6%
✅ Range Filter: Adaptive trend confirmation
✅ Pivot Points: Smart reversal detection
✅ Volume Analysis: Spike detection and volume profile
✅ Higher Timeframe: 5-minute trend confirmation
✅ HTF Support/Resistance: Key levels from higher timeframes
✅ Liquidity Sweeps: Smart money detection
✅ Opening Range Breakout: First 15-minute range
💰 Complete Trade Management
Entry Lines: Dashed green (LONG) or red (SHORT) showing exact entry
Stop Loss: Red dashed line with price label
Take Profit: Blue dashed line with price label and R:R
Partial Exits: 1R level marked with orange dashed line
All lines extend 10 bars for clean alignment with Fibonacci levels
📊 Dynamic Risk/Reward
Adaptive R:R calculation based on market volatility
Targets adjusted for pivot distances
Minimum 1.2:1 to maximum 3.5:1 for scalping
Position sizing based on account risk percentage
🎨 Professional Visualization
Clean chart layout - no clutter, only essential information
Custom EMA colors: Red (200), Aqua (48), Green (13), White (8)
Gold VWAP line for key support/resistance
Color-coded Fibonacci: Bright yellow (61.8%), white (50%), orange (38.2%), fuchsia (78.6%)
No shaded zones - pure price action focus
📈 Performance Tracking
Real-time statistics table (optional)
Win rate, total trades, P&L tracking
Average R:R and win/loss ratios
Setup-specific performance metrics
⚙️ Settings & Customization
Risk Management
Adjustable account risk per trade (default: 0.5%)
ATR-based stop loss multiplier (default: 0.8 for tight scalping)
Dynamic position sizing
Signal Sensitivity
Confluence Score Threshold: 40-100 (default: 55 for balanced signals)
Range Filter Period: 25 bars (fast signals for 1-min)
Range Filter Multiplier: 2.2 (tighter bands for more signals)
Visual Controls
Toggle signal table on/off
Show/hide Fibonacci levels
Control EMA visibility
Adjust table text size
Partial Exits
1R: 50% (default)
2R: 30% (default)
3R: 20% (default)
Fully customizable percentages
Trailing Stops
ATR-Based (best for scalping)
Pivot-Based
EMA-Based
Breakeven trigger at 0.8R
🎯 Best Use Cases
Ideal For:
✅ 1-minute scalping on liquid instruments
✅ Day traders looking for quick 2-8 minute trades
✅ High-frequency trading with 8-15 signals per session
✅ Trending markets where Range Filter excels
✅ Crypto, Forex, Futures - works on all liquid assets
Trading Style:
Timeframe: 1-minute (can work on 3-5 min with adjusted settings)
Hold Time: 3-8 minutes average
Target: 1.2-3R per trade
Frequency: 8-15 signals per day
Win Rate: 45-55% (with proper risk management)
📋 How to Use
Step 1: Wait for Signal
Watch for green triangle (BUY) or red triangle (SELL)
Signal table appears at top center automatically
Step 2: Review Confluence
Check grade (prefer A+, A, B+ for best quality)
Review all reasons listed in table
Confirm score is above your threshold (55+ recommended)
Note the R:R ratio
Step 3: Enter Trade
Enter at current market price
Set stop loss at red dashed line
Set take profit at blue dashed line
Mark 1R level (orange line) for partial exit
Step 4: Manage Trade
Exit 50% at 1R (orange line)
Move to breakeven after 0.8R
Trail remaining position using your chosen method
Exit fully at TP or opposite signal
🎨 Chart Setup Recommendations
Optimal Display:
Timeframe: 1-minute
Chart Type: Candles or Heikin Ashi
Background: Dark theme for best color visibility
Volume: Enable volume bars below chart
Complementary Indicators (optional):
Order flow/Delta for institutional confirmation
Market profile for key levels
Economic calendar for news avoidance
⚠️ Important Notes
Risk Disclaimer:
Not financial advice - for educational purposes only
Always use proper risk management (0.5-1% per trade max)
Past performance doesn't guarantee future results
Test on demo account before live trading
Best Practices:
✅ Trade during high liquidity hours (9:30-11 AM, 2-4 PM EST)
✅ Avoid news events and market open/close (first/last 2 minutes)
✅ Use tight stops (0.8-1.0 ATR) for 1-minute scalping
✅ Take partial profits quickly (1R = 50% off)
✅ Respect max daily loss limits (3% recommended)
✅ Focus on A and B grade setups for consistency
What Makes This Different:
🎯 Complete system - not just signals, but full trade management
📊 Multi-confluence - 10+ factors analyzed per trade
🎨 Professional visualization - clean, focused chart design
⚡ Optimized for 1-min - settings specifically tuned for fast scalping
📋 Transparent reasoning - see exactly why each trade was taken
🏆 Grade system - instantly know trade quality
🔧 Technical Details
Pine Script Version: 5
Overlay: Yes (plots on price chart)
Max Lines: 500
Max Labels: 100
Non-repainting: All signals confirmed on bar close
Alerts: Compatible with TradingView alerts
📞 Support & Updates
This indicator is actively maintained and optimized for 1-minute scalping. Settings can be adjusted for different timeframes and trading styles, but default configuration is specifically tuned for high-frequency 1-minute scalping.
🚀 Get Started
Add ProScalper to your 1-minute chart
Adjust settings to your risk tolerance
Wait for signals (green/red triangles)
Follow the signal table guidance
Manage trades using provided levels
Track performance with stats table
Happy Scalping! 📊⚡💰
Automated Z-scoring - [JTCAPITAL]Automated Z-Scoring - is a modified way to use statistical normalization through Z-Scores for analyzing price deviations, volatility extremes, and mean reversion opportunities in financial markets.
The indicator works by calculating in the following steps:
Source Selection
The indicator begins by selecting a user-defined price source (default is the Close price). Traders can modify this to use any indicator that is deployed on the chart, for accurate and fast Z-scoring.
Mean Calculation
A Simple Moving Average (SMA) is calculated over the selected length period (default 3000). This represents the long-term equilibrium price level or the “statistical mean” of the dataset. It provides the baseline around which all price deviations are measured.
Standard Deviation Measurement
The script computes the Standard Deviation of the price series over the same period. This value quantifies how far current prices tend to stray from the mean — effectively measuring market volatility. The larger the standard deviation, the more volatile the market environment.
Z-Score Normalization
The Z-Score is calculated as:
(Current Price − Mean) ÷ Standard Deviation .
This normalization expresses how many standard deviations the current price is away from its long-term average. A Z-Score above 0 means the price is above average, while a negative score indicates it is below average.
Visual Representation
The Z-Score is plotted dynamically, with color-coding for clarity:
Bullish readings (Z > 0) are showing positive deviation from the mean.
Bearish readings (Z < 0) are showing negative deviation from the mean.
Make sure to select the correct source for what you exactly want to Z-score.
Buy and Sell Conditions:
While the indicator itself is designed as a statistical framework rather than a direct buy/sell signal generator, traders can derive actionable strategies from its behavior:
Trend Following: When the Z-Score crosses above zero after a prolonged negative period, it suggests a return to or above the mean — a possible bullish reversal or trend continuation signal.
Mean Reversion: When the Z-score is below for example -1.5 it indicates a good time for a DCA buying opportunity.
Trend Following: When the Z-Score crosses below zero after being positive, it may indicate a momentum slowdown or bearish shift.
Mean Reversion: When the Z-score is above for example 1.5 it indicates a good time for a DCA sell opportunity
Features and Parameters:
Length – Defines the period for both SMA and Standard Deviation. A longer length smooths the Z-Score and captures broader market context, while a shorter length increases responsiveness.
Source – Allows the user to choose which price data is analyzed (Close, Open, High, Low, etc.).
Fill Visualization – Highlights the magnitude of deviation between the Z-Score and the zero baseline, enhancing readability of volatility extremes.
Specifications:
Mean (Simple Moving Average)
The SMA calculates the average of the selected source over the defined length. It provides a central value to which the price tends to revert. In this indicator, the mean acts as the equilibrium point — the “zero” reference for all deviations.
Standard Deviation
Standard Deviation measures the dispersion of data points from their mean. In trading, it quantifies volatility. A high standard deviation indicates that prices are spread out (volatile), while a low value means they are clustered near the average (stable). The indicator uses this to scale deviations consistently across different market conditions.
Z-Score
The Z-Score converts raw price data into a standardized value measured in units of standard deviation.
A Z-Score of 0 = Price equals its mean.
A Z-Score of +1 = Price is one standard deviation above the mean.
A Z-Score of −1 = Price is one standard deviation below the mean.
This allows comparison of deviation magnitudes across instruments or timeframes, independent of price level.
Length Parameter
A long lookback period (e.g., 3000 bars) smooths temporary volatility and reveals long-term mean deviations — ideal for macro trend identification. Shorter lengths (e.g., 100–500) capture quicker oscillations and are useful for short-term mean reversion trades.
Statistical Interpretation
From a probabilistic perspective, if the distribution of prices is roughly normal:
About 68% of price observations lie within ±1 standard deviation (Z between −1 and +1).
About 95% lie within ±2 standard deviations.
Therefore, when the Z-Score moves beyond ±2, it statistically represents a rare event — often corresponding to price extremes or potential reversal zones.
Practical Benefit of Z-Scoring in Trading
Z-Scoring transforms raw price into a normalized volatility-adjusted metric. This allows traders to:
Compare instruments on a common statistical scale.
Identify mean-reversion setups more objectively.
Spot volatility expansions or contractions early.
Detect when price action significantly diverges from long-term equilibrium.
By automating this process, Automated Z-Scoring - provides traders with a powerful analytical lens to measure how “stretched” the market truly is — turning abstract statistics into a visually intuitive and actionable form.
Enjoy!
Pullback Levels from ATH# ATH Pullback Levels
**Assess correction depth with precision – 5%, 10%, 15%, 20% below All-Time High**
---
### Overview
This indicator draws **horizontal support lines** at **5%, 10%, 15%, and 20%** below the **All-Time High (ATH)** of any asset. Perfect for **swing traders**, **long-term investors**, and **bull market participants** who want to:
- Measure **pullback depth** in real-time
- Identify **potential support zones**
- Set **alerts** when price enters key retracement levels
---
### Features
| Feature | Description |
|--------|-------------|
| **Dynamic ATH Tracking** | Automatically updates with every new high |
| **4 Pullback Levels** | 5%, 10%, 15%, 20% below ATH |
| **Live Pullback % Label** | Shows current % drop from ATH (top-right) |
| **Customizable Lines** | Toggle visibility, change colors & styles |
| **Built-in Alerts** | Trigger on entry into each zone |
| **No Errors** | Works on 50k+ bar charts (BTC, SPX, etc.) |
| **Time-Based Lines** | Uses `xloc.bar_time` – no 500-bar future limit |
---
### How to Use
1. Apply to any chart (stocks, crypto, forex, indices)
2. Watch the **info box** for current pullback %
3. Use lines as **potential buy zones** during corrections
4. Set **alerts** to be notified when price enters a level
> Example: If ATH = $100 →
> - 5% = $95
> - 10% = $90
> - 15% = $85
> - 20% = $80
---
### Inputs
- **Show 5% / 10% / 15% / 20% Level** → Toggle on/off
- **Line Colors** → Fully customizable
- **Line Style** → Solid, Dashed, or Dotted
---
### Alerts
Create alerts directly from the indicator:
- `"Entered 5% Pullback"`
- `"Entered 10% Pullback"`
- etc.
---
### Best For
- Bull market corrections
- Long-term position sizing
- Risk management in uptrends
- Swing entries on dips
---
### Notes
- Works on **all timeframes**
- **Log scale compatible** (lines adjust correctly)
- No repainting – ATH only updates on confirmed highs
---
**Built with Pine Script v6 – Clean, fast, reliable.**
*Happy trading!*
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.
ATR Money Line Bands V2The "ATR Money Line Bands V2" is a clever TradingView overlay designed for trend identification with volatility-aware bands, evolving from basic ATR envelopes.
Reasoning Behind Construction: The core idea is to blend a smoothed trend line with dynamic volatility bands for reliable signals in varying markets. The "Money Line" uses linear regression (ta.linreg) on closes over a length (default 16) instead of a moving average, as it fits data via least-squares for a cleaner, forward-projected trend without lag artifacts. ATR (default 12-period) powers the bands because it measures true range volatility better than std dev in gappy assets like crypto/stocks—bands offset from the Money Line by ATR * multiplier (default 1.5). A dynamic multiplier (boosts by ~33% on spikes > prior ATR * 1.3) prevents tight bands from false breakouts during surges. Trend detection checks slope against an ATR-scaled tolerance (default 0.15) to ignore noise, labeling bull/bear/neutral—avoiding whipsaws in flats.
Properties: It's an overlay with a colored Money Line (green bull, red bear, yellow neutral) and invisible bands (toggle to show gray lines) filled semi-transparently matching trend for visual pop. Dynamic adaptation makes bands widen/contract intelligently. An info table (positionable, e.g., top_right) displays real-time values: Money Line, bands, ATR, trend—great for quick scans. Limits history (2000 bars) and labels (500) for efficiency.
Tips for Usage: Apply to any timeframe/asset; defaults suit medium-term (e.g., daily stocks). Watch color flips: green for longs (enter on pullbacks to lower band), red for shorts (vice versa), yellow to sit out. Use bands as S/R—breakouts signal momentum, squeezes impending vol. Tweak length for sensitivity (shorter for intraday), multiplier for width (higher for trends), tolerance for fewer neutrals. Pair with volume/RSI for confirmation; backtest to optimize. In choppy markets, disable dynamic mult to avoid over-expansion. Overall, it's adaptive and visual—helps trend-follow without overcomplicating.
Thematic Portfolio: Quantum Computing & Core TechThis indicator tracks the aggregated performance of a curated thematic portfolio representing the Quantum Computing & Core Technology sector.
It combines leading equities and ETFs with predefined weights to reflect a diversified exposure across quantum hardware, AI infrastructure, and semiconductor backbones.
Composition:
Stocks: Rigetti (RGTI), IonQ (IONQ), D-Wave (QBTS), Palantir (PLTR), Intel (INTC), Arqit (ARQQ)
ETFs: BUG, QTUM, SOXX, IHAK
Methodology:
Each component’s normalized performance is weighted according to its strategic importance within the theme (R&D intensity, infrastructure leverage, and hardware dependence). The indicator dynamically aggregates the weighted series to visualize the cumulative return of the quantum computing ecosystem versus traditional benchmarks.
Intended use:
Compare thematic returns vs. S&P 500 or NASDAQ
Identify macro inflection points in the quantum tech narrative
Backtest thematic exposure strategies or structure twin-win / delta-one certificates
Note: This script is for analytical and educational purposes only and does not constitute financial advice.
VolumeAnlaysis### Volume Analysis (VA) Indicator
**Overview**
The Volume Analysis (VA) indicator is a dynamic overlay tool designed for traders seeking to identify high-volume breakouts, retests, and multi-timeframe volume-driven price cycles. By combining volume spikes with price action and support/resistance boxes, it highlights potential trend continuations, reversals, and cycle shifts. Ideal for intraday and swing trading on stocks, forex, or crypto, it uses a Fibonacci-inspired 1.618 multiplier to detect significant volume surges, then maps them to visual boxes and key levels for actionable insights.
This indicator draws from volume profile concepts but focuses on **breakout confirmation** and **cycle momentum**, helping you spot when "smart money" volume aligns with price extremes. It's particularly useful in volatile markets where volume precedes price moves.
**How It Works**
1. **Volume Break Detection**:
- Identifies a "Volume Break" when the current bar's volume exceeds 1.618x the highest volume from the prior 5 bars. This signals unusual activity, often preceding breakouts.
- A "Volume Retest" triggers exactly 3 bars after a break if volume has been falling steadily over those 3 bars—indicating a pullback for re-accumulation/distribution.
2. **Visual Annotations**:
- **Labels**: Green/red/yellow labels mark Volume Breaks and Retests, positioned above/below the bar based on candle direction for clarity.
- **Demand/Supply Boxes**:
- Blue semi-transparent boxes form around Retest bars, extending rightward to act as dynamic support/resistance.
- Green (bullish) or red (bearish) boxes draw from Volume Breaks, based on the original candle's open/close, highlighting potential zones for continuation.
- Limited to 5 boxes max to avoid chart clutter; older boxes fade as new ones form.
3. **Box Interaction Signals**:
- When price enters a box:
- **Reversal Hints**: Maroon (bearish rejection) or lime (bullish rejection) labels on closes against the trend with opening price momentum.
- **Breakout Arrows**: Up/down arrows on crossovers/crossunders of box tops/bottoms from Retest boxes.
- Scans all active boxes for interactions, prioritizing recent volume events.
4. **Multi-Timeframe Volume Cycles**:
- Aggregates the "Volume Break Max" level (a proxy for key price extremes tied to volume spikes) across timeframes: 1min, 5min, 10min, 30min, and 65min (using `request.security`).
- Computes **MaxVolBreak** (highest extreme) and **MinVolBreak** (lowest extreme) for trend-following levels.
- Tracks **Percent Volume Greater/Less Than Close**: Sums volumes from TFs where price is below/above these levels, creating a momentum ratio.
- **CrossClose**: Plots the prior close where this ratio crosses (gray line), signaling cycle shifts—bullish below MinVolBreak, bearish above MaxVolBreak.
- **Fills**: Red fill above CrossClose/MaxVolBreak (bearish cycle); green below CrossClose/MinVolBreak (bullish cycle).
5. **Plots**:
- Black lines for MaxVolBreak (⏫) and MinVolBreak (⏬).
- Gray 🔄 for CrossClose.
- Colors dynamically adjust (green/red) based on close relative to levels.
**Key Features**
- **Trend vs. Reversal Modes**: Toggle alerts for trend-following breaks (crosses of Max/MinVolBreak) or reversal signals (crosses of CrossClose).
- **Multi-TF Fusion**: Optionally include the chart's native timeframe in Max/Min calculations for finer tuning.
- **Box Management**: Auto-prunes to 5 boxes; focuses on retest/break alignments for "inside bar" logic.
- **Momentum Filters**: Uses rising/falling opens and crossovers for label precision, reducing noise.
- **Customizable**: Simple inputs for alert visibility and timeframe inclusion.
**Settings**
| Input | Default | Description |
|-------|---------|-------------|
| Show Volume Reversal Breaks | False | Enables alerts/labels for CrossClose crosses (cycle reversals). |
| Show Trend Following Breaks | True | Enables alerts for Max/MinVolBreak crosses (trend signals). |
| Use Current Time | False | Includes chart's native TF in multi-TF Max/Min calculations. |
**Alerts**
- **Reversal Alerts** (if enabled): "Volume Reverse Bullish/Bearish Break of " on close crosses of CrossClose.
- **Trend Alerts** (if enabled): "Trend Volume Bullish/Bearish Signal" on close crosses of Max/MinVolBreak; plus notes if prior low/high aligns with levels.
- All alerts include ticker and level value for easy scanning. Use `alert.freq_once_per_bar` to avoid spam.
**Trading Ideas**
- **Bullish Entry**: Green box formation + price holding MinVolBreak + upward arrow on retest box. Target next resistance.
- **Bearish Entry**: Red box + close above MaxVolBreak + red fill activation. Stop below recent low.
- **Cycle Trading**: Watch CrossClose crosses for regime shifts—fade extremes in overextended cycles.
- **Best Timeframes**: 5-30min for intraday; combine with daily for swings. Works best on liquid assets with reliable volume data.
**Limitations & Notes**
- Relies on accurate volume data (e.g., stocks/forex); less effective on low-volume or synthetic instruments.
- Boxes extend rightward but don't auto-delete—monitor for clutter on long histories (max_bars_back=500).
- Some logic (e.g., exact 3-bar retest) is rigid; backtest for your market.
- Open-source under MPL 2.0—fork and tweak as needed!
For questions or enhancements, drop a comment below. Happy trading! 🚀
BB LONG 2BX & FVB StrategyThis Strategy is optimized for the 2h timeframe. Happy Charting and you're welcome!
**BB LONG 2BX & FVB Strategy – Simple Text Guide**
---
### **What It Does**
A **long-only trading strategy** that:
- Enters on **strong upward momentum**
- Adds a second position when the trend gets stronger
- Takes profits in parts at **smart price levels**
- Exits fully if the trend weakens or reverses
---
### **Main Tools Used**
| Tool | Simple Meaning |
|------|----------------|
| **B-Xtrender (Oscillator)** | Measures speed of price move. Above 0 = bullish, below 0 = bearish |
| **Weekly & Monthly Timeframes** | Checks if higher timeframes agree with the trade |
| **Red ATR Line** | A moving stop-loss that follows price up |
| **Fair Value Bands (1x, 2x, 3x)** | Profit targets that adjust to market volatility |
---
### **When It Enters a Trade (Long)**
**First Entry:**
- Weekly momentum is **rising**
- Monthly momentum is **positive or increasing**
- No current position
**Second Entry (Pyramiding):**
- Already in trade
- Price breaks **above the Red ATR line** → add same size again
(Max 2 total entries)
---
### **When It Takes Profit (Scaling Out)**
| Level | Action |
|-------|--------|
| **1x Band** | Sell **50%** when price pulls back from this level |
| **2x Band** | Sell **50%** when price pulls back from this level |
| **3x Band** | **Exit everything** when price pulls back from this level |
> You can hit 1x and 2x **multiple times** – it will keep taking 50% each time
---
### **When It Exits Fully (Closes Everything)**
1. Price **closes below Red ATR line**
2. Weekly momentum shows **2 red bars in a row, both falling**
3. Weekly momentum **crosses below zero** AND price is below Red ATR
4. Weekly momentum **drops sharply** (more than 25 points in one bar)
> After full exit, it **won’t re-enter** unless price comes back below 2x band
---
### **Alerts You Get**
Every time price **touches** a profit band, you get an alert:
- “Price touched 1x band from below”
- “Price touched 1x band from above”
- Same for **2x** and **3x**
> One alert per touch, per bar
---
### **On the Chart – What You See**
- **Histogram bars (weekly momentum)**
Lime = up, Red = down
**Yellow highlight** = warning (exit soon)
- **Red broken line** = stop-loss level
- **Blue line** = fair middle price
- **Orange, Purple, Pink lines** = 1x, 2x, 3x profit targets
---
### **Best Used On**
- Daily or 4-hour charts
- Strong trending assets (like Bitcoin, Tesla, S&P 500)
---
### **Quick Rules Summary**
| Do This | When |
|--------|------|
| **Enter** | Weekly up + monthly support |
| **Add more** | Price breaks above Red line |
| **Take 50% profit** | Price pulls back from 1x or 2x |
| **Exit all** | Red line break, weak momentum, or 3x hit |
---
**Simple Idea:**
**Ride strong trends, add when confirmed, take profits in chunks, cut losses fast.**
