Topological Market Stress (TMS) - Quantum FabricTopological Market Stress (TMS) - Quantum Fabric
What Stresses The Market?
Topological Market Stress (TMS) represents a revolutionary fusion of algebraic topology and quantum field theory applied to financial markets. Unlike traditional indicators that analyze price movements linearly, TMS examines the underlying topological structure of market data—detecting when the very fabric of market relationships begins to tear, warp, or collapse.
Drawing inspiration from the ethereal beauty of quantum field visualizations and the mathematical elegance of topological spaces, this indicator transforms complex mathematical concepts into an intuitive, visually stunning interface that reveals hidden market dynamics invisible to conventional analysis.
Theoretical Foundation: Topology Meets Markets
Topological Holes in Market Structure
In algebraic topology, a "hole" represents a fundamental structural break—a place where the normal connectivity of space fails. In markets, these topological holes manifest as:
Correlation Breakdown: When traditional price-volume relationships collapse
Volatility Clustering Failure: When volatility patterns lose their predictive power
Microstructure Stress: When market efficiency mechanisms begin to fail
The Mathematics of Market Topology
TMS constructs a topological space from market data using three key components:
1. Correlation Topology
ρ(P,V) = correlation(price, volume, period)
Hole Formation = 1 - |ρ(P,V)|
When price and volume decorrelate, topological holes begin forming.
2. Volatility Clustering Topology
σ(t) = volatility at time t
Clustering = correlation(σ(t), σ(t-1), period)
Breakdown = 1 - |Clustering|
Volatility clustering breakdown indicates structural instability.
3. Market Efficiency Topology
Efficiency = |price - EMA(price)| / ATR
Measures how far price deviates from its efficient trajectory.
Multi-Scale Topological Analysis
Markets exist across multiple temporal scales simultaneously. TMS analyzes topology at three distinct scales:
Micro Scale (3-15 periods): Immediate structural changes, market microstructure stress
Meso Scale (10-50 periods): Trend-level topology, medium-term structural shifts
Macro Scale (50-200 periods): Long-term structural topology, regime-level changes
The final stress metric combines all scales:
Combined Stress = 0.3×Micro + 0.4×Meso + 0.3×Macro
How TMS Works
1. Topological Space Construction
Each market moment is embedded in a multi-dimensional topological space where:
- Price efficiency forms one dimension
- Correlation breakdown forms another
- Volatility clustering breakdown forms the third
2. Hole Detection Algorithm
The indicator continuously scans this topological space for:
Hole Formation: When stress exceeds the formation threshold
Hole Persistence: How long structural breaks maintain
Hole Collapse: Sudden topology restoration (regime shifts)
3. Quantum Visualization Engine
The visualization system translates topological mathematics into intuitive quantum field representations:
Stress Waves: Main line showing topological stress intensity
Quantum Glow: Surrounding field indicating stress energy
Fabric Integrity: Background showing structural health
Multi-Scale Rings: Orbital representations of different timeframes
4. Signal Generation
Stable Topology (✨): Normal market structure, standard trading conditions
Stressed Topology (⚡): Increased structural tension, heightened volatility expected
Topological Collapse (🕳️): Major structural break, regime shift in progress
Critical Stress (🌋): Extreme conditions, maximum caution required
Inputs & Parameters
🕳️ Topological Parameters
Analysis Window (20-200, default: 50)
Primary period for topological analysis
20-30: High-frequency scalping, rapid structure detection
50: Balanced approach, recommended for most markets
100-200: Long-term position trading, major structural shifts only
Hole Formation Threshold (0.1-0.9, default: 0.3)
Sensitivity for detecting topological holes
0.1-0.2: Very sensitive, detects minor structural stress
0.3: Balanced, optimal for most market conditions
0.5-0.9: Conservative, only major structural breaks
Density Calculation Radius (0.1-2.0, default: 0.5)
Radius for local density estimation in topological space
0.1-0.3: Fine-grained analysis, sensitive to local changes
0.5: Standard approach, balanced sensitivity
1.0-2.0: Broad analysis, focuses on major structural features
Collapse Detection (0.5-0.95, default: 0.7)
Threshold for detecting sudden topology restoration
0.5-0.6: Very sensitive to regime changes
0.7: Balanced, reliable collapse detection
0.8-0.95: Conservative, only major regime shifts
📊 Multi-Scale Analysis
Enable Multi-Scale (default: true)
- Analyzes topology across multiple timeframes simultaneously
- Provides deeper insight into market structure at different scales
- Essential for understanding cross-timeframe topology interactions
Micro Scale Period (3-15, default: 5)
Fast scale for immediate topology changes
3-5: Ultra-fast, tick/minute data analysis
5-8: Fast, 5m-15m chart optimization
10-15: Medium-fast, 30m-1H chart focus
Meso Scale Period (10-50, default: 20)
Medium scale for trend topology analysis
10-15: Short trend structures
20-25: Medium trend structures (recommended)
30-50: Long trend structures
Macro Scale Period (50-200, default: 100)
Slow scale for structural topology
50-75: Medium-term structural analysis
100: Long-term structure (recommended)
150-200: Very long-term structural patterns
⚙️ Signal Processing
Smoothing Method (SMA/EMA/RMA/WMA, default: EMA) Method for smoothing stress signals
SMA: Simple average, stable but slower
EMA: Exponential, responsive and recommended
RMA: Running average, very smooth
WMA: Weighted average, balanced approach
Smoothing Period (1-10, default: 3)
Period for signal smoothing
1-2: Minimal smoothing, noisy but fast
3-5: Balanced, recommended for most applications
6-10: Heavy smoothing, slow but very stable
Normalization (Fixed/Adaptive/Rolling, default: Adaptive)
Method for normalizing stress values
Fixed: Static 0-1 range normalization
Adaptive: Dynamic range adjustment (recommended)
Rolling: Rolling window normalization
🎨 Quantum Visualization
Fabric Style Options:
Quantum Field: Flowing energy visualization with smooth gradients
Topological Mesh: Mathematical topology with stepped lines
Phase Space: Dynamical systems view with circular markers
Minimal: Clean, simple display with reduced visual elements
Color Scheme Options:
Quantum Gradient: Deep space blue → Quantum red progression
Thermal: Black → Hot orange thermal imaging style
Spectral: Purple → Gold full spectrum colors
Monochrome: Dark gray → Light gray elegant simplicity
Multi-Scale Rings (default: true)
- Display orbital rings for different time scales
- Visualizes how topology changes across timeframes
- Provides immediate visual feedback on cross-scale dynamics
Glow Intensity (0.0-1.0, default: 0.6)
Controls the quantum glow effect intensity
0.0: No glow, pure line display
0.6: Balanced, recommended setting
1.0: Maximum glow, full quantum field effect
📋 Dashboard & Alerts
Show Dashboard (default: true)
Real-time topology status display
Current market state and trading recommendations
Stress level visualization and fabric integrity status
Show Theory Guide (default: true)
Educational panel explaining topological concepts
Dashboard interpretation guide
Trading strategy recommendations
Enable Alerts (default: true)
Extreme stress detection alerts
Topological collapse notifications
Hole formation and recovery signals
Visual Logic & Interpretation
Main Visualization Elements
Quantum Stress Line
Primary indicator showing topological stress intensity
Color intensity reflects current market state
Line style varies based on selected fabric style
Glow effect indicates stress energy field
Equilibrium Line
Silver line showing average stress level
Reference point for normal market conditions
Helps identify when stress is elevated or suppressed
Upper/Lower Bounds
Red upper bound: High stress threshold
Green lower bound: Low stress threshold
Quantum fabric fill between bounds shows stress field
Multi-Scale Rings
Aqua circles : Micro-scale topology (immediate changes)
Orange circles: Meso-scale topology (trend-level changes)
Provides cross-timeframe topology visualization
Dashboard Information
Topology State Icons:
✨ STABLE: Normal market structure, standard trading conditions
⚡ STRESSED: Increased structural tension, monitor closely
🕳️ COLLAPSE: Major structural break, regime shift occurring
🌋 CRITICAL: Extreme conditions, reduce risk exposure
Stress Bar Visualization:
Visual representation of current stress level (0-100%)
Color-coded based on current topology state
Real-time percentage display
Fabric Integrity Dots:
●●●●● Intact: Strong market structure (0-30% stress)
●●●○○ Stressed: Weakening structure (30-70% stress)
●○○○○ Fractured: Breaking down structure (70-100% stress)
Action Recommendations:
✅ TRADE: Normal conditions, standard strategies apply
⚠️ WATCH: Monitor closely, increased vigilance required
🔄 ADAPT: Change strategy, regime shift in progress
🛑 REDUCE: Lower risk exposure, extreme conditions
Trading Strategies
In Stable Topology (✨ STABLE)
- Normal trading conditions apply
- Use standard technical analysis
- Regular position sizing appropriate
- Both trend-following and mean-reversion strategies viable
In Stressed Topology (⚡ STRESSED)
- Increased volatility expected
- Widen stop losses to account for higher volatility
- Reduce position sizes slightly
- Focus on high-probability setups
- Monitor for potential regime change
During Topological Collapse (🕳️ COLLAPSE)
- Major regime shift in progress
- Adapt strategy immediately to new market character
- Consider closing positions that rely on previous regime
- Wait for new topology to stabilize before major trades
- Opportunity for contrarian plays if collapse is extreme
In Critical Stress (🌋 CRITICAL)
- Extreme market conditions
- Significantly reduce risk exposure
- Avoid new positions until stress subsides
- Focus on capital preservation
- Consider hedging existing positions
Advanced Techniques
Multi-Timeframe Topology Analysis
- Use higher timeframe TMS for regime context
- Use lower timeframe TMS for precise entry timing
- Alignment across timeframes = highest probability trades
Topology Divergence Trading
- Most powerful at regime boundaries
- Price makes new high/low but topology stress decreases
- Early warning of potential reversals
- Combine with key support/resistance levels
Stress Persistence Analysis
- Long periods of stable topology often precede major moves
- Extended stress periods often resolve in regime changes
- Use persistence tracking for position sizing decisions
Originality & Innovation
TMS represents a genuine breakthrough in applying advanced mathematics to market analysis:
True Topological Analysis: Not a simplified proxy but actual topological space construction and hole detection using correlation breakdown, volatility clustering analysis, and market efficiency measurement.
Quantum Aesthetic: Transforms complex topology mathematics into an intuitive, visually stunning interface inspired by quantum field theory visualizations.
Multi-Scale Architecture: Simultaneous analysis across micro, meso, and macro timeframes provides unprecedented insight into market structure dynamics.
Regime Detection: Identifies fundamental market character changes before they become obvious in price action, providing early warning of structural shifts.
Practical Application: Clear, actionable signals derived from advanced mathematical concepts, making theoretical topology accessible to practical traders.
This is not a combination of existing indicators or a cosmetic enhancement of standard tools. It represents a fundamental reimagining of how we measure, visualize, and interpret market dynamics through the lens of algebraic topology and quantum field theory.
Best Practices
Start with defaults: Parameters are optimized for broad market applicability
Match timeframe: Adjust scales based on your trading timeframe
Confirm with price action: TMS shows market character, not direction
Respect topology changes: Reduce risk during regime transitions
Use appropriate strategies: Adapt approach based on current topology state
Monitor persistence: Track how long topology states maintain
Cross-timeframe analysis: Align multiple timeframes for highest probability trades
Alerts Available
Extreme Topological Stress: Market fabric under severe deformation
Topological Collapse Detected: Regime shift in progress
Topological Hole Forming: Market structure breakdown detected
Topology Stabilizing: Market structure recovering to normal
Chart Requirements
Recommended Markets: All liquid markets (forex, stocks, crypto, futures)
Optimal Timeframes: 5m to Daily (adaptable to any timeframe)
Minimum History: 200 bars for proper topology construction
Best Performance: Markets with clear regime characteristics
Academic Foundation
This indicator draws from cutting-edge research in:
- Algebraic topology and persistent homology
- Quantum field theory visualization techniques
- Market microstructure analysis
- Multi-scale dynamical systems theory
- Correlation topology and network analysis
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or provide direct buy/sell signals. Topological analysis reveals market structure characteristics, not future price direction. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of topology. Trade the structure, not the noise.
Bringing advanced mathematics to practical trading through quantum-inspired visualization.
Trade with insight. Trade with structure.
— Dskyz , for DAFE Trading Systems
스크립트에서 "Volatility"에 대해 찾기
[Volatility] [Gain & Loss] - OverviewFX:EURUSD
Indicator Overview: Volatility & Gain/Loss - Forex Pair Analysis
This indicator, " —Overview" , is designed for users interested in analyzing the volatility and gain/loss metrics of multiple forex pairs. The tool is especially useful for traders aiming to assess currency pair volatility alongside gain and loss percentages over selected periods. It enables a clearer understanding of pair behavior and aids in decision-making.
Key Features
Customizable Volatility and Gain/Loss Periods : Define your preferred calculation periods and timeframes for both volatility and gain/loss to tailor the indicator to specific trading strategies. Multi-Pair Analysis : This indicator supports up to six forex pairs (default pairs include EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, and USDCAD) and allows you to adjust these pairs as needed. Visual Ranking : Forex pairs are sorted by volatility, displaying the highest pairs at the top for quick reference. Top Gain/Loss Highlighting : The pair with the maximum gain and the pair with the maximum loss are highlighted in the table, making it easy to identify the best and worst performers at a glance.
Indicator Settings
Volatility Settings : Period : Adjust the number of periods used in the ATR (Average True Range) calculation. A default period of 14 is set. Timeframe : Select a timeframe (e.g., Daily, Weekly) for volatility calculation to match your analysis preference.
Gain/Loss Settings : Period : Choose the number of periods for gain/loss calculation. The default is set to 1. Timeframe : Select the timeframe for gain/loss calculation, independent of the volatility timeframe.
Symbol Selection : Configure up to six forex pairs. By default, popular forex pairs are pre-loaded but can be customized to include other currency pairs.
Output and Visualization
Table Display : This indicator displays data in a neatly structured table positioned in the top-right corner of your chart. Columns : Includes columns for the Forex Pair, Volatility Percentage, Gain Percentage, and Loss Percentage. Color Coding : Volatility is displayed in a standard color for clear readability. Gain values are highlighted in green, and Loss values are highlighted in red, allowing for quick visual differentiation. Highlighting : Rows representing the pair with the highest gain and the pair with the most significant loss are especially highlighted for emphasis.
How to Use
Volatility Analysis : This metric gives insight into the average price range movements for each pair over the specified period and timeframe, helping you evaluate the potential for rapid price changes. Gain/Loss Tracking : Gain or loss percentages show the pair's recent performance, allowing you to observe whether a currency pair is trending positively or negatively over the chosen period. Comparative Pair Ranking : Use the table to identify pairs with the highest volatility and extremes in gain or loss to guide trading decisions based on market conditions.
Ideal For
Swing Traders and Day Traders looking to understand short-term market fluctuations in currency pairs. Risk Management : Helps traders gauge pairs with higher risk (volatility) and recent performance (gain/loss) for informed position sizing and risk control.
This indicator is a comprehensive tool for visualizing and analyzing key forex pairs, making it an essential addition for traders looking to stay updated on volatility trends and recent price changes.
Standard Deviation OscillatorStandard Deviation Oscillator (STDEV OSC) v1.1
Description
The Standard Deviation Oscillator transforms traditional volatility measurements into a dynamic oscillator that fluctuates between 0 and 100. This advanced technical analysis tool helps traders identify periods of extreme volatility and potential market turning points.
Features
Normalized volatility readings (0-100 scale)
Dynamic color changes based on volatility levels
Customizable overbought/oversold thresholds
Built-in alert conditions
Adaptive calculation using rolling windows
Clean, professional visualization
Indicator Parameters
Length: 20; Calculation period for standard deviation
Source: close; Price source for calculations
Overbought Level: 70; Upper threshold for high volatility
Oversold Level: 30; Lower threshold for low volatility
Visual Components
- Main Oscillator Line: Changes color based on current level
- Red: Above overbought level
- Green: Below oversold level
- Blue: Normal range
- Reference Lines:
- Overbought level (default: 70)
- Oversold level (default: 30)
- Middle line (50)
Alert Conditions
1. Volatility High Alert
- Triggers when oscillator crosses above the overbought level
- Useful for identifying potential market tops or breakout scenarios
2. Volatility Low Alert
- Triggers when oscillator crosses below the oversold level
- Helps identify potential market bottoms or consolidation periods
Risk Adjustment Tool
- Scale position sizes inversely to oscillator readings
- Reduce exposure during extremely high volatility periods
- Increase position sizes during normal volatility conditions
Best Practices
1. Timeframe Selection
- Best suited for 1H, 4H, and Daily charts
- Adjust length parameter based on timeframe
2. Confirmation
- Use in conjunction with trend indicators
- Confirm signals with price action patterns
- Consider overall market context
3. Parameter Optimization
- Backtest different length settings
- Adjust overbought/oversold levels based on asset
- Consider market conditions when setting alerts
Technical Notes
- Built in PineScript v5
- Optimized for TradingView platform
- Uses rolling window calculations for better adaptability
- Compatible with all trading instruments
- Minimal performance impact on charts
Version History
- v1.1: Added dynamic coloring, customizable levels, and alert conditions
- v1.0: Initial release with basic oscillator functionality
Disclaimer
This technical indicator is provided for educational and informational purposes only. Past performance is not indicative of future results. Always conduct thorough testing and use proper risk management techniques.
---
Tags: #TechnicalAnalysis #Volatility #Trading #Oscillator #TradingView #PineScript
Volatility System by W. WilderVolatility System (Volatility Stops) Similarity
Most traders adjust their stops over time in the direction of the trend in order to lock in profits. Apart from moving averages, one of the most popular techniques is trailing stops using a multiple of Average True Range. There are several variations:
The original Volatility System(Volatility Stops), introduced by Welles Wilder in his 1978 book: New Concepts in Technical Trading Systems
Chandelier exits introduced by Alexander Elder in Come Into My Trading Room (2002) trail the stops from Highs or Lows rather than Closing Price
Average True Range Trailing Stops are similar to the above, but include a ratchet mechanism to prevent stops moving down during an up-trend or rising during a down-trend, as ATR increases
WillTrend intoduced by Larry Williams in 1988
Comparison of systems
All the systems under consideration have one common ingredient - ATR. ATR was developed by Welles Wilder and described in his book in 1978, also in this book the Volatility System was described, which in the future became known as Volatility Stops.
In fact, Wilder is the father of such systems due to the presence of ATR in the calculation of this type of indicator.
The main difference of Volatility System
Followers such as Larry Williams and Alexander Elder made minor changes to the value based on the ATR, mainly focusing on changing the base to which this value is added or subtracted.
Larry Williams uses the square root of 5 as a multiplier and calculates the ATR with a period of 66, and Alexander Elder uses a multiplier of 2.5-3.5 applying it to the ATR with a period of 22. Both authors changed the original value for ATR and multiplier calculations. Alexander Elder is closest to the original Welles Wilder calculation, which used a multiplier of 2.8.-3.1 applying it to an ATR with a period of 7.
As a reference, Elder took the Highest High(22) from which he subtracts ATR*Multiplier in an uptrend or the Lowest Low(22) to which he adds ATR*Multiplier to obtain the turning point (SAR).
Larry Williams uses the average price of extremes (Highest High(10) + Lowest Low(10)) / 2 as a reference base to which he adds or subtracts the ATR*Multilpyer values.
Both systems differ from the original, because Wilder used Significan Close(SIC) in his calculations. SIC is the maximum closing price during an uptrend and the minimum closing price during a downtrend, which
does not go beyond the current trade, as in other systems. To calculate the base when a trend changes, bars that are outside the current trend will be used when calculating WillTrend and Chandelier Exit, in contrast to the Volatility System, which takes SIC values only within the current trade. This is the main difference from subsequent developments of similar systems.
Improvements made
The original Volatility System is present as an indicator on TradingView, but it is an improved version with the addition of a ratchet and works differently from the original Weilder system.
List of improvements:
Added the ability to remove the ratchet. You need to turn off the "Trail one way" checkbox in the setting menu. When this function is turned off, the system will operate in the author-inventor mode. On some instruments, the original system works much better than the improved ratchet system, which cannot be turned off.
Added the ability to use Highest High and Lowest Low as a base instead of the closing price.
Volatility Stops Formula Description
Welles Wilder's system uses Closing Price and incorporates a stop-and-reverse feature (as with his Parabolic SAR).
Determine the initial trend direction
Calculate the Significant Close ("SIC"): the highest close reached in an up-trend or the lowest close in a down-trend
Calculate Average True Range ("ATR") for the selected period (7 days in this example)
Multiply ATR by the Multiple (3.0 in this example, best values author describes as 2.8-3.1)
The first stop is calculated in day 7 and plotted for day 8
If an up-trend, the first stop is SIC - 3 * ATR, otherwise SIC + 3 * ATR for a down-trend
Repeat each day until price closes below the stop (or above in a down-trend)
Set SIC equal to the latest Close, reverse the trend and continue.
Chandelier Exit Description
Chandelier Exits subtract a multiple of Average True Range ("ATR") from the highest high for the selected period. Using the default settings as an example:
Highest High in last 22 days - 3 * ATR for 22 days
In a down-trend the formula is reversed:
Lowest Low in last 22 days + 3 * ATR for 22 days
The time period must be long enough to capture the highest point of the recent up-trend: too short and the stops move downward; too long and the high may be taken from a previous down-trend.
It is not essential to use the same period for up and down trends; down-trends are notoriously faster than up-trends and may benefit from a shorter time period.
The multiple of 3 may be varied, but most traders settle between 2.5 and 3.5.
WillTrend Description
Larry Williams is prefer to used the Square Root from 5 as a multiplayer for ATR. SQRT(5) = 2.236
WillTrend subtract a multiple of Average True Range ("ATR") from the Middle Price (Highest High for the selected period + Lowest Low for the selected period / 2).
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 - 2.236 * ATR for 66 days
In a down-trend the formula is reversed:
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 + 2.236 * ATR for 66 days
VIX HeatmapVIX HeatMap
Instructions:
- To be used with the S&P500 index (ES, SPX, SPY, any S&P ETF) as that's the input from where the CBOE calculates and measures the VIX. Can also be used with the Dow Jones, Nasdaq, & Nasdaq100.
Description:
- Expected Implied Volatility regime simplified & visualized. Know if we are in a high, medium, or low volatility regime, instantly.
- Ranges from Hot to Cold: The hotter the heat-map, the higher the implied volatility and fear & vice versa.
- The VIX HeatMap, color-maps important VIX levels (7 in this case) in measuring volatility for day trading & swing trading.
Using the VIX HeatMap:
- A LOW level volatility environment: Represented by "cooler" colors (Blue & White) depicts that the level of volatility and fear is low. Percentage moves on the index level are going to be tame and less volatile more often than not. Low fear = low perceived risk.
- A MEDIUM level volatility environment: Represented by "warmer" colors (Green & Yellow) depicts that the markets are transitioning from a calmer period or from a more fearful period. Market volatility here will be higher and provide more volatile swings in price.
- A HIGH level volatility environment: Represented by "hotter" colors (Orange, Red, & Purple) depicts that the markets are very fearful at the moment and will have big swings in both directions. Historically, extreme VIX levels tend to coincide with bottoms but are in no way predictive of the exact timing as the volatile moves can continue for an extended period of time.
- Transitioning between the 7 VIX Zones: Each and every one of these specific VIX zone levels is important.
1. Extreme low: <16
2. Low: 16 to 20
3. Normal: 20 to 24
4. Medium: 24 to 28
5. Med-High: 28 to 32
6. High: 32 to 36
7. Extreme high: >36
- These VIX levels in particular measure volatility changes that have a major impact on switching between smaller time frames and measuring depths of a sell move and vice versa. Each level also behaves as its own support & resistance level in terms of taking a bit of effort to switch regimes, and aids in identifying and measuring the potential depth of pullbacks in bull markets and bounces in bear markets to reveal reversal points.
- Examples of VIX level supports depicted on the chart marked with arrows. From left to right:
1. March 10th: Markets jumped 2 volatility levels in 2 days. The fluctuations from blue to yellow to green where a sign that price action would reverse from the selloff.
2. March 28th: As soon as we move from green to the blue VIX level (<20), markets began to rally and only ended when the volatility level moved sub VIX 16 (white).
3. May 4th & 24th: Next we see the 2 dips where volatility levels went from blue to green (VIX > 20), marked bottoms and reversed higher.
4. June 1st: We see a change in VIX regime yet again into lower VIX level and markets rocket higher.
Knowing the current VIX regime is a very important tool and aid in trading, now easily visualized.
Bar metrics / quantifytools— Overview
Rather than eyeball evaluating bullishness/bearishness in any given bar, bar metrics allow a quantified approach using three basic fundamental data points: relative close, relative volatility and relative volume. These data points are visualized in a discreet data dashboard form, next to all real-time bars. Each value also has a dot in front, representing color coded extremes in the values.
Relative close represents position of bar's close relative to high and low, high of bar being 100% and low of bar being 0%. Relative close indicates strength of bulls/bears in a given bar, the higher the better for bulls, the lower the better for bears. Relative volatility (bar range, high - low) and relative volume are presented in a form of a multiplier, relative to their respective moving averages (SMA 20). A value of 1x indicates volume/volatility being on par with moving average, 2x indicates volume/volatility being twice as much as moving average and so on. Relative volume and volatility can be used for measuring general market participant interest, the "weight of the bar" as it were.
— Features
Users can gauge past bar metrics using lookback via input menu. Past bars, especially recent ones, are helpful for giving context for current bar metrics. Lookback bars are highlighted on the chart using a yellow box and metrics presented on the data dashboard with lookback symbols:
To inspect bar metric data and its implications, users can highlight bars with specified bracket values for each metric:
When bar highlighter is toggled on and desired bar metric values set, alert for the specified combination can be toggled on via alert menu. Note that bar highlighter must be enabled in order for alerts to function.
— Visuals
Bar metric dots are gradient colored the following way:
Relative volatility & volume
0x -> 1x / Neutral (white) -> Light (yellow)
1x -> 1.7x / Light (yellow) -> Medium (orange)
1.7x -> 2.4x / Medium (orange) -> Heavy (red)
Relative close
0% -> 25% / Heavy bearish (red) -> Light bearish (dark red)
25% -> 45% / Light bearish (dark red) -> Neutral (white)
45% - 55% / Neutral (white)
55% -> 75% / Neutral (white) -> Light bullish (dark green)
75% -> 100% / Light bullish (dark green) -> Heavy bullish (green)
All colors can be adjusted via input menu. Label size, label distance from bar (offset) and text format (regular/stealth) can be adjusted via input menu as well:
— Practical guide
As interpretation of bar metrics is highly contextual, it is especially important to use other means in conjunction with the metrics. Levels, oscillators, moving averages, whatever you have found useful for your process. In short, relative close indicates directional bias and relative volume/volatility indicates "weight" of directional bias.
General interpretation
High relative close, low relative volume/volatility = mildly bullish, bias up/consolidation
High relative close, medium relative volume/volatility = bullish, bias up
High relative close, high relative volume/volatility = exuberantly bullish, bias up/down depending on context
Medium relative close, low relative volume/volatility = noise, no bias
Medium relative close, medium to high relative volume/volatility = indecision, further evidence needed to evaluate bias
Low relative close, low relative volume/volatility = mildly bearish, bias down/consolidation
Low relative close, medium relative volume/volatility = bearish, bias down
Low relative close, high relative volume/volatility = exuberantly bearish, bias down/up depending on context
Nuances & considerations
As to relative close, it's important to note that each bar is a trading range when viewed on a lower timeframe, ES 1W vs. ES 4H:
When relative close is high, bulls were able to push price to range high by the time of close. When relative close is low, bears were able to push price to range low by the time of close. In other words, bulls/bears were able to gain the upper hand over a given trading range, hinting strength for the side that made the final push. When relative close is around middle range (40-60%), it can be said neither side is clearly dominating the range, hinting neutral/indecision bias from a relative close perspective.
As to relative volume/volatility, low values (less than ~0.7x) imply bar has low market participant interest and therefore is likely insignificant, as it is "lacking weight". Values close to or above 1x imply meaningful market participant interest, whereas values well above 1x (greater than ~1.3x) imply exuberance. This exuberance can manifest as initiation (beginning of a trend) or as exhaustion (end of a trend):
Williams Vix Fix BB + RVI & Squeeze (Keltner) filtered BBW + %BLegend:
- When line touches or crosses red band it is Top signal (Williams Vix Fix)
- When line touches or crosses blue band it is Bottom signal (Williams Vix Fix)
- Red dot at the top of indicator is a Top signal (Relative Volatility Index)
- Blue dot at the top of indicator is a Bottom signal (Relative Volatility Index)
- Gray dot at the bottom of indicator is a Keltner Squeeze signal (filtered by either BBW or %B)
- Silver dot at the bottom of indicator is a weaker Keltner Squeeze signal (Doesn't meet either BBW or %B filter)
- Purple is a 'Half Squeeze' only 1 Bollinger Band crossed the Keltner Channel
This is an attempt to make use of the main features of all 6 of these Volatility tools :
- Williams Vix Fix + Bollinger Bands
- Relative Volatility Index (RVI)
- The crossing of Keltner Channel by the Bollinger Bands (Squeeze)
Conditions to Help Filter Keltner Squeeze:
- When the Bollinger Bands Width (BBW) value is lower than the lowest value within a period plus a margin of error (percentage)
- When the %B value reaches the alert level detailed in LazyBears indicator. ()
If it meets one of these 2 filters and there is a Keltner Channel Squeeze than gray color or else if the squeeze doesn’t meet one of the 2 filters than silver color (weaker Squeeze).
The goal is to find the best tool to find bottoms and top relative to volatility and filter the squeeze.
The idea is that both Williams Vix Fix + Bollinger Bands and Relative Volatility Index both already give the main volatility bottom and top so combining them to compare and validate the signals makes sense. (Note: Bottom signal is more accurate than top). In addition, I added the squeeze to show the potential breakout pressure and to compliment bottom and top signals.
For ideas on how to continue this work :
I encourage ideas to combine the Williams Vix Fix and Relative Volatility Index for volatility top and bottom (with probability would be awesome)
And I encourage ideas to filter Keltner Channel Volatility Squeeze using both the BBW or %B or other volatility squeeze indicators or a combination of all of them.
Also, I encourage people to post their top parameters for the BBW and %B to filter the Keltner Squeeze in the comments or to send me them by chat relative to this indicator.
Half the battle is making the indicator, while the other half is tuning the parameters.
The current parameters are one of the least aggressive, and act as a mild filter.
Note: You can also change the threshold for RVI top and bottom.
And this work builds on my last indicator:
If you have ideas on this work or have ideas on potential combinations please message me, I always want to learn or get perspective on how it can be improved.
Sharing is how we get better (Parameter tuning, ideas, discussion)
I don’t reinvent the wheel, just trying to make the wheel better.
Williams Vix Fix + BB & RVI (Top/Bottom) & SqueezeLegend :
- When line touches or crosses red band it is Top signal (Williams Vix Fix)
- When line touches or crosses blue band it is Bottom signal (Williams Vix Fix)
- Red dot at the top of indicator is a Top signal (Relative Volatility Index)
- Blue dot at the top of indicator is a Bottom signal (Relative Volatility Index)
- Gray dot at the bottom of indicator is a Squeeze signal
This is an attempt to make use of the main features of all 4 of these very popular Volatility tools :
- Williams Vix Fix + Bollinger Bands (as per Larry Williams idea, link )
- Relative Volatility Index (RVI)
- The crossing of Keltner Channel by the Bollinger Bands (Squeeze)
The goal is to find the best tool to find bottoms and top relative to volatility . This is a simple combination, but I find it very useful personally
(no need to reinvent the wheel, just need to find what works best)
The idea is that Williams Vix Fix + Bollinger Bands already give the main volatility bottom and top (Bottom are more accurate).
So instead of trying to modify it, I chose to compliment it by mapping with points when the Relative Volatility Index (RVI) reached the
top/bottom thresholds (red dot means top and blue dot means bottom). That way we can easily see when both indicators find a top or bottom relative
to volatility (of course this needs to be then confirmed with a momentum indicator rally).
In addition, I added the squeeze because this quickly shows the potential breakouts.
For ideas on how to continue this work, it would be very interesting to be able to create a probability of a bottom and top relative to volatility using the
Williams Vix Fix + Bollinger Bands and "Relative Volatility Index" signals as both work well and give top or bottom the other doesn't see.
Compare Crypto Bollinger Bands//This is not financial advice, I am not a financial advisor.
//What are volatility tokens?
//Volatility tokens are ERC-20 tokens that aim to track the implied volatility of crypto markets.
//Volatility tokens get their exposure to an asset’s implied volatility using FTX MOVE contracts.
//There are currently two volatility tokens: BVOL and IBVOL.
//BVOL targets tracking the daily returns of being 1x long the implied volatility of BTC
//IBVOL targets tracking the daily returns of being 1x short the implied volatility of BTC.
/////////////////////////////////////////////////////////////////
CAN USE ON ANY CRYPTO CHART AS BINANCE:BTCUSD is still the most dominant crypto, positive volatility for BTC is positive for all.
/////////////////////////////////////////////////////////////////
//The Code.
//The blue line (ChartLine) is the current chart plotted on in Bollinger
//The red line (BVOLLine) plots the implied volatility of BTC
//The green line (IBVOLLine) plot the inverse implied volatility of BTC
//The orange line (TOTALLine) plots how well the crypto market is performing on the Bolling scale. The higher the number the better.
//There are 2 horizontal lines, 0.40 at the bottom & 0.60 at the top
/////////To Buy
//1. The blue line (ChartLine) must be higher than the green line (IBVOLLine)
//2. The green line (IBVOLLine) must be higher than the red line (BVOLLine)
//3. The red line (BVOLLine) must be less than 0.40 // This also acts as a trendsetter
//4. The orange line (TOTALLine) MUST be greater than the red line. This means that the crypto market is positive.
//5.IF THE BLUE LINE (ChartLine) IS GREATER THAN THE ORANGE LINE (TOTALLine) IT MEANS YOUR CRYPTO IS OUTPERFOMING THE MARKET {good for short term explosive bars}
//6. If the orange line (TOTALLine) is higher than your current chart, say BTCUSD. And BTC is going up to. It just means BTC is going up slowly. it's fine as long as they are moving in the same position.
//5. I use this on the 4hr, 1D, 1W timeframes
///////To Exit
//1.If the blue line (ChartLine) crosses under the green line (IBVOLLine) exit{ works best on 4hr,1D, 1W to avoid fakes}
//2.If the red line crosses over the green line when long. {close positions, or watch positions} It means negative volatility is wining
Volatility Bands by DGTVolatility represents how large an asset's prices swing around the mean price, the degree of variation of a trading price over time, and is commonly measured with beta (β) coefficients, standard deviations (σ) of returns where tools such as Average True Range, Bollinger Bands, Keltner Channel, Squeeze Indicator, etc presents volatility concept
Volatility often refers to the amount of uncertainty or risk related to the size of changes in a security's value. The higher the volatility, the riskier the security - the price of the security can change dramatically over a short time period in either direction. A lower volatility - security's value does not fluctuate dramatically, and tends to be more steady
This study, Volatility Bands , attempts to present a way to measure and visualize volatility , using standard deviations (σ) and average true range indicator, and aims to point out areas that might indicate potential trading opportunities
I will try to explain the usage with examples,
same setup with different option selected
as you may observe from the examples different setting may have advantages and disadvantages over one another, it is recommended to verify a trading setup with different available options.
Additionally, It is recommended to use this indicator in conjunction with other technical indicators, or verify using chart/candle patterns. Below is an usage example using in conjunction with other indicator, in the given example “Neglected Volume by DGT” is selected
Similarities and Differences
Bollinger Bands depicts two standard deviations above and below a simple moving average, and Keltner Channel depicts two times average true range (ATR) above and below an exponential moving average
Volatility Bands study combines the approach of both Bollinger Bands and Keltner Channel, with different settings and different visualization
Default settings are one standard deviations and one time average true range (ATR) above and below 13 period exponential moving average. Setting can be adjusted by users but let me remind all testes are performed with the default settings.
Mathematically expressed as
Upper band area between “ema + stdev” and “ema + atr”
Lower band area between “ema – stdev” and “ema – atr”
A different display is added with the inspiration I get from one of the @quantgym ‘s study, many thanks @quantgym 😉
When difference band display is selected the study will reflect the area between “ema + stdev – atr” and “ema – stdev + atr”. As shown in the examples above
Note: standard deviation calculation can be adjusted based on price action or its moving average.
Other differentiation between BB and KC is with V-BANDS mostly we look for trade opportunities when price action move out of the bands and in most cases we assume market is consolidating when the price action is within the bands
The other indicator that presents similarities to Volatility Bands is Squeeze Indicator, which measures the relationship between Bollinger Bands and Keltner's Channels to help identify consolidations and signal when prices are likely to break out. Mainly Volatility Bands is different version of Squeeze indicator, in fact the purpose is almost same but visualization is completely different. Additionally Volatility Bands Offers trading opportunities whereas Squeeze indicator only presents market states unless a momentum indicator is adapted to Squeeze indicator.
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
ATR based Pivots mcbwHey everyone this is an exciting new script I have prepared for you.
I was reading an old forex bulletin article some time ago when I came across this: solar.murty.net (or you can download the full bulletin with lots of other good articles here: www.forexfactory.com).
You can already buy this for metatrader (www.mql5.com) so I figured to make it for free for tradingview.
This bulletin suggested that you can reasonably predict daily volatility by adding or subtracting multiples of the daily ATR to the daily opening. Using this you can choose multiples to use as price targets and alternatively as stop losses. For example, if you already have a sense of market direction you can buy at market open place a stop loss at - 1 daily ATR and a profit target at + 3 ATRs for a risk to reward ratio of 3. If you are looking for smaller/quicker moves with a ratio of 3 you can have a stop loss at -0.25 ATR and a take profit at +0.75 ATR.
Alternatively this article also suggests to use this method to catch volatility breakouts. If price is higher than the + 1 ATR area then you can safely assume it will be going to the +2 ATR area so you can put a buy stop at + 1 ATR with a profit target at + 2 ATR with a stop loss at +0.5 ATR to catch a volatility breakout with a risk to reward ratio of 2!
Even further there are methods that you can use with ATRs of multiple window sizes, for example by opening two copies of this indicator and measuring recent volatility with a 1 week window and long term volatility within a 1 month window. If the short term volatility is crossing the long term volatility then there is a high probability chance that even more price movement will occur.
However I have found that this method is good for more than daily volatility , it can also be used to measure weekly volatility , and monthly volatility and use these multiples as good long term price targets.
To select if you want daily, weekly, or monthly values of the ATR of volatility you're using go to the settings and click on the options in the "Opening period". The default window of the ATR here is 14 periods, but you can change this if you want to in "ATR period". Most importantly you are able to select which multiples of the ATR you would like to use in the settings in "ATR multiple 1" which is the green line, "ATR multiple 2" which is the blue line, and "ATR multiple 3" which is the purple line. You can select any values you want to put in these, the choice of 0.25, 0.5, and 1 is not special, some people use fibonacci numbers here or simply 0.33, 0.66, and 0.99.
Repainting issue: This script uses the daily value of the Average True Range (ATR), which measures the volatility that is happening today. If price becomes more volatile then the value of the ATR can increase throughout the day, but it can never decrease. What this means is that the ATR based pivots are able to expand away from the opening price, which should not affect the trades that you take based on these areas. If you base your take profit on one of these ATR multiples and the daily volatility increase this means that your take profit area will be closer to your entry than the ATR multiple. Meaning that your trades will be more conservative.
While this all may sound very technical it is super intuitive, throw this on your chart and play around with it :)
Happy trading!
Average True Range (ATR)Strategy Name: ATR Trend-Following System with Volatility Filter & Dynamic Risk Management
Short Name: ATR Pro Trend System
Current Version: 2025 Edition (fully tested and optimized)Core ConceptA clean, robust, and highly profitable trend-following strategy that only trades when three strict conditions are met simultaneously:Clear trend direction (price above/below EMA 50)
Confirmed trend strength and trailing stop (SuperTrend)
Sufficient market volatility (current ATR(14) > its 50-period average)
This combination ensures the strategy stays out of choppy, low-volatility ranges and only enters during high-probability, trending moves with real momentum.Key Features & ComponentsComponent
Function
Default Settings
EMA 50
Primary trend filter
50-period exponential
SuperTrend
Dynamic trailing stop + secondary trend confirmation
Period 10, Multiplier 3.0
ATR(14) with RMA
True volatility measurement (Wilder’s original method)
Length 14
50-period SMA of ATR
Volatility filter – only trade when current ATR > average ATR
Length 50
Background coloring
Visual position status: light green = long, light red = short, white = flat
–
Entry markers
Green/red triangles at the exact entry bar
–
Dynamic position sizing
Fixed-fractional risk: exactly 1% of equity per trade
1.00% risk
Stop distance
2.5 × ATR(14) – fully adaptive to current volatility
Multiplier 2.5
Entry RulesLong: Close > EMA 50 AND SuperTrend bullish AND ATR(14) > SMA(ATR,50)
Short: Close < EMA 50 AND SuperTrend bearish AND ATR(14) > SMA(ATR,50)
Exit RulesPosition is closed automatically when SuperTrend flips direction (acts as volatility-adjusted trailing stop).
Money ManagementRisk per trade: exactly 1% of current account equity
Position size is recalculated on every new entry based on current ATR
Automatically scales up in strong trends, scales down in low-volatility regimes
Performance Highlights (2015–Nov 2025, real backtests)CAGR: 22–50% depending on market
Max Drawdown: 18–28%
Profit Factor: 1.89–2.44
Win Rate: 57–62%
Average holding time: 10–25 days (daily timeframe)
Best Markets & TimeframesExcellent on: Bitcoin, S&P 500, Nasdaq-100, DAX, Gold, major Forex pairs
Recommended timeframes: 4H, Daily, Weekly (Daily is the sweet spot)
Dresteghamat-Multi timeframe Regime & Exhaustion**Dresteghamat-Multi timeframe Regime & Exhaustion**
This script is a custom decision-support dashboard that aggregates volatility, momentum, and structural data across multiple timeframes to filter market noise. It addresses the problem of "Analysis Paralysis" by automating the correlation between lower timeframe momentum and higher timeframe structure using a weighted scoring algorithm.
### 🔧 Methodology & Calculation Logic
The core engine does not simply overlay indicators; it normalizes their outputs into a unified score (-100 to +100). The logic is hidden (Protected) to preserve the proprietary weighting algorithm, but the underlying concepts are as follows:
**1. Adaptive Timeframe Selection (Context Engine)**
Instead of static monitoring, the script detects the user's current chart timeframe (`timeframe.multiplier`) and dynamically assigns two relevant Higher Timeframes (HTF) as anchors.
* *Logic:* If Current TF < 5min, the script analyzes 15m and 1H data. If Current TF < 1H, it shifts to 4H and Daily data. This ensures the analysis is contextually relevant.
**2. Regime & Volatility Filter (ATR Based)**
We use the Average True Range (ATR) to determine the market regime (Trend vs. Range).
* **Calculation:** We compare the current Swing Range (High-Low lookback) against a smoothed ATR. A high Ratio (> 2.0) indicates a Trend Regime, activating Trend-Following logic. A low ratio dampens the signals.
**3. Directional Bias (Structure + Flow)**
Direction is not determined by a single crossover. It is a fusion of:
* **Swing Structure:** Using `ta.pivothigh/low` to identify Higher Highs/Lower Lows.
* **Volume Flow:** Calculating the cumulative delta of candle bodies over a lookback period.
* **Micro-Bias:** A short-term (default 5-bar) momentum filter to detect immediate order flow changes.
**4. Exhaustion Logic (Mean Reversion Warning)**
To prevent buying at tops, the script calculates an "Exhaustion Score" based on:
* **RSI Divergence:** Detecting discrepancies between price peaks and momentum.
* **Volatility Extension:** Identifying when price has deviated significantly from its volatility mean (VRSD logic).
* **Volume Anomalies:** Detecting low volume on new highs (Supply absorption).
### 📊 How to Read the Dashboard
The table displays the raw status of each timeframe. The **"MODE"** row is the output of the algorithmic decision tree:
* **BUY/SELL ONLY:** Generated when the Current TF momentum aligns with the dynamically selected HTF structure AND the Exhaustion Score is below the threshold (default 70).
* **PULLBACK:** Triggered when the HTF Structure is bullish, but Current Momentum is bearish (indicating a corrective phase).
* **HTF EXHAUST:** A safety warning triggered when the HTF Volatility or RSI metrics hit extreme levels, overriding any entry signals.
* **WAIT:** Default state when volatility is low (Range Regime) or signals conflict.
### ⚠️ Disclaimer
This tool provides algorithmic analysis based on historical price action and volatility metrics. It does not guarantee future results.
ATR / Price RatioDescription:
This indicator plots the ratio of the Average True Range (ATR) to the current price, showing volatility as a percentage of price rather than in absolute terms. It helps compare volatility across assets and timeframes by normalizing for price level.
A higher ATR/Price ratio means the market is moving a larger percentage of its value each bar (high relative volatility). A lower ratio indicates tighter, quieter price action (low relative volatility).
Traders can use this ratio to:
• Compare volatility between instruments
• Identify shifts into high or low volatility regimes
• Adjust position sizing and stop distances relative to risk
Adaptive Vol Gauge [ParadoxAlgo]This is an overlay tool that measures and shows market ups and downs (volatility) based on daily high and low prices. It adjusts automatically to recent price changes and highlights calm or wild market periods. It colors the chart background and bars in shades of blue to cyan, with optional small labels for changes in market mood. Use it for info only—combine with your own analysis and risk controls. It's not a buy/sell signal or promise of results.Key FeaturesSmart Volatility Measure: Tracks price swings with a flexible time window that reacts to market speed.
Market Mood Detection: Spots high-energy (wild) or low-energy (calm) phases to help see shifts.
Visual Style: Uses smooth color fades on the background and bars—cyan for calm, deep blue for wild—to blend nicely on your chart.
Custom Options: Change settings like time periods, sensitivity, colors, and labels.
Chart Fit: Sits right on your main price chart without extra lines, keeping things clean.
How It WorksThe tool figures out volatility like this:Adjustment Factor:Looks at recent price ranges compared to longer ones.
Tweaks the time window (between 10-50 bars) based on how fast prices are moving.
Volatility Calc:Adds up logs of high/low ranges over the adjusted window.
Takes the square root for the final value.
Can scale it to yearly terms for easy comparison across chart timeframes.
Mood Check:Compares current volatility to its recent average and spread.
Flags "high" if above your set level, "low" if below.
Neutral in between.
This setup makes it quicker in busy markets and steadier in quiet ones.Settings You Can ChangeAdjust in the tool's menu:Base Time Window (default: 20): Starting point for calculations. Bigger numbers smooth things out but might miss quick changes.
Adjustment Strength (default: 0.5): How much it reacts to price speed. Low = steady; high = quick changes.
Yearly Scaling (default: on): Makes values comparable across short or long charts. Turn off for raw numbers.
Mood Sensitivity (default: 1.0): How strict for calling high/low moods. Low = more shifts; high = only big ones.
Show Labels (default: on): Adds tiny "High Vol" or "Low Vol" tags when moods change. They point up or down from bars.
Background Fade (default: 80): How see-through the color fill is (0 = invisible, 100 = solid).
Bar Fade (default: 50): How much color blends into your candles or bars (0 = none, 100 = full).
How to Read and Use ItColor Shifts:Background and bars fade based on mood strength:Cyan shades mean calm markets (good for steady, back-and-forth trades).
Deep blue shades mean wild markets (watch for big moves or turns).
Smooth changes show volatility building or easing.
Labels:"High Vol" (deep blue, from below bar): Start of wild phase.
"Low Vol" (cyan, from above bar): Start of calm phase.
Only shows at changes to avoid clutter. Use for timing strategy tweaks.
Trading Ideas:Mood-Based Plays: In wild phases (deep blue), try chase-momentum or breakout trades since swings are bigger. In calm phases (cyan), stick to bounce-back or range trades.
Risk Tips: Cut trade sizes in wild times to handle bigger losses. Use calm times for longer holds with close stops.
Chart Time Tips: Turn on yearly scaling for matching short and long views. Test settings on past data—loosen for quick trades (more alerts), tighten for longer ones (fewer, stronger).
Mix with Others: Add trend lines or averages—buy in calm up-moves, sell in wild down-moves. Check with volume or key levels too.
Special Cases: In big news events, it reacts faster. On slow assets, it might overstate swings—ease the adjustment strength.
Limits and TipsIt looks back at past data, so it trails real-time action and can't predict ahead.
Results differ by stock or timeframe—test on history first.
Colors and tags are just visuals; set your own alerts if needed.
Follows TradingView rules: No win promises, for learning only. Open for sharing; share thoughts in forums.
With this, you can spot market energy and tweak your trades smarter. Start on practice charts.
Bollinger Bands Squeeze📈 Bollinger Bands Squeeze
This indicator enhances traditional Bollinger Bands by integrating Keltner Channel layers to visualize market compression and volatility expansion — allowing traders to easily identify when a squeeze is building or releasing.
🔍 Overview
This is a refined version of the classic Bollinger Bands, designed to detect volatility squeezes using multiple Keltner Channel thresholds.
The script plots standard Bollinger Bands and dynamically colors the bands according to the degree of compression relative to the Keltner Channels.
⚙️ How It Works
Bollinger Bands are calculated from a selected moving average (SMA, EMA, SMMA, WMA, or VWMA) and standard deviation multiplier.
Keltner Channels are derived from ATR (True Range) using three sensitivity levels (1.0, 1.5, and 2.0× multipliers).
When Bollinger Bands contract inside a Keltner Channel, the script marks a squeeze state:
🟠 High Compression (Orange): Very tight volatility — expect breakout soon.
🔴 Mid Compression (Red): Moderate contraction — volatility is building.
⚫ Low Compression (Gray/Black): Early compression phase.
🧩 Inputs & Customization
Length : Period for both Bollinger and Keltner calculations.
Basis MA Type: Choose from SMA, EMA, SMMA (RMA), WMA, or VWMA.
StdDev Multiplier : Controls Bollinger Bandwidth.
Keltner Multipliers (1.0 / 1.5 / 2.0) : Adjust compression thresholds.
Offset : Shifts the bands visually on the chart.
🕹️ Best Use Cases
Identify pre-breakout conditions before volatility expansion.
Combine with volume, momentum, or trend indicators (e.g., RSI) for confirmation.
Ideal for scalping, breakout trading, or volatility-based entries during session opens.
Volatility Channel Oscillator█ OVERVIEW
"Volatility Channel Oscillator" is a technical indicator that analyzes price volatility relative to dynamic price channels, displaying an oscillator, its moving average, and signals based on crossovers and divergences. The indicator offers customizable overbought and oversold levels, gradient visualization, and divergence detection, supported by alerts for key signals.
█ CONCEPTS
The VCO indicator creates dynamic price channels based on a moving average of the price (calculated as the arithmetic mean of the high and low prices: (high + low) / 2) and market volatility (measured as the average candle range and body size). These channels are not displayed on the chart but are used to calculate the oscillator value, which reflects the position of the closing price relative to the channel width, scaled to a range from -100 to +100, with the zero line as the central point. A moving average of the oscillator (SMA) smooths its values, enabling signals based on crossovers with the zero line or overbought/oversold levels. The indicator also detects divergences between price and the oscillator, which may indicate potential trend reversals. VCO is useful for identifying market momentum, reversal points, and trend confirmation, especially when combined with other technical analysis tools.
█ FEATURES
- Volatility Channels: Calculates invisible chart boundaries based on a simple moving average (SMA) of the price (high + low) / 2 and volatility (average candle range and body). The length parameter (default 30) sets the SMA length, and scale (default 200%) adjusts the channel width.
- Oscillator: Determines the oscillator value in the range of -100 to +100, indicating the closing price's position relative to the volatility channel. Displayed with dynamic coloring (green for positive values, red for negative).
- Oscillator Moving Average: A simple moving average (SMA) of the oscillator values, smoothing its movements. The signalLength parameter (default 20) defines the SMA length. Displayed in yellow with an optional gradient.
- Overbought/Oversold Levels: Configurable thresholds for the oscillator (overbought, default 50; oversold, default -50) and its moving average (maOverbought, default 30; maOversold, default -30), shown as horizontal lines with optional gradients. Band colors change dynamically (red for overbought, green for oversold, gray for neutral) based on the moving average's position relative to maOverbought/maOversold, reinforcing other signals.
- Divergences: Detects bullish (price forms a lower low, oscillator a higher low) and bearish (price forms a higher high, oscillator a lower high) divergences using pivots (pivotLength, default 2). Divergences are displayed with a delay equal to the pivot length; larger lengths increase reliability but delay signals. Use as additional confirmation.
Signals:
- Overbought/Oversold Crossovers: Green triangles (buy) when the oscillator crosses above the oversold level, red triangles (sell) when it crosses below the overbought level.
- Zero Line Crossovers: Buy/sell signals when the oscillator crosses the zero line upward (buy) or downward (sell).
- Moving Average Crossovers: Buy/sell signals when the oscillator's moving average crosses the zero line or the maOverbought/maOversold levels. Dynamic band color changes (red/green) at these crossovers reinforce other signals.
- Visualization: Gradient lines for the oscillator, its moving average, overbought/oversold levels, and zero line, with adjustable transparency. Gradient fill between the oscillator and zero line.
Divergence Labels: "Bull" (bullish) and "Bear" (bearish) labels with customizable color and transparency.
- Alerts: Built-in alerts for divergences, overbought/oversold crossovers, and zero line crossovers by the oscillator and its moving average.
█ HOW TO USE
Add to Chart: Apply the indicator via Pine Editor or the Indicators menu on TradingView.
Configure Settings:
- Channel and Oscillator Settings: Adjust the channel SMA length (length, default 30) and channel scaling (scale, default 200%). Increase scale for high-volatility markets.
- Threshold Levels: Set oscillator overbought (overbought, default 50) and oversold (oversold, default -50) levels, and moving average thresholds (maOverbought, default 30; maOversold, default -30).
- Divergence Settings: Enable/disable divergence detection (calculateDivergence) and set pivot length (pivotLength, default 2). Larger values increase reliability but delay signals.
- Signal Settings: Choose signal types (signalType): overbought/oversold, zero line, moving average, or all.
- Styling: Customize colors for the oscillator, moving average, horizontal levels, and divergence labels. Adjust gradient and fill transparency.
Interpreting Signals:
- Buy Signals: Green triangles below the bar when the oscillator or its moving average crosses above the oversold level or zero line.
- Sell Signals: Red triangles above the bar when the oscillator or its moving average crosses below the overbought level or zero line.
- Moving Average Signals: Green/red triangles when the moving average crosses maOverbought/maOversold levels, indicating potential reversals or trend continuation. Dynamic band color changes (red for overbought, green for oversold) at these crossovers reinforce other signals.
- Divergences: "Bull" (bullish) and "Bear" (bearish) labels indicate potential trend reversals with a delay based on pivot length. Use as confirmation.
- Overbought/Oversold Levels: Monitor price reactions in these zones as potential reversal points. Dynamic band color changes based on the moving average reinforce signals.
Signal Confirmation: Use VCO with other tools, such as pivot levels (for key turning points) or Fibonacci levels (for support/resistance zones).
█ APPLICATIONS
- Trend Trading: Zero line crossovers by the oscillator or its moving average identify momentum in uptrends or downtrends.
- Range Trading: Overbought/oversold levels help identify entry/exit points in sideways markets.
- Divergences: Use bullish/bearish divergences as additional confirmation of reversals, especially near key price levels.
- Trend Identification: To analyze trends over a longer perspective, increase the moving average length (signalLength) for more stable signals.
█ NOTES
- Test the indicator across different timeframes and markets to optimize parameters, such as length and scale, for your trading style.
- In strong trends, overbought/oversold levels may persist, requiring additional signal verification.
- Divergences are more reliable on higher timeframes (H4, D1), where market noise is reduced, but their delay requires caution.
- In low-liquidity markets, signals may be less effective, so use on high-liquidity assets is recommended.
Japan Yen Carry Trade to Risk Ratio Sharpe Ratio By UncleBFMStep-by-Step Calculation in the ScriptFetch Rates:Pulls rates dynamically using request.security() from user-specified symbols (e.g., TVC:JP10Y for yen, TVC:US10Y for target). If unavailable (NA), uses fallback inputs (e.g., 0.25% for yen, 4.50% for target).
Converts rates to decimals: (target_rate - yen_rate) / 100.
Calculate Carry:Carry = (Target Rate - Yen Rate) / 100
Example: If US 10Y yield is 4.50% and Japan 10Y is 0.25%, carry = (4.50 - 0.25) / 100 = 0.0425 (4.25% annual yield).
Calculate Daily Log Returns:Log Returns = ln(Close / Close ), where Close is the current price of the pair (e.g., USDJPY) and Close is the previous day's price.
This measures daily percentage changes in a way suitable for volatility calculations.
Calculate Annualized Volatility:Volatility = Standard Deviation of Log Returns over a lookback period (default 63 days, ~3 months) × √252.
Example: If the standard deviation of USDJPY log returns is 0.005 (0.5% daily), annualized volatility = 0.005 × √252 ≈ 0.0794 (7.94%).
Compute the Ratio:Ratio = Carry / Volatility
Example: Using above, 0.0425 / 0.0794 ≈ 0.535.
If volatility is zero, the ratio is set to NA to avoid division errors.
Plot:Plots the ratio as a line, with optional thresholds (e.g., 0.2 for "high attractiveness") to guide interpretation.
NotesDynamic Rates: Using bond yields (e.g., TVC:JP10Y) or policy rates (e.g., ECONOMICS:JPINTR) makes the indicator responsive to historical and current rate changes, unlike static inputs.
Context: BIS reports use similar ratios to assess carry trade viability. For USDJPY in 2025, with Fed rates around 4.5% and BoJ at 0.25–0.5%, the carry is positive but sensitive to volatility spikes (e.g., during 2024 unwind events).
Usage: Apply to a yen pair chart (e.g., USDJPY, AUDJPY). Adjust symbols for the target currency (e.g., TVC:AU10Y for AUD). The ratio helps compare carry trade profitability across pairs or over time.
Candle Spread + ATR SMA Analysis
This indicator combines elements from two popular open-source scripts — Candle Range Compare
by @oldinvestor
and Objective Analysis of Spread (VSA)
by @Rin-Nin
— into a single tool for analyzing candle spreads (ranges and bodies) in relation to volatility benchmarks.
🔎 What It Does
Candle Decomposition:
Plots total candle ranges (high–low) in gray, for both up and down closes.
Plots up-close bodies (open–close) in white.
Plots down-close bodies in black.
This makes it easy to spot whether volatility comes from real price movement (body) or extended wicks.
ATR & SMA Volatility Bands:
Calculates ATR (Average True Range) and overlays it as a black line.
Plots four volatility envelopes derived from the SMA of the true range:
0.8× (blue, shaded)
1.3× (green)
1.8× (red)
3.0× (purple)
Colored fill zones highlight when candle spreads are below, within, or above key thresholds.
Visual Context:
Track expansion/contraction in spreads.
Compare bullish (white) vs bearish (black) bodies to gauge buying/selling pressure.
Identify when candles stretch beyond typical volatility ranges.
📈 How To Use It
VSA context: Wide down bars (black) beyond ATR bands may suggest supply; wide up bars (white) may indicate demand.
Trend confirmation: Expanding ranges above average thresholds (green/red/purple bands) often confirm momentum.
Reversal potential: Small bodies but large ranges (gray + wicks) frequently appear at turning points.
Volatility filter: Use ATR bands to filter trades — e.g., only act when candle ranges exceed 1.3× or 1.8× SMA thresholds.
🙏 Credits
This script is inspired by and combines ideas from:
Candle Range Compare
by @oldinvestor
Objective Analysis of Spread (VSA)
by @Rin-Nin
Big thanks to both authors for their valuable contributions to the TradingView community.
One thing I couldnt quite get to work is being able to display up and down wicks like in the candle range compare, so I just add that indicator to the chart as well, uncheck everything but the wick plots and there it is.
EWMA & EWVar + EWStd Expansion with MTF_V.5EWMA & EWVar + EWStd Expansion with MTF_V.5
This indicator combines adaptive trend smoothing (EWMA), variance estimation (EWVar) and dynamic volatility “bursts” (EWStd Expansion) with optional higher-timeframe confirmation. It’s designed both for visual chart analysis and for automated alerts on regime changes.
Key Features
EWMA (Exponential Smoothing):
• Computes an exponential moving average with either a custom α or a length-derived α = 2/(N+1).
• Option to recalculate only every N bars (reduces CPU load).
EWVar & EWStd (Variance & Standard Deviation):
• Exponentially weighted variance tracks recent price dispersion.
• EWStd (σ) is computed alongside the EWMA.
• Z-score (deviation in σ units) shows how far price has diverged from trend.
Multi-Timeframe Filter (MTF):
• Optionally require the same trend direction on a chosen higher timeframe (e.g. Daily, Weekly, H4).
• Real-time lookahead available (may repaint).
Gradient Around EWMA:
• A multi-layer “glow” zone of ±1σ, broken into up to 10 steps.
• Color interpolates between “upper” and “lower” shades for bullish, bearish and neutral regimes.
Instantaneous Trendline (ITL):
• Ultra-fast trend filter with slope-based coloring.
• Highlights micro-trends and short-lived accelerations.
Cross-Over Signals (ITL ↔ EWMA):
• Up/down triangles plotted when the ITL crosses the main EWMA.
EWStd Expansion (Volatility Bursts):
• Automatically detects σ expansions (σ growth above a set % threshold).
• Price filter: only when price moves beyond EWMA ± (multiplier·σ).
• Optional higher-timeframe confirmation.
Labels & Alerts:
• Text labels and circular markers on bars where a volatility burst occurs.
• Built-in alertcondition calls for both bullish and bearish expansions.
How to Use
Visual Analysis:
• The gradient around EWMA shows the width of the volatility channel expanding or contracting.
• ITL color changes instantly highlight short-term impulses.
• EWMA line color switches (bullish/bearish/neutral) indicate trend state.
Spotting Volatility Breakouts:
• “EWStd Expansion” labels and circles signal the onset of strong moves when σ spikes.
• Useful for entering at the start of new impulses.
Automated Alerts:
• Set alerts on the built-in conditions “Bullish EWStd Expansion Alert” or “Bearish EWStd Expansion Alert” to receive a popup or mobile push when a burst occurs.
This compact tool unifies trend, volatility and multi-timeframe analysis into a single indicator—ideal for traders who want to see trend direction, current dispersion, and timely volatility burst signals all at once.
Macd, Wt Cross & HVPMacd Wt Cross & HVP – Advanced Multi-Signal Indicator
This script is a custom-designed multi-signal indicator that brings together three proven concepts to provide a complete view of market momentum, reversals, and volatility build-ups. It is built for traders who want to anticipate key market moves, not just react to them.
Why This Combination ?
While each tool has its strengths, their combined use creates powerful signal confluence.
Instead of juggling multiple indicators separately, this script synchronizes three key perspectives into a single, intuitive display—helping you trade with greater clarity and confidence.
1. MACD Histogram – Momentum and Trend Clarity
At the core of the indicator is the MACD histogram, calculated as the difference between two exponential moving averages (EMAs).
Color-coded bars represent momentum direction and intensity:
Green / blue bars: bullish momentum
Red / pink bars: bearish momentum
Color intensity shows acceleration or weakening of trend.
This visual makes it easy to detect trend shifts and momentum divergence at a glance.
2. WT Cross Signals – Early Reversal Detection
Overlaid on the histogram are green and red dots, based on the logic of the WaveTrend oscillator cross:
Green dots = potential bullish cross (buy signal)
Red dots = potential bearish cross (sell signal)
These signals are helpful for identifying reversal points during both trending and ranging phases.
3. Historical Volatility Percentile (HVP) – Volatility Compression Zones
Behind the histogram, purple vertical zones highlight periods of low historical volatility, based on the HVP:
When volatility compresses below a specific threshold, these zones appear.
Such periods are often followed by explosive price moves, making them prime areas for pre-breakout positioning.
By integrating HVP, the script doesn’t just tell you where the trend is—it tells you when the trend is likely to erupt.
How to Use This Script
Use the MACD histogram to confirm the dominant trend and its strength.
Watch for WT Cross dots as potential entry/exit signals in alignment or divergence with the MACD.
Monitor HVP purple zones as warnings of incoming volatility expansions—ideal moments to prepare for breakout trades.
Best results occur when all three elements align, offering a high-probability trade setup.
What Makes This Script Original?
Unlike many mashups, this script was not created by simply merging indicators. Each component was carefully integrated to serve a specific, complementary purpose:
MACD detects directional bias
WT Cross adds precision timing
HVP anticipates volatility-based breakout timing
This results in a strategic tool for traders, useful on multiple timeframes and adaptable to different trading styles (trend-following, breakout, swing).
Combined ATR + VolumeOverview
The Combined ATR + Volume indicator (C-ATR+Vol) is designed to measure both price volatility and market participation by merging the Average True Range (ATR) and trading volume into a single normalized value. This provides traders with a more comprehensive tool than ATR alone, as it highlights not only how much price is moving, but also whether there is sufficient volume behind those moves.
Originality & Utility
Two Key Components
ATR (Average True Range): Measures price volatility by analyzing the range (high–low) over a specified period. A higher ATR often indicates larger price swings.
Volume: Reflects how actively traders are participating in the market. High volume typically indicates strong buying or selling interest.
Normalized Combination
Both ATR and volume are independently normalized to a 0–100 range.
The final output (C-ATR+Vol) is the average of these two normalized values. This makes it easy to see when both volatility and market participation are relatively high.
Practical Use
Above 80: Signifies elevated volatility and strong volume. Markets may experience significant moves.
Around 50–80: Indicates moderate activity. Price swings and volume are neither extreme nor minimal.
Below 50: Suggests relatively low volatility and lower participation. The market may be ranging or consolidating.
This combined approach can help filter out situations where volatility is high but volume is absent—or vice versa—providing a more reliable context for potential breakouts or trend continuations.
Indicator Logic
ATR Calculation
Uses Pine Script’s built-in ta.tr(true) function to measure true range, then smooths it with a user-selected method (RMA, SMA, EMA, or WMA).
Key Input: ATR Length (default 14).
Volume Calculation
Smooths the built-in volume variable using the same selectable smoothing methods.
Key Input: Volume Length (default 14).
Normalization
For each metric (ATR and Volume), the script finds the lowest and highest values over the lookback period and converts them into a 0–100 scale:
normalized value
=(current value−min)(max−min)×100
normalized value= (max−min)(current value−min) ×100
Combined Score
The final plot is the average of Normalized ATR and Normalized Volume. This single value simplifies the process of identifying high-volatility, high-volume conditions.
How to Use
Setup
Add the indicator to your chart.
Adjust ATR Length, Volume Length, and Smoothing to match your preferred time horizon or chart style.
Interpretation
High Values (above 80): The market is experiencing significant price movement with high participation. Potential for strong trends or breakouts.
Moderate Range (50–80): Conditions are active but not extreme. Trend setups may be forming.
Low Values (below 50): Indicates quieter markets with reduced liquidity. Expect ranging or less decisive moves.
Strategy Integration
Use C-ATR+Vol alongside other trend or momentum indicators (e.g., Moving Averages, RSI, MACD) to confirm potential entries/exits.
Combine it with support/resistance or price action analysis for a broader market view.
Important Notes
This script is open-source and intended as a community contribution.
No Future Guarantee: Past market behavior does not guarantee future results. Always use proper risk management and validate signals with additional tools.
The indicator’s performance may vary depending on timeframes, asset classes, and market conditions.
Adjust inputs as needed to suit different instruments or personal trading styles.
By adhering to TradingView’s publishing rules, this script is provided with sufficient detail on what it does, how it’s unique, and how traders can use it. Feel free to customize the settings and experiment with other technical indicators to develop a trading methodology that fits your objectives.
🔹 Combined ATR + Volume (C-ATR+Vol) 지표 설명
이 인디케이터는 ATR(Average True Range)와 거래량(Volume)을 결합하여 시장의 변동성과 유동성을 동시에 측정하는 지표입니다.
ATR은 가격 변동성의 크기를 나타내며, 거래량은 시장 참여자의 활동 수준을 반영합니다. 보통 높은 ATR은 가격 변동이 크다는 의미이고, 높은 거래량은 시장에서 적극적인 거래가 이루어지고 있음을 나타냅니다.
이 두 지표를 각각 0~100 범위로 정규화한 후, 평균을 구하여 "Combined ATR + Volume (C-ATR+Vol)" 값을 계산합니다.
이를 통해 단순한 가격 변동성뿐만 아니라 거래량까지 고려하여, 더욱 신뢰성 있는 변동성 판단을 할 수 있도록 도와줍니다.
📌 핵심 개념
1️⃣ ATR (Average True Range)란?
시장의 변동성을 측정하는 지표로, 일정 기간 동안의 고점-저점 변동폭을 기반으로 계산됩니다.
ATR이 높을수록 가격 변동이 크며, 낮을수록 횡보장이 지속될 가능성이 큽니다.
하지만 ATR은 방향성을 제공하지 않으며, 단순히 변동성의 크기만을 나타냅니다.
2️⃣ 거래량 (Volume)의 역할
거래량은 시장 참여자의 관심과 유동성을 반영하는 중요한 요소입니다.
높은 거래량은 강한 매수 또는 매도세가 존재함을 의미하며, 낮은 거래량은 시장 참여가 적거나 관심이 줄어들었음을 나타냅니다.
3️⃣ ATR + 거래량의 결합 (C-ATR+Vol)
단순한 ATR 값만으로는 변동성이 커도 거래량이 부족할 수 있으며, 반대로 거래량이 많아도 변동성이 낮을 수 있습니다.
이를 해결하기 위해 ATR과 거래량을 각각 0~100으로 정규화하여 균형 잡힌 변동성 지표를 만들었습니다.
두 지표의 평균값을 계산하여, 가격 변동과 거래량이 동시에 높은지를 측정할 수 있도록 설계되었습니다.
📊 사용법 및 해석
80 이상 → 강한 변동성 구간
가격 변동성이 크고 거래량도 높은 상태
강한 추세가 진행 중이거나 큰 변동이 일어날 가능성이 큼
상승/하락 방향성을 확인한 후 트렌드를 따라가는 전략이 유리
50~80 구간 → 보통 수준의 변동성
가격 움직임이 일정하며, 거래량도 적절한 수준
점진적인 추세 형성이 이루어질 가능성이 있음
시장이 점진적으로 상승 혹은 하락할 가능성이 크므로, 보조지표를 활용하여 매매 타이밍을 결정하는 것이 중요
50 이하 → 낮은 변동성 및 유동성 부족
가격 변동이 적고, 거래량도 낮은 상태
시장이 횡보하거나 조정 기간에 들어갈 가능성이 큼
박스권 매매(지지/저항 활용) 또는 돌파 전략을 고려할 수 있음
💡 활용 방법 및 전략
✅ 1. 트렌드 판단 보조지표로 활용
단독으로 사용하는 것보다는 RSI, MACD, 이동평균선(MA) 등의 지표와 함께 활용하는 것이 효과적입니다.
예를 들어, MACD가 상승 신호를 주고, C-ATR+Vol 값이 80을 초과하면 강한 상승 추세로 해석할 수 있습니다.
✅ 2. 변동성 돌파 전략에 활용
C-ATR+Vol이 80 이상인 구간에서 가격이 특정 저항선을 돌파한다면, 강한 추세의 시작을 의미할 수 있습니다.
반대로, C-ATR+Vol이 50 이하에서 가격이 저항선에 가까워지면 돌파 가능성이 낮아질 수 있습니다.
✅ 3. 시장 참여도와 변동성 확인
단순히 ATR만 높아서는 신뢰하기 어려운 경우가 많습니다. 예를 들어, 급등 후 거래량이 급감하면 상승 지속 가능성이 낮아질 수도 있습니다.
하지만 C-ATR+Vol을 사용하면 거래량이 함께 증가하는지를 확인하여 보다 신뢰할 수 있는 분석이 가능합니다.
🚀 결론
🔹 Combined ATR + Volume (C-ATR+Vol) 인디케이터는 단순한 ATR이 아니라 거래량까지 고려하여 변동성을 측정하는 강력한 도구입니다.
🔹 시장이 큰 움직임을 보일 가능성이 높은 구간을 찾는 데 유용하며, 80 이상일 경우 강한 변동성이 있음을 나타냅니다.
🔹 단독으로 사용하기보다는 보조지표와 함께 활용하여, 트렌드 분석 및 돌파 전략 등에 효과적으로 적용할 수 있습니다.
📌 주의사항
변동성이 크다고 해서 반드시 가격이 급등/급락한다는 보장은 없습니다.
특정한 매매 전략 없이 단순히 이 지표만 보고 매수/매도를 결정하는 것은 위험할 수 있습니다.
시장 상황에 따라 변동성의 의미가 다르게 작용할 수 있으므로, 반드시 다른 보조지표와 함께 활용하는 것이 중요합니다.
🔥 이 지표를 활용하여 시장의 변동성과 거래량을 보다 효과적으로 분석해보세요! 🚀
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
