ICT PDA - Gold & BTC (QuickScalp Bias/FVG/OB/OTE + Alerts)What this script does
This indicator implements a complete ICT Price Delivery Algorithm (PDA) workflow tailored for XAUUSD and BTCUSD. It combines HTF bias, OTE zones, Fair Value Gaps, Order Blocks, micro-BOS confirmation, and liquidity references into a single, cohesive tool with early and final alerts. The script is not a mashup for cosmetic plotting; each component feeds the next decision step.
Why this is original/useful
Symbol-aware impulse filter: A dynamic displacement threshold kTune adapts to Gold/BTC volatility (body/ATR vs. per-symbol factor), reducing noise on fast markets without hiding signals.
Scalping preset: “Quick Clean” mode limits drawings to the most recent bars and keeps only the latest FVG/OB zones for a clear chart.
Three display modes: Full, Clean, and Signals-Only to match analysis vs. execution.
Actionable alerts: Early heads-up when price enters OTE in the HTF bias direction, and Final alerts once mitigation + micro-break confirm the setup.
How it works (high-level logic)
HTF Bias: Uses request.security() on a user-selected timeframe (e.g., 240m) and EMA filter. Bias = close above/below HTF EMA.
Dealing Range & OTE: Recent swing high/low (pivot length configurable) define the range; OTE (62–79%) boxes are drawn contextually for up/down ranges.
Displacement: A candle’s body/ATR must exceed kTune and break short-term structure (displacement up/down).
FVG: 3-bar imbalance (bull: low > high ; bear: high < low ). Latest gaps are tracked and extended.
Order Blocks: Last opposite candle prior to a qualifying displacement that breaks recent highs/lows; zones are drawn and extended.
Entry & Alerts:
Long: Bullish bias + price inside buy-OTE + mitigation of a bullish FVG or OB + micro BOS up → “PDA Long (Final)”.
Short: Bearish bias + price inside sell-OTE + mitigation of a bearish FVG or OB + micro BOS down → “PDA Short (Final)”.
Early Alerts: Trigger as soon as price enters OTE in the direction of the active bias.
Inputs & controls (key ones)
Bias (HTF): timeframe minutes, EMA length.
Structure: ATR length, Impulse Threshold (Body/ATR), swing pivot length, OB look-back.
OTE/FVG/OB/LP toggles: show/hide components.
Auto-Tune: per-symbol factors for Gold/BTC + manual tweak.
Display/Performance: View Mode, keep-N latest FVG/OB, limit drawings to last N bars.
Recommended usage (scalping)
Timeframes: Execute on M1–M5 with HTF bias from 120–240m.
Defaults (starting point): ATR=14, Impulse Threshold≈1.6; Gold factor≈1.05, BTC factor≈0.90; Keep FVG/OB=2; last 200–300 bars; View Mode=Clean.
Workflow: Wait for OTE in bias direction → see mitigation (FVG/OB) → confirm with micro BOS → manage risk to nearest liquidity (prev-day H/L or recent swing).
Alerts available
“PDA Early Long/Short”
“PDA Long (Final)” / “PDA Short (Final)”
Attach alerts on “Any alert() function call” or the listed conditions.
Chart & screenshots
Please include symbol and timeframe on screenshots. The on-chart HUD shows the script name and state to help reviewers understand context.
Limitations / notes
This is a discretionary framework. Signals can cluster during news or extreme volatility; use your own risk management. No guarantee of profitability.
Changelog (brief)
v1.2 QuickScalp: added Quick Clean preset, safer array handling, symbol-aware impulse tuning, display modes.
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ملخص عربي:
المؤشر يطبق تسلسل PDA عملي للذهب والبتكوين: تحيز من فريم أعلى، مناطق OTE، فجوات FVG، بلوكات أوامر OB، وتأكيد micro-BOS، مع تنبيهات مبكرة ونهائية. تمت إضافة وضع “Quick Clean” لتقليل العناصر على الشارت وحساسية إزاحة تتكيّف مع الأصل. للاستخدام كسكالب: نفّذ على M1–M5 مع تحيز 120–240 دقيقة، وابدأ من الإعدادات المقترحة بالأعلى. هذا إطار سلوكي وليس توصية مالية.
Cerca negli script per "gaps"
Forecast PriceTime Oracle [CHE] Forecast PriceTime Oracle — Prioritizes quality over quantity by using Power Pivots via RSI %B metric to forecast future pivot highs/lows in price and time
Summary
This indicator identifies potential pivot highs and lows based on out-of-bounds conditions in a modified RSI %B metric, then projects future occurrences by estimating time intervals and price changes from historical medians. It provides visual forecasts via diagonal and horizontal lines, tracks achievement with color changes and symbols, and displays a dashboard for statistical overview including hit rates. Signals are robust due to median-based aggregation, which reduces outlier influence, and optional tolerance settings for near-misses, making it suitable for anticipating reversals in ranging or trending markets.
Motivation: Why this design?
Standard pivot detection often lags or generates false signals in volatile conditions, missing the timing of true extrema. This design leverages out-of-bounds excursions in RSI %B to capture "Power Pivots" early—focusing on quality over quantity by prioritizing significant extrema rather than every minor swing—then uses historical deltas in time and price to forecast the next ones, addressing the need for proactive rather than reactive analysis. It assumes that pivot spacing follows statistical patterns, allowing users to prepare entries or exits ahead of confirmation.
What’s different vs. standard approaches?
- Reference baseline: Diverges from traditional ta.pivothigh/low, which require fixed left/right lengths and confirm only after bars close, often too late for dynamic markets.
- Architecture differences:
- Detects extrema during OOB runs rather than post-bar symmetry.
- Aggregates deltas via medians (or alternatives) over a user-defined history, capping arrays to manage resources.
- Applies tolerance thresholds for hit detection, with options for percentage, absolute, or volatility-adjusted (ATR) flexibility.
- Freezes achieved forecasts with visual states to avoid clutter.
- Practical effect: Charts show proactive dashed projections instead of retrospective dots; the dashboard reveals evolving hit rates, helping users gauge reliability over time without manual calculation.
How it works (technical)
The indicator first computes a smoothed RSI over a specified length, then applies Bollinger Bands to derive %B, flagging out-of-bounds below zero or above one hundred as potential run starts. During these runs, it tracks the extreme high or low price and bar index. Upon exit from the OOB state, it confirms the Power Pivot at that extreme and records the time delta (bars since prior) and price change percentage to rolling arrays.
For forecasts, it calculates the median (or selected statistic) of recent deltas, subtracts the confirmation delay (bars from apex to exit), and projects ahead by that adjusted amount. Price targets use the median change applied to the origin pivot value. Lines are drawn from the apex to the target bar and price, with a short horizontal at the endpoint. Arrays store up to five active forecasts, pruning oldest on overflow.
Tolerance adjusts hit checks: for highs, if the high reaches or exceeds the target (adjusted by tolerance); for lows, if the low drops to or below. Once hit, the forecast freezes, changing colors and symbols, and extends the horizontal to the hit bar. Persistent variables maintain last pivot states across bars; arrays initialize empty and grow until capped at history length.
Parameter Guide
Source: Specifies the data input for the RSI computation, influencing how price action is captured. Default is close. For conservative signals in noisy environments, switch to high; using low boosts responsiveness but may increase false positives.
RSI Length: Sets the smoothing period for the RSI calculation, with longer values helping to filter out whipsaws. Default is 32. Opt for shorter lengths like 14 to 21 on faster timeframes for quicker reactions, or extend to 50 or more in strong trends to enhance stability at the cost of some lag.
BB Length: Defines the period for the Bollinger Bands applied to %B, directly affecting how often out-of-bounds conditions are triggered. Default is 20. Align it with the RSI length: shorter periods detect more potential runs but risk added noise, while longer ones provide better filtering yet might overlook emerging extrema.
BB StdDev: Controls the multiplier for the standard deviation in the bands, where wider settings reduce false out-of-bounds alerts. Default is 2.0. Narrow it to 1.5 for highly volatile assets to catch more signals, or broaden to 2.5 or higher to emphasize only major movements.
Show Price Forecast: Enables or disables the display of diagonal and target lines along with their updates. Default is true. Turn it off for simpler chart views, or keep it on to aid in trade planning.
History Length: Determines the number of recent pivot samples used for median-based statistics, where more history leads to smoother but potentially less current estimates. Default is 50. Start with a minimum of 5 to build data; limit to 100 to 200 to prevent outdated regimes from skewing results.
Max Lookahead: Limits the number of bars projected forward to avoid overly extended lines. Default is 500. Reduce to 100 to 200 for intraday focus, or increase for longer swing horizons.
Stat Method: Selects the aggregation technique for time and price deltas: Median for robustness against outliers, Trimmed Mean (20%) for a balanced trim of extremes, or 75th Percentile for a conservative upward tilt. Default is Median. Use Median for even distributions; switch to Percentile when emphasizing potential upside in trending conditions.
Tolerance Type: Chooses the approach for flexible hit detection: None for exact matches, Percentage for relative adjustments, Absolute for fixed point offsets, or ATR for scaling with volatility. Default is None. Begin with Percentage at 0.5 percent for currency pairs, or ATR for adapting to cryptocurrency swings.
Tolerance %: Provides the relative buffer when using Percentage mode, forgiving small deviations. Default is 0.5. Set between 0.2 and 1.0 percent; higher values accommodate gaps but can overstate hit counts.
Tolerance Points: Establishes a fixed offset in price units for Absolute mode. Default is 0.0010. Tailor to the asset, such as 0.0001 for forex pairs, and validate against past wick behavior.
ATR Length: Specifies the period for the Average True Range in dynamic tolerance calculations. Default is 14. This is the standard setting; shorten to 10 to reflect more recent volatility.
ATR Multiplier: Adjusts the ATR scale for tolerance width in ATR mode. Default is 0.5. Range from 0.3 for tighter precision to 0.8 for greater leniency.
Dashboard Location: Positions the summary table on the chart. Default is Bottom Right. Consider Top Left for better visibility on mobile devices.
Dashboard Size: Controls the text scaling for dashboard readability. Default is Normal. Choose Tiny for dense overlays or Large for detailed review sessions.
Text/Frame Color: Sets the color scheme for dashboard text and borders. Default is gray. Align with your chart theme, opting for lighter shades on dark backgrounds.
Reading & Interpretation
Forecast lines appear as dashed diagonals from confirmed pivots to projected targets, with solid horizontals at endpoints marking price levels. Open targets show a target symbol (🎯); achieved ones switch to a trophy symbol (🏆) in gray, with lines fading to gray. The dashboard summarizes median time/price deltas, sample counts, and hit rates—rising rates indicate improving forecast alignment. Colors differentiate highs (red) from lows (lime); frozen states signal validated projections.
Practical Workflows & Combinations
- Trend following: Enter long on low forecast hits during uptrends (higher highs/lower lows structure); filter with EMA crossovers to ignore counter-trend signals.
- Reversal setups: Short above high projections in overextended rallies; use volume spikes as confirmation to reduce false breaks.
- Exits/Stops: Trail stops to prior pivot lows; conservative on low hit rates (below 50%), aggressive above 70% with tight tolerance.
- Multi-TF: Apply on 1H for entries, 4H for time projections; combine with Ichimoku clouds for confluence on targets.
- Risk management: Position size inversely to delta uncertainty (wider history = smaller bets); avoid low-liquidity sessions.
Behavior, Constraints & Performance
Confirmation occurs on OOB exit, so live-bar pivots may adjust until close, but projections update only on events to minimize repaint. No security or HTF calls, so no external lookahead issues. Arrays cap at history length with shifts; forecasts limited to five active, pruning FIFO. Loops iterate over small fixed sizes (e.g., up to 50 for stats), efficient on most hardware. Max lines/labels at 500 prevent overflow.
Known limits: Sensitive to OOB parameter tuning—too tight misses runs; assumes stationary pivot stats, which may shift in regime changes like low vol. Gaps or holidays distort time deltas.
Sensible Defaults & Quick Tuning
Defaults suit forex/crypto on 1H–4H: RSI 32/BB 20 for balanced detection, Median stats over 50 samples, None tolerance for exactness.
- Too many false runs: Increase BB StdDev to 2.5 or RSI Length to 50 for filtering.
- Lagging forecasts: Shorten History Length to 20; switch to 75th Percentile for forward bias.
- Missed near-hits: Enable Percentage tolerance at 0.3% to capture wicks without overcounting.
- Cluttered charts: Reduce Max Lookahead to 200; disable dashboard on lower TFs.
What this indicator is—and isn’t
This is a forecasting visualization layer for pivot-based analysis, highlighting statistical projections from historical patterns. It is not a standalone system—pair with price action, volume, and risk rules. Not predictive of all turns; focuses on OOB-derived extrema, ignoring volume or news impacts.
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
T3 ATR [DCAUT]█ T3 ATR
📊 ORIGINALITY & INNOVATION
The T3 ATR indicator represents an important enhancement to the traditional Average True Range (ATR) indicator by incorporating the T3 (Tilson Triple Exponential Moving Average) smoothing algorithm. While standard ATR uses fixed RMA (Running Moving Average) smoothing, T3 ATR introduces a configurable volume factor parameter that allows traders to adjust the smoothing characteristics from highly responsive to heavily smoothed output.
This innovation addresses a fundamental limitation of traditional ATR: the inability to adapt smoothing behavior without changing the calculation period. With T3 ATR, traders can maintain a consistent ATR period while adjusting the responsiveness through the volume factor, making the indicator adaptable to different trading styles, market conditions, and timeframes through a single unified implementation.
The T3 algorithm's triple exponential smoothing with volume factor control provides improved signal quality by reducing noise while maintaining better responsiveness compared to traditional smoothing methods. This makes T3 ATR particularly valuable for traders who need to adapt their volatility measurement approach to varying market conditions without switching between multiple indicator configurations.
📐 MATHEMATICAL FOUNDATION
The T3 ATR calculation process involves two distinct stages:
Stage 1: True Range Calculation
The True Range (TR) is calculated using the standard formula:
TR = max(high - low, |high - close |, |low - close |)
This captures the greatest of the current bar's range, the gap from the previous close to the current high, or the gap from the previous close to the current low, providing a comprehensive measure of price movement that accounts for gaps and limit moves.
Stage 2: T3 Smoothing Application
The True Range values are then smoothed using the T3 algorithm, which applies six exponential moving averages in succession:
First Layer: e1 = EMA(TR, period), e2 = EMA(e1, period)
Second Layer: e3 = EMA(e2, period), e4 = EMA(e3, period)
Third Layer: e5 = EMA(e4, period), e6 = EMA(e5, period)
Final Calculation: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
The coefficients (c1, c2, c3, c4) are derived from the volume factor (VF) parameter:
a = VF / 2
c1 = -a³
c2 = 3a² + 3a³
c3 = -6a² - 3a - 3a³
c4 = 1 + 3a + a³ + 3a²
The volume factor parameter (0.0 to 1.0) controls the weighting of these coefficients, directly affecting the balance between responsiveness and smoothness:
Lower VF values (approaching 0.0): Coefficients favor recent data, resulting in faster response to volatility changes with minimal lag but potentially more noise
Higher VF values (approaching 1.0): Coefficients distribute weight more evenly across the smoothing layers, producing smoother output with reduced noise but slightly increased lag
📊 COMPREHENSIVE SIGNAL ANALYSIS
Volatility Level Interpretation:
High Absolute Values: Indicate strong price movements and elevated market activity, suggesting larger position risks and wider stop-loss requirements, often associated with trending markets or significant news events
Low Absolute Values: Indicate subdued price movements and quiet market conditions, suggesting smaller position risks and tighter stop-loss opportunities, often associated with consolidation phases or low-volume periods
Rapid Increases: Sharp spikes in T3 ATR often signal the beginning of significant price moves or market regime changes, providing early warning of increased trading risk
Sustained High Levels: Extended periods of elevated T3 ATR indicate sustained trending conditions with persistent volatility, suitable for trend-following strategies
Sustained Low Levels: Extended periods of low T3 ATR indicate range-bound conditions with suppressed volatility, suitable for mean-reversion strategies
Volume Factor Impact on Signals:
Low VF Settings (0.0-0.3): Produce responsive signals that quickly capture volatility changes, suitable for short-term trading but may generate more frequent color changes during minor fluctuations
Medium VF Settings (0.4-0.7): Provide balanced signal quality with moderate responsiveness, filtering out minor noise while capturing significant volatility changes, suitable for swing trading
High VF Settings (0.8-1.0): Generate smooth, stable signals that filter out most noise and focus on major volatility trends, suitable for position trading and long-term analysis
🎯 STRATEGIC APPLICATIONS
Position Sizing Strategy:
Determine your risk per trade (e.g., 1% of account capital - adjust based on your risk tolerance and experience)
Decide your stop-loss distance multiplier (e.g., 2.0x T3 ATR - this varies by market and strategy, test different values)
Calculate stop-loss distance: Stop Distance = Multiplier × Current T3 ATR
Calculate position size: Position Size = (Account × Risk %) / Stop Distance
Example: $10,000 account, 1% risk, T3 ATR = 50 points, 2x multiplier → Position Size = ($10,000 × 0.01) / (2 × 50) = $100 / 100 points = 1 unit per point
Important: The ATR multiplier (1.5x - 3.0x) should be determined through backtesting for your specific instrument and strategy - using inappropriate multipliers may result in stops that are too tight (frequent stop-outs) or too wide (excessive losses)
Adjust the volume factor to match your trading style: lower VF for responsive stop distances in short-term trading, higher VF for stable stop distances in position trading
Dynamic Stop-Loss Placement:
Determine your risk tolerance multiplier (typically 1.5x to 3.0x T3 ATR)
For long positions: Set stop-loss at entry price minus (multiplier × current T3 ATR value)
For short positions: Set stop-loss at entry price plus (multiplier × current T3 ATR value)
Trail stop-losses by recalculating based on current T3 ATR as the trade progresses
Adjust the volume factor based on desired stop-loss stability: higher VF for less frequent adjustments, lower VF for more adaptive stops
Market Regime Identification:
Calculate a reference volatility level using a longer-period moving average of T3 ATR (e.g., 50-period SMA)
High Volatility Regime: Current T3 ATR significantly above reference (e.g., 120%+) - favor trend-following strategies, breakout trades, and wider targets
Normal Volatility Regime: Current T3 ATR near reference (e.g., 80-120%) - employ standard trading strategies appropriate for prevailing market structure
Low Volatility Regime: Current T3 ATR significantly below reference (e.g., <80%) - favor mean-reversion strategies, range trading, and prepare for potential volatility expansion
Monitor T3 ATR trend direction and compare current values to recent history to identify regime transitions early
Risk Management Implementation:
Establish your maximum portfolio heat (total risk across all positions, typically 2-6% of capital)
For each position: Calculate position size using the formula Position Size = (Account × Individual Risk %) / (ATR Multiplier × Current T3 ATR)
When T3 ATR increases: Position sizes automatically decrease (same risk %, larger stop distance = smaller position)
When T3 ATR decreases: Position sizes automatically increase (same risk %, smaller stop distance = larger position)
This approach maintains constant dollar risk per trade regardless of market volatility changes
Use consistent volume factor settings across all positions to ensure uniform risk measurement
📋 DETAILED PARAMETER CONFIGURATION
ATR Length Parameter:
Default Setting: 14 periods
This is the standard ATR calculation period established by Welles Wilder, providing balanced volatility measurement that captures both short-term fluctuations and medium-term trends across most markets and timeframes
Selection Principles:
Shorter periods increase sensitivity to recent volatility changes and respond faster to market shifts, but may produce less stable readings
Longer periods emphasize sustained volatility trends and filter out short-term noise, but respond more slowly to genuine regime changes
The optimal period depends on your holding time, trading frequency, and the typical volatility cycle of your instrument
Consider the timeframe you trade: Intraday traders typically use shorter periods, swing traders use intermediate periods, position traders use longer periods
Practical Approach:
Start with the default 14 periods and observe how well it captures volatility patterns relevant to your trading decisions
If ATR seems too reactive to minor price movements: Increase the period until volatility readings better reflect meaningful market changes
If ATR lags behind obvious volatility shifts that affect your trades: Decrease the period for faster response
Match the period roughly to your typical holding time - if you hold positions for N bars, consider ATR periods in a similar range
Test different periods using historical data for your specific instrument and strategy before committing to live trading
T3 Volume Factor Parameter:
Default Setting: 0.7
This setting provides a reasonable balance between responsiveness and smoothness for most market conditions and trading styles
Understanding the Volume Factor:
Lower values (closer to 0.0) reduce smoothing, allowing T3 ATR to respond more quickly to volatility changes but with less noise filtering
Higher values (closer to 1.0) increase smoothing, producing more stable readings that focus on sustained volatility trends but respond more slowly
The trade-off is between immediacy and stability - there is no universally optimal setting
Selection Principles:
Match to your decision speed: If you need to react quickly to volatility changes for entries/exits, use lower VF; if you're making longer-term risk assessments, use higher VF
Match to market character: Noisier, choppier markets may benefit from higher VF for clearer signals; cleaner trending markets may work well with lower VF for faster response
Match to your preference: Some traders prefer responsive indicators even with occasional false signals, others prefer stable indicators even with some delay
Practical Adjustment Guidelines:
Start with default 0.7 and observe how T3 ATR behavior aligns with your trading needs over multiple sessions
If readings seem too unstable or noisy for your decisions: Try increasing VF toward 0.9-1.0 for heavier smoothing
If the indicator lags too much behind volatility changes you care about: Try decreasing VF toward 0.3-0.5 for faster response
Make meaningful adjustments (0.2-0.3 changes) rather than small increments - subtle differences are often imperceptible in practice
Test adjustments in simulation or paper trading before applying to live positions
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
The T3 smoothing algorithm provides improved responsiveness compared to traditional RMA smoothing used in standard ATR. The triple exponential design with volume factor control allows the indicator to respond more quickly to genuine volatility changes while maintaining the ability to filter noise through appropriate VF settings. This results in earlier detection of volatility regime changes compared to standard ATR, particularly valuable for risk management and position sizing adjustments.
Signal Stability:
Unlike simple smoothing methods that may produce erratic signals during transitional periods, T3 ATR's multi-layer exponential smoothing provides more stable signal progression. The volume factor parameter allows traders to tune signal stability to their preference, with higher VF settings producing remarkably smooth volatility profiles that help avoid overreaction to temporary market fluctuations.
Comparison with Standard ATR:
Adaptability: T3 ATR allows adjustment of smoothing characteristics through the volume factor without changing the ATR period, whereas standard ATR requires changing the period length to alter responsiveness, potentially affecting the fundamental volatility measurement
Lag Reduction: At lower volume factor settings, T3 ATR responds more quickly to volatility changes than standard ATR with equivalent periods, providing earlier signals for risk management adjustments
Noise Filtering: At higher volume factor settings, T3 ATR provides superior noise filtering compared to standard ATR, producing cleaner signals for long-term analysis without sacrificing volatility measurement accuracy
Flexibility: A single T3 ATR configuration can serve multiple trading styles by adjusting only the volume factor, while standard ATR typically requires multiple instances with different periods for different trading applications
Suitable Use Cases:
T3 ATR is well-suited for the following scenarios:
Dynamic Risk Management: When position sizing and stop-loss placement need to adapt quickly to changing volatility conditions
Multi-Style Trading: When a single volatility indicator must serve different trading approaches (day trading, swing trading, position trading)
Volatile Markets: When standard ATR produces too many false volatility signals during choppy conditions
Systematic Trading: When algorithmic systems require a single, configurable volatility input that can be optimized for different instruments
Market Regime Analysis: When clear identification of volatility expansion and contraction phases is critical for strategy selection
Known Limitations:
Like all technical indicators, T3 ATR has limitations that users should understand:
Historical Nature: T3 ATR is calculated from historical price data and cannot predict future volatility with certainty
Smoothing Trade-offs: The volume factor setting involves a trade-off between responsiveness and smoothness - no single setting is optimal for all market conditions
Extreme Events: During unprecedented market events or gaps, T3 ATR may not immediately reflect the full scope of volatility until sufficient data is processed
Relative Measurement: T3 ATR values are most meaningful in relative context (compared to recent history) rather than as absolute thresholds
Market Context Required: T3 ATR measures volatility magnitude but does not indicate price direction or trend quality - it should be used in conjunction with directional analysis
Performance Expectations:
T3 ATR is designed to help traders measure and adapt to changing market volatility conditions. When properly configured and applied:
It can help reduce position risk during volatile periods through appropriate position sizing
It can help identify optimal times for more aggressive position sizing during stable periods
It can improve stop-loss placement by adapting to current market conditions
It can assist in strategy selection by identifying volatility regimes
However, volatility measurement alone does not guarantee profitable trading. T3 ATR should be integrated into a comprehensive trading approach that includes directional analysis, proper risk management, and sound trading psychology.
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. T3 ATR provides adaptive volatility measurement but has limitations and should not be used as the sole basis for trading decisions. The indicator measures historical volatility patterns, and past volatility characteristics do not guarantee future volatility behavior. Market conditions can change rapidly, and extreme events may produce volatility readings that fall outside historical norms.
Traders should combine T3 ATR with directional analysis tools, support/resistance analysis, and other technical indicators to form a complete trading strategy. Proper backtesting and forward testing with appropriate risk management is essential before applying T3 ATR-based strategies to live trading. The volume factor parameter should be optimized for specific instruments and trading styles through careful testing rather than assuming default settings are optimal for all applications.
RSI Bollinger Bands [DCAUT]█ RSI Bollinger Bands
📊 ORIGINALITY & INNOVATION
The RSI Bollinger Bands indicator represents a meaningful advancement in momentum analysis by combining two proven technical tools: the Relative Strength Index (RSI) and Bollinger Bands. This combination addresses a significant limitation in traditional RSI analysis - the use of fixed overbought/oversold thresholds (typically 70/30) that fail to adapt to changing market volatility conditions.
Core Innovation:
Rather than relying on static threshold levels, this indicator applies Bollinger Bands statistical analysis directly to RSI values, creating dynamic zones that automatically adjust based on recent momentum volatility. This approach helps reduce false signals during low volatility periods while remaining sensitive to genuine extremes during high volatility conditions.
Key Enhancements Over Traditional RSI:
Dynamic Thresholds: Overbought/oversold zones adapt to market conditions automatically, eliminating the need for manual threshold adjustments across different instruments and timeframes
Volatility Context: Band width provides immediate visual feedback about momentum volatility, helping traders distinguish between stable trends and erratic movements
Reduced False Signals: During ranging markets, narrower bands filter out minor RSI fluctuations that would trigger traditional fixed-threshold signals
Breakout Preparation: Band squeeze patterns (similar to price-based BB) signal potential momentum regime changes before they occur
Self-Referencing Analysis: By measuring RSI against its own statistical behavior rather than arbitrary levels, the indicator provides more relevant context
📐 MATHEMATICAL FOUNDATION
Two-Stage Calculation Process:
Stage 1: RSI Calculation
RSI = 100 - (100 / (1 + RS))
where RS = Average Gain / Average Loss over specified period
The RSI normalizes price momentum into a bounded 0-100 scale, making it ideal for statistical band analysis.
Stage 2: Bollinger Bands on RSI
Basis = MA(RSI, BB Length)
Upper Band = Basis + (StdDev(RSI, BB Length) × Multiplier)
Lower Band = Basis - (StdDev(RSI, BB Length) × Multiplier)
Band Width = Upper Band - Lower Band
The Bollinger Bands measure RSI's standard deviation from its own moving average, creating statistically-derived dynamic zones.
Statistical Interpretation:
Under normal distribution assumptions with default 2.0 multiplier, approximately 95% of RSI values should fall within the bands
Band touches represent statistically significant momentum extremes relative to recent behavior
Band width expansion indicates increasing momentum volatility (strengthening trend or increasing uncertainty)
Band width contraction signals momentum consolidation and potential regime change preparation
📊 COMPREHENSIVE SIGNAL ANALYSIS
Visual Color Signals:
This indicator features dynamic color fills that highlight extreme momentum conditions:
Green Fill (Above Upper Band):
Appears when RSI breaks above the upper band, indicating exceptionally strong bullish momentum
Represents dynamic overbought zone - not necessarily a reversal signal but a warning of extreme conditions
In strong uptrends, green fills can persist as RSI "rides the band" - this indicates sustained momentum strength
Exit of green zone (RSI falling back below upper band) often signals initial momentum weakening
Red Fill (Below Lower Band):
Appears when RSI breaks below the lower band, indicating exceptionally weak bearish momentum
Represents dynamic oversold zone - potential reversal or continuation signal depending on trend context
In strong downtrends, red fills can persist as RSI "rides the band" - this indicates sustained selling pressure
Exit of red zone (RSI rising back above lower band) often signals initial momentum recovery
Position-Based Signals:
Upper Band Interactions:
RSI Touching Upper Band: Dynamic overbought condition - momentum is extremely strong relative to recent volatility, potential exhaustion or continuation depending on trend context
RSI Riding Upper Band: Sustained strong momentum, often seen in powerful trends, not necessarily an immediate reversal signal but warrants monitoring for exhaustion
RSI Crossing Below Upper Band: Initial momentum weakening signal, particularly significant if accompanied by price divergence
Lower Band Interactions:
RSI Touching Lower Band: Dynamic oversold condition - momentum is extremely weak relative to recent volatility, potential reversal or continuation of downtrend
RSI Riding Lower Band: Sustained weak momentum, common in strong downtrends, monitor for potential exhaustion
RSI Crossing Above Lower Band: Initial momentum strengthening signal, early indication of potential reversal or consolidation
Basis Line Signals:
RSI Above Basis: Bullish momentum regime - upward pressure dominant
RSI Below Basis: Bearish momentum regime - downward pressure dominant
Basis Crossovers: Momentum regime shifts, more significant when accompanied by band width changes
RSI Oscillating Around Basis: Balanced momentum, often indicates ranging market conditions
Volatility-Based Signals:
Band Width Patterns:
Narrow Bands (Squeeze): Momentum volatility compression, often precedes significant directional moves, similar to price coiling patterns
Expanding Bands: Increasing momentum volatility, indicates trend acceleration or growing uncertainty
Narrowest Band in 100 Bars: Extreme compression alert, high probability of upcoming volatility expansion
Advanced Pattern Recognition:
Divergence Analysis:
Bullish Divergence: Price makes lower lows while RSI touches or stays above previous lower band touch, suggests downward momentum weakening
Bearish Divergence: Price makes higher highs while RSI touches or stays below previous upper band touch, suggests upward momentum weakening
Hidden Bullish: Price makes higher lows while RSI makes lower lows at the lower band, indicates strong underlying bullish momentum
Hidden Bearish: Price makes lower highs while RSI makes higher highs at the upper band, indicates strong underlying bearish momentum
Band Walk Patterns:
Upper Band Walk: RSI consistently touching or staying near upper band indicates exceptionally strong trend, wait for clear break below basis before considering reversal
Lower Band Walk: RSI consistently at lower band signals very weak momentum, requires break above basis for reversal confirmation
🎯 STRATEGIC APPLICATIONS
Strategy 1: Mean Reversion Trading
Setup Conditions:
Market Type: Ranging or choppy markets with no clear directional trend
Timeframe: Works best on lower timeframes (5m-1H) or during consolidation phases
Band Characteristic: Normal to narrow band width
Entry Rules:
Long Entry: RSI touches or crosses below lower band, wait for RSI to start rising back toward basis before entry
Short Entry: RSI touches or crosses above upper band, wait for RSI to start falling back toward basis before entry
Confirmation: Use price action confirmation (candlestick reversal patterns) at band touches
Exit Rules:
Target: RSI returns to basis line or opposite band
Stop Loss: Fixed percentage or below recent swing low/high
Time Stop: Exit if position not profitable within expected timeframe
Strategy 2: Trend Continuation Trading
Setup Conditions:
Market Type: Clear trending market with higher highs/lower lows
Timeframe: Medium to higher timeframes (1H-Daily)
Band Characteristic: Expanding or wide bands indicating strong momentum
Entry Rules:
Long Entry in Uptrend: Wait for RSI to pull back to basis line or slightly below, enter when RSI starts rising again
Short Entry in Downtrend: Wait for RSI to rally to basis line or slightly above, enter when RSI starts falling again
Avoid Counter-Trend: Do not fade RSI at bands during strong trends (band walk patterns)
Exit Rules:
Trailing Stop: Move stop to break-even when RSI reaches opposite band
Trend Break: Exit when RSI crosses basis against trend direction with conviction
Band Squeeze: Reduce position size when bands start narrowing significantly
Strategy 3: Breakout Preparation
Setup Conditions:
Market Type: Consolidating market after significant move or at key technical levels
Timeframe: Any timeframe, but longer timeframes provide more reliable breakouts
Band Characteristic: Narrowest band width in recent 100 bars (squeeze alert)
Preparation Phase:
Identify band squeeze condition (bands at multi-period narrowest point)
Monitor price action for consolidation patterns (triangles, rectangles, flags)
Prepare bracket orders for both directions
Wait for band expansion to begin
Entry Execution:
Breakout Confirmation: Enter in direction of RSI band breakout (RSI breaks above upper band or below lower band)
Price Confirmation: Ensure price also breaks corresponding technical level
Volume Confirmation: Look for volume expansion supporting the breakout
Risk Management:
Stop Loss: Place beyond consolidation pattern opposite extreme
Position Sizing: Use smaller size due to false breakout risk
Quick Exit: Exit immediately if RSI returns inside bands within 1-3 bars
Strategy 4: Multi-Timeframe Analysis
Timeframe Selection:
Higher Timeframe: Daily or 4H for trend context
Trading Timeframe: 1H or 15m for entry signals
Confirmation Timeframe: 5m or 1m for precise entry timing
Analysis Process:
Trend Identification: Check higher timeframe RSI position relative to bands, trade only in direction of higher timeframe momentum
Setup Formation: Wait for trading timeframe RSI to show pullback to basis in trending direction
Entry Timing: Use confirmation timeframe RSI band touch or crossover for precise entry
Alignment Confirmation: All timeframes should show RSI moving in same direction for highest probability setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Close (Default): Standard price point, balances responsiveness and reliability
HL2: Reduces noise from intrabar volatility, provides smoother RSI values
HLC3 or OHLC4: Further smoothing for very choppy markets, slower to respond but more stable
Volume-Weighted: Consider using VWAP or volume-weighted prices for additional liquidity context
RSI Length Parameter:
Shorter Periods (5-10): More responsive but generates more signals, suitable for scalping or very active trading, higher noise level
Standard (14): Default and most widely used setting, proven balance between responsiveness and reliability, recommended starting point
Longer Periods (21-30): Smoother momentum measurement, fewer but potentially more reliable signals, better for swing trading or position trading
Optimization Note: Test across different market regimes, optimal length often varies by instrument volatility characteristics
RSI MA Type Parameter:
RMA (Default): Wilder's original smoothing method, provides traditional RSI behavior with balanced lag, most widely recognized and tested, recommended for standard technical analysis
EMA: Exponential smoothing gives more weight to recent values, faster response to momentum changes, suitable for active trading and trending markets, reduces lag compared to RMA
SMA: Simple average treats all periods equally, smoothest output with highest lag, best for filtering noise in choppy markets, useful for long-term position analysis
WMA: Weighted average emphasizes recent data less aggressively than EMA, middle ground between SMA and EMA characteristics, balanced responsiveness for swing trading
Advanced Options: Full access to 25+ moving average types including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive behavior), T3 (smoothness), Kalman Filter (optimal estimation)
Selection Guide: RMA for traditional analysis and backtesting consistency, EMA for faster signals in trending markets, SMA for stability in ranging markets, adaptive types (KAMA/FRAMA) for varying volatility regimes
BB Length Parameter:
Short Length (10-15): Tighter bands that react quickly to RSI changes, more frequent band touches, suitable for active trading styles
Standard (20): Balanced approach providing meaningful statistical context without excessive lag
Long Length (30-50): Smoother bands that filter minor RSI fluctuations, captures only significant momentum extremes, fewer but higher quality signals
Relationship to RSI Length: Consider BB Length greater than RSI Length for cleaner signals
BB MA Type Parameter:
SMA (Default): Standard Bollinger Bands calculation using simple moving average for basis line, treats all periods equally, widely recognized and tested approach
EMA: Exponential smoothing for basis line gives more weight to recent RSI values, creates more responsive bands that adapt faster to momentum changes, suitable for trending markets
RMA: Wilder's smoothing provides consistent behavior aligned with traditional RSI when using RMA for both RSI and BB calculations
WMA: Weighted average for basis line balances recent emphasis with historical context, middle ground between SMA and EMA responsiveness
Advanced Options: Full access to 25+ moving average types for basis calculation, including HMA (reduced lag), DEMA/TEMA (enhanced responsiveness), KAMA/FRAMA (adaptive to volatility changes)
Selection Guide: SMA for standard Bollinger Bands behavior and backtesting consistency, EMA for faster band adaptation in dynamic markets, matching RSI MA type creates unified smoothing behavior
BB Multiplier Parameter:
Conservative (1.5-1.8): Tighter bands resulting in more frequent touches, useful in low volatility environments, higher signal frequency but potentially more false signals
Standard (2.0): Default setting representing approximately 95% confidence interval under normal distribution, widely accepted statistical threshold
Aggressive (2.5-3.0): Wider bands capturing only extreme momentum conditions, fewer but potentially more significant signals, reduces false signals in high volatility
Adaptive Approach: Consider adjusting multiplier based on instrument characteristics, lower multiplier for stable instruments, higher for volatile instruments
Parameter Optimization Workflow:
Start with default parameters (RSI:14, BB:20, Mult:2.0)
Test across representative sample period including different market regimes
Adjust RSI length based on desired responsiveness vs stability tradeoff
Tune BB length to match your typical holding period
Modify multiplier to achieve desired signal frequency
Validate on out-of-sample data to avoid overfitting
Document optimal parameters for different instruments and timeframes
Reference Levels Display:
Enabled (Default): Shows traditional 30/50/70 levels for comparison with dynamic bands, helps visualize the adaptive advantage
Disabled: Cleaner chart focusing purely on dynamic zones, reduces visual clutter for experienced users
Educational Value: Keeping reference levels visible helps understand how dynamic bands differ from fixed thresholds across varying market conditions
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Comparison with Traditional RSI:
Fixed Threshold RSI Limitations:
In ranging low-volatility markets: RSI rarely reaches 70/30, missing tradable extremes
In trending high-volatility markets: RSI frequently breaks through 70/30, generating excessive false reversal signals
Across different instruments: Same thresholds applied to volatile crypto and stable forex pairs produce inconsistent results
Threshold Adjustment Problem: Manually changing thresholds for different conditions is subjective and lagging
RSI Bollinger Bands Advantages:
Automatic Adaptation: Bands adjust to current volatility regime without manual intervention
Consistent Logic: Same statistical approach works across different instruments and timeframes
Reduced False Signals: Band width filtering helps distinguish meaningful extremes from noise
Additional Information: Band width provides volatility context missing in standard RSI
Objective Extremes: Statistical basis (standard deviations) provides objective extreme definition
Comparison with Price-Based Bollinger Bands:
Price BB Characteristics:
Measures absolute price volatility
Affected by large price gaps and outliers
Band position relative to price not normalized
Difficult to compare across different price scales
RSI BB Advantages:
Normalized Scale: RSI's 0-100 bounds make band interpretation consistent across all instruments
Momentum Focus: Directly measures momentum extremes rather than price extremes
Reduced Gap Impact: RSI calculation smooths price gaps impact on band calculations
Comparable Analysis: Same RSI BB appearance across stocks, forex, crypto enables consistent strategy application
Performance Characteristics:
Signal Quality:
Higher Signal-to-Noise Ratio: Dynamic bands help filter RSI oscillations that don't represent meaningful extremes
Context-Aware Alerts: Band width provides volatility context helping traders adjust position sizing and stop placement
Reduced Whipsaws: During consolidations, narrower bands prevent premature signals from minor RSI movements
Responsiveness:
Adaptive Lag: Band calculation introduces some lag, but this lag is adaptive to current conditions rather than fixed
Faster Than Manual Adjustment: Automatic band adjustment is faster than trader's ability to manually modify thresholds
Balanced Approach: Combines RSI's inherent momentum lag with BB's statistical smoothing for stable yet responsive signals
Versatility:
Multi-Strategy Application: Supports both mean reversion (ranging markets) and trend continuation (trending markets) approaches
Universal Instrument Coverage: Works effectively across equities, forex, commodities, cryptocurrencies without parameter changes
Timeframe Agnostic: Same interpretation applies from 1-minute charts to monthly charts
Limitations and Considerations:
Known Limitations:
Dual Lag Effect: Combines RSI's momentum lag with BB's statistical lag, making it less suitable for very short-term scalping
Requires Volatility History: Needs sufficient bars for BB calculation, less effective immediately after major regime changes
Statistical Assumptions: Assumes RSI values are somewhat normally distributed, extreme trending conditions may violate this
Not a Standalone System: Like all indicators, should be combined with price action analysis and risk management
Optimal Use Cases:
Best for swing trading and position trading timeframes
Most effective in markets with alternating volatility regimes
Ideal for traders who use multiple instruments and timeframes
Suitable for systematic trading approaches requiring consistent logic
Suboptimal Conditions:
Very low timeframes (< 5 minutes) where lag becomes problematic
Instruments with extreme volatility spikes (gap-prone markets)
Markets in strong persistent trends where mean reversion rarely occurs
Periods immediately following major structural changes (new trading regime)
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand the interaction between momentum measurement and statistical volatility bands. The RSI Bollinger Bands has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
No Predictive Guarantee: Past band touches and patterns do not guarantee future price behavior
Market Regime Dependency: Indicator performance varies significantly between trending and ranging market conditions
Complementary Analysis Required: Should be used alongside price action, support/resistance levels, and fundamental analysis
Risk Management Essential: Always use proper position sizing, stop losses, and risk controls regardless of signal quality
Parameter Sensitivity: Different instruments and timeframes may require parameter optimization for optimal results
Continuous Monitoring: Band characteristics change with market conditions, requiring ongoing assessment
Recommended Supporting Analysis:
Price structure analysis (support/resistance, trend lines)
Volume confirmation for breakout signals
Multiple timeframe alignment
Market context awareness (news events, session times)
Correlation analysis with related instruments
The indicator aims to provide adaptive momentum analysis that adjusts to changing market volatility, but traders must apply sound judgment, proper risk management, and comprehensive market analysis in their decision-making process.
ICT Levels Breach Scanner (12M Timeframe)Detects and scans for breaches of key Inner Circle Trader (ICT) concepts on the yearly (12M) chart: Swing Lows (3-bar wick pivots), Rejection Blocks (3-bar body pivots), Fair Value Gaps (3-bar inefficiencies), and Volume Imbalances (bullish body gaps ≥0.15%, unmitigated).
Features:
Tracks active levels with arrays for real-time breach detection (price low below any level triggers alert).
Visuals: Blue solid lines (Swing Lows), orange dashed (Rejection Blocks), purple dotted (FVGs), green boxes (VIs)—all extending right.
Red triangle + bgcolor alert on breach bar; built-in alertcondition for notifications.
Optimized for Pine Screener: Filter stocks (e.g., US exchanges) showing symbols where price has traded below these levels on the latest 12M bar.
Usage: Apply to a 12M chart for viz, or add to Screener > Pine tab for multi-symbol scans. Customize gap % or add bearish variants via inputs. Ideal for spotting potential support in long-term trends.
ICT-inspired; test on liquid stocks like AAPL/TSLA. Not financial advice.
MACD Enhanced [DCAUT]█ MACD Enhanced
📊 ORIGINALITY & INNOVATION
The MACD Enhanced represents a significant improvement over traditional MACD implementations. While Gerald Appel's original MACD from the 1970s was limited to exponential moving averages (EMA), this enhanced version expands algorithmic options by supporting 21 different moving average calculations for both the main MACD line and signal line independently.
This improvement addresses an important limitation of traditional MACD: the inability to adapt the indicator's mathematical foundation to different market conditions. By allowing traders to select from algorithms ranging from simple moving averages (SMA) for stability to advanced adaptive filters like Kalman Filter for noise reduction, this implementation changes MACD from a fixed-algorithm tool into a flexible instrument that can be adjusted for specific market environments and trading strategies.
The enhanced histogram visualization system uses a four-color gradient that helps communicate momentum strength and direction more clearly than traditional single-color histograms.
📐 MATHEMATICAL FOUNDATION
The core calculation maintains the proven MACD formula: Fast MA(source, fastLength) - Slow MA(source, slowLength), but extends it with algorithmic flexibility. The signal line applies the selected smoothing algorithm to the MACD line over the specified signal period, while the histogram represents the difference between MACD and signal lines.
Available Algorithms:
The implementation supports a comprehensive spectrum of technical analysis algorithms:
Basic Averages: SMA (arithmetic mean), EMA (exponential weighting), RMA (Wilder's smoothing), WMA (linear weighting)
Advanced Averages: HMA (Hull's low-lag), VWMA (volume-weighted), ALMA (Arnaud Legoux adaptive)
Mathematical Filters: LSMA (least squares regression), DEMA (double exponential), TEMA (triple exponential), ZLEMA (zero-lag exponential)
Adaptive Systems: T3 (Tillson T3), FRAMA (fractal adaptive), KAMA (Kaufman adaptive), MCGINLEY_DYNAMIC (reactive to volatility)
Signal Processing: ULTIMATE_SMOOTHER (low-pass filter), LAGUERRE_FILTER (four-pole IIR), SUPER_SMOOTHER (two-pole Butterworth), KALMAN_FILTER (state-space estimation)
Specialized: TMA (triangular moving average), LAGUERRE_BINOMIAL_FILTER (binomial smoothing)
Each algorithm responds differently to price action, allowing traders to match the indicator's behavior to market characteristics: trending markets benefit from responsive algorithms like EMA or HMA, while ranging markets require stable algorithms like SMA or RMA.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Histogram Interpretation:
Positive Values: Indicate bullish momentum when MACD line exceeds signal line, suggesting upward price pressure and potential buying opportunities
Negative Values: Reflect bearish momentum when MACD line falls below signal line, indicating downward pressure and potential selling opportunities
Zero Line Crosses: MACD crossing above zero suggests transition to bullish bias, while crossing below indicates bearish bias shift
Momentum Changes: Rising histogram (regardless of positive/negative) signals accelerating momentum in the current direction, while declining histogram warns of momentum deceleration
Advanced Signal Recognition:
Divergences: Price making new highs/lows while MACD fails to confirm often precedes trend reversals
Convergence Patterns: MACD line approaching signal line suggests impending crossover and potential trade setup
Histogram Peaks: Extreme histogram values often mark momentum exhaustion points and potential reversal zones
🎯 STRATEGIC APPLICATIONS
Comprehensive Trend Confirmation Strategies:
Primary Trend Validation Protocol:
Identify primary trend direction using higher timeframe (4H or Daily) MACD position relative to zero line
Confirm trend strength by analyzing histogram progression: consistent expansion indicates strong momentum, contraction suggests weakening
Use secondary confirmation from MACD line angle: steep angles (>45°) indicate strong trends, shallow angles suggest consolidation
Validate with price structure: trending markets show consistent higher highs/higher lows (uptrend) or lower highs/lower lows (downtrend)
Entry Timing Techniques:
Pullback Entries in Uptrends: Wait for MACD histogram to decline toward zero line without crossing, then enter on histogram expansion with MACD line still above zero
Breakout Confirmations: Use MACD line crossing above zero as confirmation of upward breakouts from consolidation patterns
Continuation Signals: Look for MACD line re-acceleration (steepening angle) after brief consolidation periods as trend continuation signals
Advanced Divergence Trading Systems:
Regular Divergence Recognition:
Bullish Regular Divergence: Price creates lower lows while MACD line forms higher lows. This pattern is traditionally considered a potential upward reversal signal, but should be combined with other confirmation signals
Bearish Regular Divergence: Price makes higher highs while MACD shows lower highs. This pattern is traditionally considered a potential downward reversal signal, but trading decisions should incorporate proper risk management
Hidden Divergence Strategies:
Bullish Hidden Divergence: Price shows higher lows while MACD displays lower lows, indicating trend continuation potential. Use for adding to existing long positions during pullbacks
Bearish Hidden Divergence: Price creates lower highs while MACD forms higher highs, suggesting downtrend continuation. Optimal for adding to short positions during bear market rallies
Multi-Timeframe Coordination Framework:
Three-Timeframe Analysis Structure:
Primary Timeframe (Daily): Determine overall market bias and major trend direction. Only trade in alignment with daily MACD direction
Secondary Timeframe (4H): Identify intermediate trend changes and major entry opportunities. Use for position sizing decisions
Execution Timeframe (1H): Precise entry and exit timing. Look for MACD line crossovers that align with higher timeframe bias
Timeframe Synchronization Rules:
Daily MACD above zero + 4H MACD rising = Strong uptrend context for long positions
Daily MACD below zero + 4H MACD declining = Strong downtrend context for short positions
Conflicting signals between timeframes = Wait for alignment or use smaller position sizes
1H MACD signals only valid when aligned with both higher timeframes
Algorithm Considerations by Market Type:
Trending Markets: Responsive algorithms like EMA, HMA may be considered, but effectiveness should be tested for specific market conditions
Volatile Markets: Noise-reducing algorithms like KALMAN_FILTER, SUPER_SMOOTHER may help reduce false signals, though results vary by market
Range-Bound Markets: Stability-focused algorithms like SMA, RMA may provide smoother signals, but individual testing is required
Short Timeframes: Low-lag algorithms like ZLEMA, T3 theoretically respond faster but may also increase noise
Important Note: All algorithm choices and parameter settings should be thoroughly backtested and validated based on specific trading strategies, market conditions, and individual risk tolerance. Different market environments and trading styles may require different configuration approaches.
📋 DETAILED PARAMETER CONFIGURATION
Comprehensive Source Selection Strategy:
Price Source Analysis and Optimization:
Close Price (Default): Most commonly used, reflects final market sentiment of each period. Best for end-of-day analysis, swing trading, daily/weekly timeframes. Advantages: widely accepted standard, good for backtesting comparisons. Disadvantages: ignores intraday price action, may miss important highs/lows
HL2 (High+Low)/2: Midpoint of the trading range, reduces impact of opening gaps and closing spikes. Best for volatile markets, gap-prone assets, forex markets. Calculation impact: smoother MACD signals, reduced noise from price spikes. Optimal when asset shows frequent gaps, high volatility during specific sessions
HLC3 (High+Low+Close)/3: Weighted average emphasizing the close while including range information. Best for balanced analysis, most asset classes, medium-term trading. Mathematical effect: 33% weight to high/low, 33% to close, provides compromise between close and HL2. Use when standard close is too noisy but HL2 is too smooth
OHLC4 (Open+High+Low+Close)/4: True average of all price points, most comprehensive view. Best for complete price representation, algorithmic trading, statistical analysis. Considerations: includes opening sentiment, smoothest of all options but potentially less responsive. Optimal for markets with significant opening moves, comprehensive trend analysis
Parameter Configuration Principles:
Important Note: Different moving average algorithms have distinct mathematical characteristics and response patterns. The same parameter settings may produce vastly different results when using different algorithms. When switching algorithms, parameter settings should be re-evaluated and tested for appropriateness.
Length Parameter Considerations:
Fast Length (Default 12): Shorter periods provide faster response but may increase noise and false signals, longer periods offer more stable signals but slower response, different algorithms respond differently to the same parameters and may require adjustment
Slow Length (Default 26): Should maintain a reasonable proportional relationship with fast length, different timeframes may require different parameter configurations, algorithm characteristics influence optimal length settings
Signal Length (Default 9): Shorter lengths produce more frequent crossovers but may increase false signals, longer lengths provide better signal confirmation but slower response, should be adjusted based on trading style and chosen algorithm characteristics
Comprehensive Algorithm Selection Framework:
MACD Line Algorithm Decision Matrix:
EMA (Standard Choice): Mathematical properties: exponential weighting, recent price emphasis. Best for general use, traditional MACD behavior, backtesting compatibility. Performance characteristics: good balance of speed and smoothness, widely understood behavior
SMA (Stability Focus): Equal weighting of all periods, maximum smoothness. Best for ranging markets, noise reduction, conservative trading. Trade-offs: slower signal generation, reduced sensitivity to recent price changes
HMA (Speed Optimized): Hull Moving Average, designed for reduced lag. Best for trending markets, quick reversals, active trading. Technical advantage: square root period weighting, faster trend detection. Caution: can be more sensitive to noise
KAMA (Adaptive): Kaufman Adaptive MA, adjusts smoothing based on market efficiency. Best for varying market conditions, algorithmic trading. Mechanism: fast smoothing in trends, slow smoothing in sideways markets. Complexity: requires understanding of efficiency ratio
Signal Line Algorithm Optimization Strategies:
Matching Strategy: Use same algorithm for both MACD and signal lines. Benefits: consistent mathematical properties, predictable behavior. Best when backtesting historical strategies, maintaining traditional MACD characteristics
Contrast Strategy: Use different algorithms for optimization. Common combinations: MACD=EMA, Signal=SMA for smoother crossovers, MACD=HMA, Signal=RMA for balanced speed/stability, Advanced: MACD=KAMA, Signal=T3 for adaptive behavior with smooth signals
Market Regime Adaptation: Trending markets: both fast algorithms (EMA/HMA), Volatile markets: MACD=KALMAN_FILTER, Signal=SUPER_SMOOTHER, Range-bound: both slow algorithms (SMA/RMA)
Parameter Sensitivity Considerations:
Impact of Parameter Changes:
Length Parameter Sensitivity: Small parameter adjustments can significantly affect signal timing, while larger adjustments may fundamentally change indicator behavior characteristics
Algorithm Sensitivity: Different algorithms produce different signal characteristics. Thoroughly test the impact on your trading strategy before switching algorithms
Combined Effects: Changing multiple parameters simultaneously can create unexpected effects. Recommendation: adjust parameters one at a time and thoroughly test each change
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Response Characteristics by Algorithm:
Fastest Response: ZLEMA, HMA, T3 - minimal lag but higher noise
Balanced Performance: EMA, DEMA, TEMA - good trade-off between speed and stability
Highest Stability: SMA, RMA, TMA - reduced noise but increased lag
Adaptive Behavior: KAMA, FRAMA, MCGINLEY_DYNAMIC - automatically adjust to market conditions
Noise Filtering Capabilities:
Advanced algorithms like KALMAN_FILTER and SUPER_SMOOTHER help reduce false signals compared to traditional EMA-based MACD. Noise-reducing algorithms can provide more stable signals in volatile market conditions, though results will vary based on market conditions and parameter settings.
Market Condition Adaptability:
Unlike fixed-algorithm MACD, this enhanced version allows real-time optimization. Trending markets benefit from responsive algorithms (EMA, HMA), while ranging markets perform better with stable algorithms (SMA, RMA). The ability to switch algorithms without changing indicators provides greater flexibility.
Comparative Performance vs Traditional MACD:
Algorithm Flexibility: 21 algorithms vs 1 fixed EMA
Signal Quality: Reduced false signals through noise filtering algorithms
Market Adaptability: Optimizable for any market condition vs fixed behavior
Customization Options: Independent algorithm selection for MACD and signal lines vs forced matching
Professional Features: Advanced color coding, multiple alert conditions, comprehensive parameter control
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always combine with proper risk management and thorough strategy testing.
Larry Williams Oops StrategyThis strategy is a modern take on Larry Williams’ classic Oops setup. It trades intraday while referencing daily bars to detect opening gaps and align entries with the prior day’s direction. Risk is managed with day-based stops, and—unlike the original—all positions are closed at the end of the session (or at the last bar’s close), not at a fixed profit target or the first profitable open.
Entry Rules
Long setup (bullish reversion): Today opens below yesterday’s low (down gap) and yesterday’s candle was bearish. Place a buy stop at yesterday’s low + Filter (ticks).
Short setup (bearish reversion): Today opens above yesterday’s high (up gap) and yesterday’s candle was bullish. Place a sell stop at yesterday’s high − Filter (ticks).
Longs are only taken on down-gap days; shorts only on up-gap days.
Protective Stop
If long, stop loss trails the current day’s low.
If short, stop loss trails the current day’s high.
Exit Logic
Positions are force-closed at the end of the session (in the last bar), ensuring no overnight exposure. There is no take-profit; only stop loss or end-of-day flat.
Notes
This strategy is designed for intraday charts (minutes/seconds) using daily data for gaps and prior-day direction.
Longs/shorts can be enabled or disabled independently.
GRG/RGR Signal, MA, Ranges and PivotsThis indicator is a combination of several indicators.
It is a combination of two of my indicators which I solely use for trading
1. EMA 10-20-50-200, Pivots and Previous Day/Week/Month range
2. 3/4-Bar GRG / RGR Pattern (Conditional 4th Candle)
You can use them individually if you already have some of them or just use this one. Belive me when I say, this is all you need, along with market structure knowlege and even if you don’t have that, this indicator has been doing wonders for me. This is all I use. I do not use anything else.
**Note - Do checkout the indicators individually as I have added valuable information in the comment section.
It contains the following,
1. 10 EMA/SMA - configurable
2. 20 EMA/SMA - configurable
3. 50 EMA/SMA - configurable
4. 200 EMA/SMA - configurable
5. Previous Day's Range - configurable
6. Previous Week's Range - configurable
7. Previous Month's Range - configurable
8. Pivots - configurable
9. Buy Sell Signal - configurable
The Moving Averages
It is a very important combination and using it correctly with price action will strengthen your entries and exits.
The ema's or sma's added are the most powerful ones and they do definitely act as support and resistance.
The Daily/Weekly/Monthly Ranges
The Daily/Weekly/Monthly ranges are extremely important for any trader and should be used for targets and reversals.
Pivots
Pivots can provide support and resistance level. R5 and S5 can be used to check for over stretched conditions. You can customise them however you like. It is a full pivot indicator.
It is defaulted to show R5 and S5 only to reduce noise in the chart but it can be customised.
The 3/4 RGR or GRG Signal Generator
Combined with a 3/4 RGR or GRG setup can be all a trader needs.
You don't need complex strategies and SMC concepts to trade. Simple EMAs, ranges and RGR/GRG setup is the most winning combination.
This indicator can be used to identify the Green-Red-Green or Red-Green-Red pattern.
It is a price action indicator where a price action which identifies the defeat of buyers and sellers.
If the buyers comprehensively defeat the sellers then the price moves up and if the sellers defeat the buyers then the price moves down.
In my trading experience this is what defines the price movement.
It is a 3 or 4 candle pattern, beyond that i.e, 5 or more candles could mean a very sideways market and unnecessary signal generation.
How does it work?
Upside/Green signal
1. Say candle 1 is Green, which means buyers stepped in, then candle 2 is Red or a Doji, that means sellers brought the price down. Then if candle 3 is forming to be Green and breaks the closing of the 1st candle and opening of the 2nd candle, then a green arrow will appear and that is the place where you want to take your trade.
2. Here the buyers defeated the sellers.
3. Sometimes candle 3 falls short but candle 4 breaks candle 1's closing and candle 2's opening price. We can enter on candle 4.
4. Important - We need to enter the trade as soon as the price moves above the candle 1 and 2's body and should not wait for the 3rd or 4th candle to close. Ignore wicks.
5. But for a more optimised entry I have added an option to use candle’s highs and lows instead of open and close. This reduces lot of noise and provides us with more precise entry. This setting is turned on by default.
6. I have restricted it to 4 candles and that is all that is needed. More than that is a longer sideways market.
7. I call it the +-+ or GRG pattern or Green-Red-Green or Buyer-Seller-Buyer or Seller defeated or just Buyer pattern.
8. Stop loss can be candle 2's mid for safe traders (that includes me) or candle 2's body low for risky traders.
9. Back testing suggests that body low will be useless and result in more points in loss because for the bigger move this point will not be touched, so why not get out faster.
Downside/Red signal
1. Say candle 1 is Red, which means sellers stepped in, then candle 2 is Green or a Doji, that means buyers took the price up. Then if candle 3 is forming to be Red and breaks the closing of the 1st candle and opening of the 2nd candle then a Red arrow will appear and that is the place where you want to take your trade.
2. Sometimes candle 3 falls short but candle 4 breaks candle 1's closing and candle 2's opening price. We can enter on candle 4.
3. We need to enter the trade as soon as the price moves below the candle 1 and 2's body and should not wait for the 3rd or 4th candle to close.
4. But for a more optimised entry I have added an option to use candle’s highs and lows instead of open and close. This reduces lot of noise and provides us with more precise entry. This setting is turned on by default.
5. I have restricted it to 4 candles and that is all that is needed. More than that is a longer sideways market.
6. I call it the -+- or RGR pattern or Red-Green-Red or Seller-Buyer-Seller or Buyer defeated or just Seller pattern.
7. Stop loss can be candle 2's mid for safe traders ( that includes me) or candle 2's body high for risky traders.
8. Back testing suggests that body high will be useless and result in more points in loss because for the bigger move this point will not be touched, so why not get out faster.
Combining Indicators and Signal
Combining these indicators with GRG/RGR signal can be very powerful and can provide big moves.
1. MA crossover and Signal - This is very powerful and provides a very big move. Trades can be held for longer. If after taking the trade we notice that the MA crossover has happened then trades can be held for higher targets.
2. Pivots and Signal - Pivots and add a support or resistance point. Take profits on these points. R5/S5 are over streched conditions so we can start looking for reversal signals and ignore other signals
3. Intraday Range - first 1, 5, 15 min of the day - Sideways days is when price will stay in these ranges. You can take profits at these ranges or if the range is broken and we get a signal, then it can mean that the direction will be sustained.
4. Previous Day/Week/Month Ranges - These can be used as Take Profit points if the price is moving towards them after getting the signal. If the range is broken and we get a signal then it can be a strong signal. They can also be used as reversal points if a strong signal is generated.
Important Settings
1. Include 4th Candle Confirmation - You can enable or disable the 4th candle signal to avoid the noise, but at times I have noticed that the 4th candle gives a very strong signal or I can say that the strong signal falls on the 4th candle. This is mostly a coincidence.
2. Bars to check (default 10) - You can also configure how many previous bars should the signal be generated for. 10 to 30 is good enough. To backtest increase it to 2000 or 5000 for example.
3. Use Candle High/Low for confirmation instead of Candle Open/Close - More optimized entry and noise reduction. This option is now defaulted to false.
4. Show Green-Red-Green (bull) signals - Show only bull entries. Useful when I have a predefined view i.e, I know market is going to go up today.
5. Show Red-Green-Red (bear) signals - Show only bear entries. Useful when I have a predefined view i.e, I know market is going to go down today.
6. 3rd candle should be a Strong candle before considering 4th candle - This will enforce additional logic in 4 candle setup that the 3rd candle is the candle in our direction of breakout. This means something like GRGG is mandatory, which is still the default behaviour. If disabled, the 3rd candle can be any candle and 4th candle will act as our breakout candle. This behaviour has led to breakouts and breakdowns as times, hence I added this as a separate feature. Vice-versa for a RGGR.
For a 4 candle setup till now we were expecting GRGG or RGRR but we can let the system ignore the 3rd candle completely if needed.
This will result in additional signals.
7. Three intraday ranges added for index and stock traders - 1 min, 5 min and 15 min ranges will be displayed. These are disabled by default except 15 min. These are very important ranges and in sideways days the price will usually move within the 15 min. A breakout of this range and a positive signal can be a very powerful setup.
Safe traders can avoid taking a trade in this range as it can lead to fakeouts.
The line style, width, color and opacity are configurable.
Pointers/Golden Rules
1. If after taking the trade, the next candle moves in your direction and closes strong bullish or bearish, then move SL to break even and after that you can trail it.
2. If a upside trade hits SL and immediately a down side trade signal is generated on the next candle then take it. Vice versa is true.
3. Trades need to be taken on previous 2 candle's body high or low combined and not the wicks.
4. The most losses a trader takes is on a sideways day and because in our strategy the stop loss is so small that even on a sideways day we'll get out with a little profit or worst break even.
5. Hold trades for longer targets and don't panic.
6. If last 3-4 days have been sideways then there is a good probability that today will be trending so we can hold our trade for longer targets. Inverse is true when the market has been trending for 2-3 days then volatility followed by sideways is coming (DOW theory). Target to hold the trade for whole day and not exit till the day closes.
7. In general avoid trading in the middle of the day for index and stocks. Divide the day into 3 parts and avoid the middle.
8. Use Support/Resistance, 10, 20, 50, 200 EMA/SMA, Gaps, Whole/Round numbers(very imp) for identifying targets.
9. Trail your SL.
10. For indexes I would use 5 min and 15 min timeframe and at times 10 mins.
11. For commodities and crypto we can use higher timeframe as well. Look for signals during volatile time durations and avoid trading the whole day. Signal usually gives good targets on those times.
12. If a GRG or RGR pattern appears on a daily timeframe then this is our time to go big.
13. Minimum Risk to Reward should be 1:2 and for longer targets can be 1:4 to 1:10.
14. Trade with small lot size. Money management will happen automatically.
15. With small lot size and correct Risk-Reward we can be very profitable. Don't trade with big lot size.
16. Stay in the market for longer and collect points not money.
17. Very imp - Watch market and learn to generate a market view.
18. Very imp - Only 3 type of candles are needed in trading -
Strong Bullish (Big Green candle), Strong Bearish (Big Red candle),
Hammer (it is Strong Bullish), Inverse Hammer (it is Strong Bearish)
and Doji (indecision or confusion).
If on daily timeframe I see Strong Bullish candle previous day then I am biased to the upside the next day, if I see Strong Bearish candle the previous day then I am biased to the downside the next day, if I see Doji on the previous day then I am cautious the next day, if there are back to back Dojis forming in daily or weekly then I am preparing for big move so time to go big once I get the signal.
19. Most Important Candlestick pattern - Bullish and Bearish Engulfing
20. The only Chart patterns I need -
a) Falling Wedge/Channel Bullish Pattern Uptrend or Bull Flag - Buying - Forming over a couple days for intraday and forming over a couple of weeks for swing
b) Falling Wedge/Channel Bullish Pattern Downtrend or Falling Channel - Buying
c) Rising Wedge Bearish Pattern Uptrend or Rising Channel - Selling
d) Rising Wedge Bearish Pattern Downtrend or Bear flag - Selling
e) Head and Shoulder - Over a longer period not for intraday. In 15 min takes few days and for swing 1hr or 4h or daily can take few days
f) M and W pattern - Reversal Patterns - They form within the above 4 patterns, usually resulting in the break of trend line
21. How Gaps work -
a) Small Gap up in Uptrend - Market can fill the gap and reverse. The perception is that people are buying. If previous day candle was Strong Bullish then market view is up.
b) Big Gap up in Uptrend - Not news driven - Profit booking will come but may not fill the entire gap
c) Big Gap up in Uptrend - News driven, war related, tax, interest rate - Market can keep going up without stopping.
c) Flat opening in Uptrend - Big chance of market going up. If previous day candle was Strong Bullish then view is upwards, if it was Doji then still upwards.
d) Gap down in Uptrend - Market is surprised. After going down initially it can go up
e) Small Gap down in Downtrend - Market can fill the gap and keep moving down. If previous day candle was Strong Bearish then view is still down.
f) Flat opening in Downtrend - View is down, short today.
g) Big Gap down in Downtrend - Profit booking and foolish buying will come but market view is still down.
h) Gap down with News - Volatility, sideways then down.
i) Gap Up in Downtrend - Can move up - Price can move up during 2/3rd of the day and End of the day revert and close in red.
22. Go big on bearish days for option traders. Puts are better bought and Calls are better sold.
23. Cluster of green signals can lead to bigger move on the upside and vice versa for red signals.
24. Most of this is what I learned from successful traders (from the top 2%) only the indicator is mine.
ULTIMATE Smart Trading Pro 🔥
## 🇬🇧 ENGLISH
### 📊 The Most Complete All-in-One Trading Indicator
**ULTIMATE Smart Trading Pro** combines the best technical analysis tools and Smart Money Concepts into a single powerful and intelligent indicator. Designed for serious traders who want a real edge in the markets.
---
### ✨ KEY FEATURES
#### 💰 **SMART MONEY CONCEPTS**
- **Order Blocks**: Automatically detects institutional zones where "smart money" enters positions
- **Break of Structure (BOS)**: Identifies structure breaks to confirm trend changes
- **Liquidity Zones**: Spots equal highs/lows areas where institutions hunt stops
- **Market Structure**: Visually displays bullish (green background) or bearish (red background) structure
#### 📈 **ADVANCED TECHNICAL INDICATORS**
- **RSI with Auto Divergences**: Classic RSI + automatic detection of bullish and bearish divergences
- **MACD with Signals**: Identifies bullish and bearish crossovers in real-time
- **Dynamic Support & Resistance**: Adaptive zones with intelligent scoring based on volume, multiple touches, and ATR
- **Fair Value Gaps (FVG)**: Detects unfilled price gaps (imbalance zones)
#### 📐 **AUTOMATIC TOOLS**
- **Auto Fibonacci**: Automatically calculates Fibonacci retracement levels on the last major trend
- **Pivot Points**: Daily, Weekly, or Monthly pivot points (PP, R1, R2, S1, S2)
- **Pattern Finder**: Automatically detects candlestick patterns (Hammer, Shooting Star, Engulfing, Morning/Evening Star) and chart patterns (Double Top/Bottom)
---
### 🎯 HOW TO USE IT
#### Quick Setup:
1. **Add the indicator** to your chart
2. **Open Settings** and enable/disable modules as needed
3. **Adjust parameters** for your trading style (scalping, swing, day trading)
#### Optimal Trading Setup:
🔥 **ULTRA STRONG Signal** when you have:
- An institutional **Order Block**
- Aligned with a **Support/Resistance** tested 3+ times
- An unfilled **FVG** nearby
- An **RSI divergence** confirming the reversal
- On a key **Fibonacci** level (50%, 61.8%, or 78.6%)
- Favorable market structure (green background for buys, red for sells)
---
### 💡 UNIQUE ADVANTAGES
✅ **Adaptive Intelligence**: Automatically adjusts to market volatility (ATR)
✅ **Volume Filters**: Validates important levels with volume confirmation
✅ **Multi-Timeframe Ready**: Works on all timeframes (1m to 1M)
✅ **Complete Alerts**: Notifications for all important signals
✅ **Clear Interface**: Emojis and colored labels for quick identification
✅ **Intelligent Scoring**: Levels ranked by importance (🔴🔴🔴 = very strong)
✅ **100% Customizable**: Enable only what you need
---
### 🎨 SYMBOL LEGEND
**Smart Money:**
- 🟢 OB = Bullish Order Block
- 🔴 OB = Bearish Order Block
- BOS ↑/↓ = Break of Structure
- 💧 LIQ = Liquidity Zone
**Candlestick Patterns:**
- 🔨 = Hammer (bullish signal)
- ⭐ = Shooting Star (bearish signal)
- 📈 = Bullish Engulfing
- 📉 = Bearish Engulfing
- 🌅 = Morning Star (bullish reversal)
- 🌆 = Evening Star (bearish reversal)
**Indicators:**
- 🚀 MACD ↑ = Bullish crossover
- 📉 MACD ↓ = Bearish crossover
- ⚠️ DIV = Bearish RSI divergence
- ✅ DIV = Bullish RSI divergence
**Support & Resistance:**
- 🟢/🔴 S1, R1 = Support/Resistance
- 🟢🟢🟢/🔴🔴🔴 = VERY strong level (3+ touches)
- (×N) = Number of times touched
---
### ⚙️ RECOMMENDED SETTINGS
**For Scalping (1m - 5m):**
- SR Lookback: 15
- Structure Strength: 3
- RSI: 14
- Volume Filter: ON
**For Day Trading (15m - 1H):**
- SR Lookback: 20
- Structure Strength: 5
- RSI: 14
- All filters: ON
**For Swing Trading (4H - Daily):**
- SR Lookback: 30
- Structure Strength: 7
- Pattern Lookback: 100
- Fibonacci: ON
---
### 🚨 DISCLAIMER
This indicator is a decision support tool. It does not guarantee profits and does not constitute financial advice. Always test on a demo account before real use. Trading involves significant risks.
---
## 📞 SUPPORT & UPDATES
For questions, suggestions, or bug reports, please comment below or contact the author.
**Version:** 1.0
**Last Updated:** October 2025
**Compatible:** TradingView Pine Script v6
---
### 🌟 If you find this indicator useful, please give it a 👍 and share it with other traders!
**Happy Trading! 🚀📈**
HPZ — 4H Sell Zones (Ultra High Quality)Only finds sell setups.
Only shows overlaps between 4H Fair Value Gaps and Bearish Order Blocks.
Filters out small gaps or candles with too little momentum.
Displays a red box(HPZ) only when overlap is valid.
Optionally shows a “HPZ sell” label when price enters the zone.
Includes tiny swing markers for visual reference.
HPZ — 4H Buy Zones (Ultra High Quality)Only finds BUY setups.
Only shows overlaps between 4H Fair Value Gaps and Bullish Order Blocks.
Filters out small gaps or candles with too little momentum.
Displays a green box (HPZ) only when overlap is valid.
Optionally shows a “HPZ BUY” label when price enters the zone.
Includes tiny swing markers for visual reference.
US Government Shutdowns – Full History (with durations)이 지표는 1976년 이후 실제로 정부 기능이 중단된 모든 미국 정부 셧다운 기간을 시각화합니다.
S&P500 또는 지정한 심볼 차트 위에 각 셧다운 구간을 세로선과 음영 박스로 표시하고,
각 기간의 지속일수(일) 라벨을 함께 제공합니다.
데이터 출처: 미국 하원 공식 기록 (U.S. House History – Funding Gaps and Shutdowns in the Federal Government)
기능
• 모든 셧다운 구간 자동 표시
• 음영/세로선/라벨 개별 On-Off 가능
• 진행 중인 셧다운은 자동으로 ‘현재 시점까지’ 확장 표시
시장 변동성 분석, 정책 이벤트 리스크 평가, 장기 매크로 백테스트 등에 유용합니다.
This indicator visualizes all official US government shutdown periods since 1976 directly on any selected chart (default: S&P 500).
Each shutdown period is shown with vertical lines and shaded boxes, along with labels indicating the duration in days.
Data Source: U.S. House History – Funding Gaps and Shutdowns in the Federal Government
Features:
• Displays every historical shutdown automatically
• Optional shading, lines, and duration labels
• Ongoing shutdowns dynamically extend to the current date
Useful for analyzing volatility around fiscal policy events and long-term macro correlations.
LA - Opening Price based Previous day Range PivotThis "LA - Opening Price based Previous day Range Pivot" indicator is a custom technical analysis tool designed for Trading View charts. It plots support and resistance levels (often referred to as pivots or ranges) based on the current opening price combined with the previous period's trading range. The "previous period" can be daily, weekly, or monthly, making it a multi-timeframe tool. These levels are projected using Fibonacci-inspired multipliers to create potential breakout or reversal zones.
The core idea is inspired by concepts like the Opening Range Breakout (ORB) strategy or Fibonacci pivots, but it's customized here to use a dynamic range calculation (the maximum of several absolute price differences) rather than a simple high-low range. This makes it more robust for volatile markets. Levels are symmetric above (resistance) and below (support) the opening price, helping traders identify potential entry/exit points, stop-losses, or targets. This will be useful when there is a gap-up/down as in Nifty/Sensex .
Purpose of the Indicator:
To visualize potential support/resistance zones for the current trading session based on the opening price and historical range data. This helps traders anticipate price movements, such as breakouts above resistance or bounces off support
Use Cases:
Intraday Trading: On lower timeframes (e.g., 5-min or 15-min charts), it shows daily levels for short-term trades.
Swing Trading: On higher timeframes (e.g., hourly or daily), it displays weekly/monthly levels for longer holds.
Range Identification: The filled bands highlight "zones" where price might consolidate or reverse.
Conditional Display: Levels only appear on appropriate timeframes (e.g., daily levels on intraday charts <60min), preventing clutter.
Theoretical Basis: It builds on pivot point theory, where the opening price acts as a central pivot. Multipliers (e.g., 0.618 for Fibonacci golden ratio) project levels, assuming price often respects these ratios due to market psychology.
How Calculations Work
Let's dive into the math with examples. Assume a stock with:
Current daily open (cdo) = $100
Previous daily high (pdh) = $105, low (pdl) = $95, close (pdc) = $102, close 2 days ago (pdc2) = $98
Step 1: Dynamic Range Calculation (var_d2):
This is the max of:
|pdh - pdc2| = |105 - 98| = 7
|pdl - pdc2| = |95 - 98| = 3
|pdh - pdl| = |105 - 95| = 10 (previous day range)
|pdh - cdo| = |105 - 100| = 5
|pdl - cdo| = |95 - 100| = 5
|pdc - cdo| = |102 - 100| = 2
|pdc2 - cdo| = |98 - 100| = 2
Max = 10 (so range = 10). This ensures the range accounts for gaps and extended moves, not just high-low.
Step 2: Level Projections:
Resistance (above open): Open + (Range * Multiplier)
dre6 = 100 + (10 * 1.5) = 115
dre5 = 100 + (10 * 1.27) ≈ 112.7
... down to dre0 = 100 + (10 * 0.1) = 101
dre50 = 100 + (10 * 0.5) = 105 (midpoint)
Support (below open): Open - (Range * Multiplier)
dsu0 = 100 - (10 * 0.1) = 99
... up to dsu6 = 100 - (10 * 1.5) = 85
Without Indicator
With Indicator
Pros and Cons
Pros:
Multi-Timeframe Flexibility: Seamlessly integrates daily, weekly, and monthly levels, useful for aligning short-term trades with longer trends (e.g., intraday breakout confirmed by weekly support).
Dynamic Range Calculation: Unlike standard pivots (just (H+L+C)/3), it uses max of multiple diffs, capturing gaps/volatility better—great for stocks with overnight moves.
Customizable via Inputs: Users can toggle levels, adjust multipliers, or change timeframes without editing code. Inline inputs keep the UI clean.
Visual Aids: Filled bands make zones obvious; conditional colors highlight "tight" vs. "wide" ranges (e.g., for volatility assessment).
Fibonacci Integration: Levels based on proven ratios, appealing to technical traders. Symmetric supports/resistances simplify strategy building (e.g., buy at support, sell at resistance).
No Repainting: Uses historical data with lookahead, so levels are fixed once calculated—reliable for back-testing.
Cons:
Chart Clutter: With all toggles on, 50+ plots/fills can overwhelm the chart, especially on mobile or small screens. Requires manual disabling.
Complexity for Beginners: Many inputs and calculations; without understanding fib ratios or range logic, it might confuse new users.
Performance Overhead: On low timeframes (e.g., 1-min), fetching higher TF data multiple times could lag, especially with many symbols or back-tests.
Assumes Volatility Persistence: Relies on previous range projecting future moves; in low-vol markets (e.g., sideways trends), levels may be irrelevant or too wide/narrow.
No Alerts or Signals: Purely visual; no built-in buy/sell alerts or crossover conditions—users must add separately.
Hardcoded Styles/Colors: Limited customization without code edits (e.g., can't change line styles via inputs).
Also, not optimized for non-stock assets (e.g., forex with 24/7 trading).
In summary, this is a versatile pivot tool for range-based trading based on Opening price, excelling in volatile markets but requiring some setup. If you're using it, start with defaults on a daily chart and toggle off unnecessary levels.
Shamji's Liquidity Sweep + FVG (Follow-up + Filters) Purpose (what it does)
This indicator looks for two related price structures used by many smart-money / liquidity-hunt traders:
Liquidity Sweeps — candles that wick beyond a recent swing high (for buy-side stop-hunts) or swing low (for sell-side stop-hunts), then close back inside. These are flagged as potential stop-hunt events that clear obvious liquidity.
Fair Value Gaps (FVGs) — simple 3-bar style gaps where an older bar’s high is below the current low (bullish FVG) or an older bar’s low is above the current high (bearish FVG). When an FVG appears after a sweep (within a configurable window), this is considered a follow-up alignment.
The script adds optional filters (volume spike and candle-range vs ATR) to increase confidence, and can restrict marking/alerts to only events that meet the follow-up and filter rules.
Order Block Volumatic FVG StrategyInspired by: Volumatic Fair Value Gaps —
License: CC BY-NC-SA 4.0 (Creative Commons Attribution–NonCommercial–ShareAlike).
This script is a non-commercial derivative work that credits the original author and keeps the same license.
What this strategy does
This turns BigBeluga’s visual FVG concept into an entry/exit strategy. It scans bullish and bearish FVG boxes, measures how deep price has mitigated into a box (as a percentage), and opens a long/short when your mitigation threshold and filters are satisfied. Risk is managed with a fixed Stop Loss % and a Trailing Stop that activates only after a user-defined profit trigger.
Additions vs. the original indicator
✅ Strategy entries based on % mitigation into FVGs (long/short).
✅ Lower-TF volume split using upticks/downticks; fallback if LTF data is missing (distributes prior bar volume by close’s position in its H–L range) to avoid NaN/0.
✅ Per-FVG total volume filter (min/max) so you can skip weak boxes.
✅ Age filter (min bars since the FVG was created) to avoid fresh/immature boxes.
✅ Bull% / Bear% share filter (the 46%/53% numbers you see inside each FVG).
✅ Optional candle confirmation and cooldown between trades.
✅ Risk management: fixed SL % + Trailing Stop with a profit trigger (doesn’t trail until your trigger is reached).
✅ Pine v6 safety: no unsupported args, no indexof/clamp/when, reverse-index deletes, guards against zero/NaN.
How a trade is decided (logic overview)
Detect FVGs (same rules as the original visual logic).
For each FVG currently intersected by the bar, compute:
Mitigation % (how deep price has entered the box).
Bull%/Bear% split (internal volume share).
Total volume (printed on the box) from LTF aggregation or fallback.
Age (bars) since the box was created.
Apply your filters:
Mitigation ≥ Long/Short threshold.
Volume between your min and max (if enabled).
Age ≥ min bars (if enabled).
Bull% / Bear% within your limits (if enabled).
(Optional) the current candle must be in trade direction (confirm).
If multiple FVGs qualify on the same bar, the strategy uses the most recent one.
Enter long/short (no pyramiding).
Exit with:
Fixed Stop Loss %, and
Trailing Stop that only starts after price reaches your profit trigger %.
Input settings (quick guide)
Mitigation source: close or high/low. Use high/low for intrabar touches; close is stricter.
Mitigation % thresholds: minimal mitigation for Long and Short.
TOTAL Volume filter: skip FVGs with too little/too much total volume (per box).
Bull/Bear share filter: require, e.g., Long only if Bull% ≥ 50; avoid Short when Bull% is high (Short Bull% max).
Age filter (bars): e.g., ≥ 20–30 bars to avoid fresh boxes.
Confirm candle: require candle direction to match the trade.
Cooldown (bars): minimum bars between entries.
Risk:
Stop Loss % (fixed from entry price).
Activate trailing at +% profit (the trigger).
Trailing distance % (the trailing gap once active).
Lower-TF aggregation:
Auto: TF/Divisor → picks 1/3/5m automatically.
Fixed: choose 1/3/5/15m explicitly.
If LTF can’t be fetched, fallback allocates prior bar’s volume by its close position in the bar’s H–L.
Suggested starting presets (you should optimize per market)
Mitigation: 60–80% for both Long/Short.
Bull/Bear share:
Long: Bull% ≥ 50–70, Bear% ≤ 100.
Short: Bull% ≤ 60 (avoid shorting into strong support), Bear% ≥ 0–70 as you prefer.
Age: ≥ 20–30 bars.
Volume: pick a min that filters noise for your symbol/timeframe.
Risk: SL 4–6%, trailing trigger 1–2%, distance 1–2% (crypto example).
Set slippage/fees in Strategy Properties.
Notes, limitations & best practices
Data differences: The LTF split uses request.security_lower_tf. If the exchange/data feed has sparse LTF data, the fallback kicks in (it’s deliberate to avoid NaNs but is a heuristic).
Real-time vs backtest: The current bar can update until close; results on historical bars use closed data. Use “Bar Replay” to understand intrabar effects.
No pyramiding: Only one position at a time. Modify pyramiding in the header if you need scaling.
Assets: For spot/crypto, TradingView “volume” is exchange volume; in some markets it may be tick volume—interpret filters accordingly.
Risk disclosure: Past performance ≠ future results. Use appropriate position sizing and risk controls; this is not financial advice.
Credits
Visual FVG concept and original implementation: BigBeluga.
This derivative strategy adds entry/exit logic, volume/age/share filters, robust LTF handling, and risk management while preserving the original spirit.
License remains CC BY-NC-SA 4.0 (non-commercial, attribution required, share-alike).
Liquidity + FVG + OB Markings (Fixed v6)This indicator is built for price-action traders.
It automatically finds and plots three key structures on your chart:
Liquidity Levels – swing highs & lows that often get targeted by price.
Fair-Value Gaps (FVG) – inefficient price gaps between candles.
Order-Blocks (OB) – zones created by strong, high-volume impulsive candles.
It also provides alerts and a small information table so you can quickly gauge the current market context.
StdDev Supertrend {CHIPA}StdDev Supertrend ~ C H I P A is a supertrend style trend engine that replaces ATR with standard deviation as the volatility core. It can operate on raw prices or log return volatility, with optional smoothing to control noise.
Key features include:
Supertrend trailing rails built from a stddev scaled envelope that flips the regime only when price closes through the opposite rail.
Returns-based mode that scales volatility by log returns for more consistent behavior across price regimes.
Optional smoothing on the volatility input to tune responsiveness versus stability.
Directional gap fill between price and the active trend line on the main chart; opacity adapts to the distance (vs ATR) so wide gaps read stronger and small gaps stay subtle.
Secondary pane view of the rails with the same adaptive fade, plus an optional candle overlay for context.
Clean alerts that fire once when state changes
Use cases: medium-term trend following, stop/flip systems, and visual regime confirmation when you prefer stddev-based distance over ATR.
Note: no walk-forward or robustness testing is implied; parameter choices and risk controls are on you.
Pairs Trading Scanner [BackQuant]Pairs Trading Scanner
What it is
This scanner analyzes the relationship between your chart symbol and a chosen pair symbol in real time. It builds a normalized “spread” between them, tracks how tightly they move together (correlation), converts the spread into a Z-Score (how far from typical it is), and then prints clear LONG / SHORT / EXIT prompts plus an at-a-glance dashboard with the numbers that matter.
Why pairs at all?
Markets co-move. When two assets are statistically related, their relationship (the spread) tends to oscillate around a mean.
Pairs trading doesn’t require calling overall market direction you trade the relative mispricing between two instruments.
This scanner gives you a robust, visual way to find those dislocations, size their significance, and structure the trade.
How it works (plain English)
Step 1 Pick a partner: Select the Pair Symbol to compare against your chart symbol. The tool fetches synchronized prices for both.
Step 2 Build a spread: Choose a Spread Method that defines “relative value” (e.g., Log Spread, Price Ratio, Return Difference, Price Difference). Each lens highlights a different flavor of divergence.
Step 3 Validate relationship: A rolling Correlation checks if the pair is moving together enough to be tradable. If correlation is weak, the scanner stands down.
Step 4 Standardize & score: The spread is normalized (mean & variability over a lookback) to form a Z-Score . Large absolute Z means “stretched,” small means “near fair.”
Step 5 Signals: When the Z-Score crosses user-defined thresholds with sufficient correlation , entries print:
LONG = long chart symbol / short pair symbol,
SHORT = short chart symbol / long pair symbol,
EXIT = mean reversion into the exit zone or correlation failure.
Core concepts (the three pillars)
Spread Method Your definition of “distance” between the two series.
Guidance:
Log Spread: Focuses on proportional differences; robust when prices live on different scales.
Price Ratio: Classic relative value; good when you care about “X per Y.”
Return Difference: Emphasizes recent performance gaps; nimble for momentum-to-mean plays.
Price Difference: Straight subtraction; intuitive for similar-scale assets (e.g., two ETFs).
Correlation A rolling score of co-movement. The scanner requires it to be above your Min Correlation before acting, so you’re not trading random divergence.
Z-Score “How abnormal is today’s spread?” Positive = chart richer than pair; negative = cheaper. Thresholds define entries/exits with transparent, statistical context.
What you’ll see on the chart
Correlation plot (blue line) with a dashed Min Correlation guide. Above the line = green zone for signals; below = hands off.
Z-Score plot (white line) with colored, dashed Entry bands and dotted Exit bands. Zero line for mean.
Normalized spread (yellow) for a quick “shape read” of recent divergence swings.
Signal markers :
LONG (green label) when Z < –Entry and corr OK,
SHORT (red label) when Z > +Entry and corr OK,
EXIT (gray label) when Z returns inside the Exit band or correlation drops below the floor.
Background tint for active state (faint green for long-spread stance, faint red for short-spread stance).
The two built-in dashboards
Statistics Table (top-right)
Pair Symbol Your chosen partner.
Correlation Live value vs. your minimum.
Z-Score How stretched the spread is now.
Current / Pair Prices Real-time anchors.
Signal State NEUTRAL / LONG / SHORT.
Price Ratio Context for ratio-style setups.
Analysis Table (bottom-right)
Avg Correlation Typical co-movement level over your window.
Max |Z| The recent extremes of dislocation.
Spread Volatility How “lively” the spread has been.
Trade Signal A human-readable prompt (e.g., “LONG A / SHORT B” or “NO TRADE” / “LOW CORRELATION”).
Risk Level LOW / MEDIUM / HIGH based on current stretch (absolute Z).
Signals logic (plain English)
Entry (LONG): The spread is unusually negative (chart cheaper vs pair) and correlation is healthy. Expect mean reversion upward in the spread: long chart, short pair.
Entry (SHORT): The spread is unusually positive (chart richer vs pair) and correlation is healthy. Expect mean reversion downward in the spread: short chart, long pair.
Exit: The spread relaxes back toward normal (inside your exit band), or correlation deteriorates (relationship no longer trusted).
A quick, repeatable workflow
1) Choose your pair in context (same sector/theme or known macro link). Think: “Do these two plausibly co-move?”
2) Pick a spread lens that matches your narrative (ratio for relative value, returns for short-term performance gaps, etc.).
3) Confirm correlation is above your floor no corr, no trade.
4) Wait for a stretch (Z beyond Entry band) and a printed LONG / SHORT .
5) Manage to the mean (EXIT band) or correlation failure; let the scanners’ state/labels keep you honest.
Settings that matter (and why)
Spread Method Defines the “mispricing” you care about.
Correlation Period Longer = steadier regime read, shorter = snappier to regime change.
Z-Score Period The window that defines “normal” for the spread; it sets the yardstick.
Use Percentage Returns Normalizes series when using return-based logic; keep on for mixed-scale assets.
Entry / Exit Thresholds Set your stretch and your target reversion zone. Wider entries = rarer but stronger signals.
Minimum Correlation The gatekeeper. Raising it favors quality over quantity.
Choosing pairs (practical cheat sheet)
Same family: two index ETFs, two oil-linked names, two gold miners, two L1 tokens.
Hedge & proxy: stock vs. sector ETF, BTC vs. BTC index, WTI vs. energy ETF.
Cross-venue or cross-listing: instruments that are functionally the same exposure but price differently intraday.
Reading the cues like a pro
Divergence shape: The yellow normalized spread helps you see rhythm fast spike and snap-back versus slow grind.
Corr-first discipline: Don’t fight the “Min Correlation” line. Good pairs trading starts with a relationship you can trust.
Exit humility: When Z re-centers, let the EXIT do its job. The edge is the journey to the mean, not overstaying it.
Frequently asked (quick answers)
“Long/Short means what exactly?”
LONG = long the chart symbol and short the pair symbol.
SHORT = short the chart symbol and long the pair symbol.
“Do I need same price scales?” No. The spread methods normalize in different ways; choose the one that fits your use case (log/ratio are great for mixed scales).
“What if correlation falls mid-trade?” The scanner will neutralize the state and print EXIT . Relationship first; trade second.
Field notes & patterns
Snap-back days: After a one-sided session, return-difference spreads often flag cleaner intraday mean reversions.
Macro rotations: Ratio spreads shine during sector re-weights (e.g., value vs. growth ETFs); look for steady corr + elevated |Z|.
Event bleed-through: If one symbol reacts to news and its partner lags, Z often flags a high-quality, short-horizon re-centering.
Display controls at a glance
Show Statistics Table Live state & key numbers, top-right.
Show Analysis Table Context/risk read, bottom-right.
Show Correlation / Spread / Z-Score Toggle the sub-charts you want visible.
Show Entry/Exit Signals Turn markers on/off as needed.
Coloring Adjust Long/Short/Neutral and correlation line colors to match your theme.
Alerts (ready to route to your workflow)
Pairs Long Entry Z falls through the long threshold with correlation above minimum.
Pairs Short Entry Z rises through the short threshold with correlation above minimum.
Pairs Trade Exit Z returns to neutral or the relationship fails your correlation floor.
Correlation Breakdown Rolling correlation crosses your minimum; relationship caution.
Final notes
The scanner is designed to keep you systematic: require relationship (correlation), quantify dislocation (Z-Score), act when stretched, stand down when it normalizes or the relationship degrades. It’s a full, visual loop for relative-value trading that stays out of your way when it should and gets loud only when the numbers line up.
Smarter Money Concepts Dashboard [PhenLabs]📊Smarter Money Concepts Dashboard
Version: PineScript™v6
📌Description
The Smarter Money Concepts Dashboard is a comprehensive institutional trading analysis tool that combines six of our most powerful smarter money concepts indicators into one unified suite. This advanced system automatically detects and visualizes Fair Value Gaps, Inverted FVGs, Order Blocks, Wyckoff Springs/Upthrusts, Wick Rejection patterns, and ICT Market Structure analysis.
Built for serious traders who need institutional-grade market analysis, this dashboard eliminates subjective interpretation by automatically identifying where smart money is likely positioned. The integrated real-time dashboard provides instant status updates on all active patterns, making it easy to monitor market conditions at a glance.
🚀Points of Innovation
● Multi-Module Integration: Six different SMC concepts unified in one comprehensive system
● Real-Time Dashboard Display: Live tracking of all active patterns with customizable positioning
● Advanced Volume Filtering: Institutional volume confirmation across all pattern types
● Automated Pattern Management: Smart memory system prevents chart clutter while maintaining relevant zones
● Probability-Based Wyckoff Detection: Mathematical probability calculations for spring/upthrust patterns
● Dual FVG System: Both standard and inverted Fair Value Gap detection with equilibrium analysis
🔧Core Components
● Fair Value Gap Engine: Detects standard FVGs with volume confirmation and equilibrium line analysis
● Inverted FVG Module: Advanced IFVG detection using RVI momentum filtering for inversion confirmation
● Order Block System: Institutional order block identification with customizable mitigation methods
● Wyckoff Pattern Recognition: Automated spring and upthrust detection with probability scoring
● Wick Rejection Analysis: High-probability reversal patterns based on wick-to-body ratios
● ICT Market Structure: Simplified institutional concepts with commitment tracking
🔥Key Features
● Comprehensive Pattern Detection: All major SMC concepts in one indicator with automatic identification
● Volume-Confirmed Signals: Multiple volume filters ensure only institutional-grade patterns are highlighted
● Interactive Dashboard: Real-time status display with active pattern counts and module status
● Smart Memory Management: Automatic cleanup of old patterns while preserving relevant market zones
● Full Alert System: Complete notification coverage for all pattern types and signal generations
● Customizable Display Options: Adjustable colors, transparency, and positioning for all visual elements
🎨Visualization
● Color-Coded Zones: Distinct color schemes for bullish/bearish patterns across all modules
● Dynamic Box Extensions: Automatically extending zones until mitigation or invalidation
● Equilibrium Lines: Fair Value Gap midpoint analysis with dotted line visualization
● Signal Markers: Clear spring/upthrust signals with directional arrows and probability indicators
● Dashboard Table: Professional-grade status panel with module activation and pattern counts
● Candle Coloring: Wick rejection highlighting with transparency-based visual emphasis
📖Usage Guidelines
Fair Value Gap Settings
● Days to Analyze: Default 15, Range 1-100 - Controls historical FVG detection period
● Volume Filter: Enables institutional volume confirmation for gap validity
● Min Volume Ratio: Default 1.5 - Minimum volume spike required for gap recognition
● Show Equilibrium Lines: Displays FVG midpoint analysis for precise entry targeting
Order Block Configuration
● Scan Range: Default 25 bars - Lookback period for structure break identification
● Volume Filter: Institutional volume confirmation for order block validation
● Mitigation Method: Wick or Close-based invalidation for different trading styles
● Min Volume Ratio: Default 1.5 - Volume threshold for significant order block formation
Wyckoff Analysis Parameters
● S/R Lookback: Default 20 - Support/resistance calculation period for spring/upthrust detection
● Volume Spike Multiplier: Default 1.5 - Required volume increase for pattern confirmation
● Probability Threshold: Default 0.7 - Minimum probability score for signal generation
● ATR Recovery Period: Default 5 - Price recovery calculation for pattern strength assessment
Market Structure Settings
● Auto-Detect Zones: Automatic identification of high-volume thin zones
● Proximity Threshold: Default 0.20% - Price proximity requirements for zone interaction
● Test Window: Default 20 bars - Time period for zone commitment calculation
Display Customization
● Dashboard Position: Four corner options for optimal chart layout
● Text Size: Scalable from Tiny to Large for different screen configurations
● Pattern Colors: Full customization of all bullish and bearish zone colors
✅Best Use Cases
● Swing Trading: Identify major institutional zones for multi-day position entries
● Day Trading: Precise intraday entries at Fair Value Gaps and Order Block boundaries
● Trend Analysis: Market structure confirmation for directional bias establishment
● Risk Management: Clear invalidation levels provided by all pattern boundaries
● Multi-Timeframe Analysis: Works across all timeframes from 1-minute to monthly charts
⚠️Limitations
● Market Condition Dependency: Performance varies between trending and ranging market environments
● Volume Data Requirements: Requires accurate volume data for optimal pattern confirmation
● Lagging Nature: Some patterns confirmed after initial price movement has begun
● Pattern Density: High-volatility markets may generate excessive pattern signals
● Educational Tool: Requires understanding of smart money concepts for effective application
💡What Makes This Unique
● Complete SMC Integration: First indicator to combine all major smart money concepts comprehensively
● Real-Time Dashboard: Instant visual feedback on all active institutional patterns
● Advanced Volume Analysis: Multi-layered volume confirmation across all detection modules
● Probability-Based Signals: Mathematical approach to Wyckoff pattern recognition accuracy
● Professional Memory Management: Sophisticated pattern cleanup without losing market relevance
🔬How It Works
1. Pattern Detection Phase:
● Multi-timeframe scanning for institutional footprints across all enabled modules
● Volume analysis integration confirms patterns meet institutional trading criteria
● Real-time pattern validation ensures only high-probability setups are displayed
2. Signal Generation Process:
● Automated zone creation with precise boundary definitions for each pattern type
● Dynamic extension system maintains relevance until mitigation or invalidation occurs
● Alert system activation provides immediate notification of new pattern formations
3. Dashboard Update Cycle:
● Live status monitoring tracks all active patterns and module states continuously
● Pattern count updates provide instant feedback on current market condition density
● Commitment tracking for market structure analysis shows institutional engagement levels
💡Note:
This indicator represents institutional trading concepts and should be used as part of a comprehensive trading strategy. Pattern recognition accuracy improves with understanding of smart money principles. Combine with proper risk management and multiple confirmation methods for optimal results.
Big Candle Trend█ OVERVIEW
The "Big Candle Trend" indicator is a technical analysis tool written in Pine Script® v6 that identifies large signal candles on the chart and determines the trend direction based on the analysis of all candles within a specified period. Designed for traders seeking a simple yet effective tool to identify key market movements and trends, the indicator provides clarity and precision through flexible settings, trend line visualization, and retracement lines on signal candles.
█ CONCEPTS
The goal of the "Big Candle Trend" indicator was to create a tool based solely on the size of candle bodies and their relative positions, making it universal and effective across all markets (stocks, forex, cryptocurrencies) and timeframes. Unlike traditional indicators that often rely on complex formulas or external data (e.g., volume), this indicator uses simple yet powerful price action logic. Large signal candles are identified by comparing their body size to the average body size over a selected period, and the trend is determined by analyzing price changes over a longer period relative to the average candle body size. Additionally, the indicator draws horizontal lines on signal candles, aiding in setting Stop Loss levels or delayed entries.
█ FEATURES
Large Signal Candle Detection: Identifies candles with a body larger than the average body multiplied by a user-defined multiplier, aligned with the trend (if the trend filter is enabled). Signals are displayed as triangles (green for bullish, red for bearish).
Trend Analysis: Determines the trend (uptrend, downtrend, or neutral) by comparing the price change over a selected period (trend_length) to the average candle body size multiplied by a trend strength multiplier. The trend starts when:
Uptrend: The price change (difference between the current close and the close from an earlier period) is positive and exceeds the average candle body size multiplied by the trend strength multiplier (avg_body_trend * trend_mult).
Downtrend: The price change is negative and exceeds, in absolute value, the average candle body size multiplied by the trend strength multiplier.
Neutral Trend: The price change is below the required threshold, indicating no clear market direction.The trend ends when the price change no longer meets the conditions for an uptrend or downtrend, transitioning to a neutral state or switching to the opposite trend when the price change reverses and meets the conditions for the new trend. This approach differs from standard methods as it focuses on price dynamics in the context of candle body size, offering a more intuitive and direct way to gauge trend strength.
Smoothed Trend Line: Displays a trend line based on the average price (HL2, i.e., the average of the high and low of a candle), smoothed using a user-defined smoothing parameter. The trend line reflects the market direction but is not tied to breakouts, unlike many other trend indicators, allowing for more flexible interpretation.
Retracement Lines: Draws horizontal lines on signal candles at a user-defined level (e.g., 0.618). The lines are displayed to the right of the candle, with a width of one candle. For bullish candles, the line is measured from the top of the body (close) downward, and for bearish candles, from the bottom of the body (close) upward, aiding in setting Stop Loss or delayed entries.
Trend Option: Option to enable a trend filter that limits large candle signals to those aligned with the current trend, enhancing signal precision.
Customizable Visualization: Allows customization of colors for uptrend, downtrend, and neutral states, trend line style, and shadow fill between the trend line and price.
Alerts: Built-in alerts for large signal candles (bullish and bearish) and trend changes (start of uptrend, downtrend, or neutral trend).
█ HOW TO USE
Add to Chart: Apply the indicator to your TradingView chart via the Pine Editor or Indicators menu.
Configure Settings:
Candle Settings:
Average Period (Candles): Sets the period for calculating the average candle body size.
Large Candle Multiplier: Multiplier determining how large a candle’s body must be to be considered "large".
Trend Settings:
Trend Period: Period for analyzing price changes to determine the trend.
Trend Strength Multiplier: Multiplier setting the minimum price change required to identify a significant trend.
Trend Line Smoothing: Degree of smoothing for the trend line.
Show Trend Line: Enables/disables the display of the trend line.
Apply Trend Filter: Limits large candle signals to those aligned with the current trend.
Trend Colors:
Customize colors for uptrend (green), downtrend (red), and neutral (gray) states, and enable/disable shadow fill.
Retracement Settings:
Retracement Level (0.0-1.0): Sets the level for lines on signal candles (e.g., 0.618).
Line Width: Sets the thickness of retracement lines.
Interpreting Signals:
Bullish Signal: A green triangle below the candle indicates a large bullish candle aligned with an uptrend (if the trend filter is enabled). A horizontal line is drawn to the right of the candle at the retracement level, measured from the top of the body downward.
Bearish Signal: A red triangle above the candle indicates a large bearish candle aligned with a downtrend (if the trend filter is enabled). A horizontal line is drawn to the right of the candle at the retracement level, measured from the bottom of the body upward.
rend Line: Shows the market direction (green for uptrend, red for downtrend, gray for neutral). Unlike many indicators, the trend line’s color is not tied to its breakout, allowing for more flexible interpretation of market dynamics.
Alerts: Set up alerts in TradingView for large signal candles or trend changes to receive real-time notifications.
Combining with Other Tools: Use the indicator alongside other technical analysis tools, such as support/resistance levels, RSI, moving averages, or Fair Value Gaps (FVG), to confirm signals.
█ APPLICATIONS
Price Action Trading: Large signal candles can indicate key market moments, such as breakouts of support/resistance levels or strong price rejections. Use signal candles in conjunction with support/resistance levels or FVG to identify entry opportunities. Retracement lines help set Stop Loss levels (e.g., below the line for bullish candles, above for bearish) or delayed entries after price returns to the retracement level and confirms trend continuation. Note that large candles often generate Fair Value Gaps (FVG), which should be considered when setting Stop Loss levels.
Trend Strategies: Enable the trend filter to limit signals to those aligned with the dominant market direction. For example, in an uptrend, look for large bullish candles as continuation signals. The indicator can also be used for position pyramiding, adding positions as subsequent large candles confirm trend continuation.
Practical Approach:
Large candles with high volume may indicate strong market participation, increasing signal reliability.
The trend line helps visually assess market direction and confirm large candle signals.
Retracement lines on signal candles aid in identifying key levels for Stop Loss or delayed entries.
█ NOTES
The indicator works across all markets and timeframes due to its universal logic based on candle body size and relative positioning.
Adjust settings (e.g., trend period, large candle multiplier, retracement level) to suit your trading style and timeframe.
Test the indicator on various markets (stocks, forex, cryptocurrencies) and timeframes to optimize its performance.
Use in conjunction with other technical analysis tools to enhance signal accuracy.
Martingale Strategy Simulator [BackQuant]Martingale Strategy Simulator
Purpose
This indicator lets you study how a martingale-style position sizing rule interacts with a simple long or short trading signal. It computes an equity curve from bar-to-bar returns, adapts position size after losing streaks, caps exposure at a user limit, and summarizes risk with portfolio metrics. An optional Monte Carlo module projects possible future equity paths from your realized daily returns.
What a martingale is
A martingale sizing rule increases stake after losses and resets after a win. In its classical form from gambling, you double the bet after each loss so that a single win recovers all prior losses plus one unit of profit. In markets there is no fixed “even-money” payout and returns are multiplicative, so an exact recovery guarantee does not exist. The core idea is unchanged:
Lose one leg → increase next position size
Lose again → increase again
Win → reset to the base size
The expectation of your strategy still depends on the signal’s edge. Sizing does not create positive expectancy on its own. A martingale raises variance and tail risk by concentrating more capital as a losing streak develops.
What it plots
Equity – simulated portfolio equity including compounding
Buy & Hold – equity from holding the chart symbol for context
Optional helpers – last trade outcome, current streak length, current allocation fraction
Optional diagnostics – daily portfolio return, rolling drawdown, metrics table
Optional Monte Carlo probability cone – p5, p16, p50, p84, p95 aggregate bands
Model assumptions
Bar-close execution with no slippage or commissions
Shorting allowed and frictionless
No margin interest, borrow fees, or position limits
No intrabar moves or gaps within a bar (returns are close-to-close)
Sizing applies to equity fraction only and is capped by your setting
All results are hypothetical and for education only.
How the simulator applies it
1) Directional signal
You pick a simple directional rule that produces +1 for long or −1 for short each bar. Options include 100 HMA slope, RSI above or below 50, EMA or SMA crosses, CCI and other oscillators, ATR move, BB basis, and more. The stance is evaluated bar by bar. When the stance flips, the current trade ends and the next one starts.
2) Sizing after losses and wins
Position size is a fraction of equity:
Initial allocation – the starting fraction, for example 0.15 means 15 percent of equity
Increase after loss – multiply the next allocation by your factor after a losing leg, for example 2.00 to double
Reset after win – return to the initial allocation
Max allocation cap – hard ceiling to prevent runaway growth
At a high level the size after k consecutive losses is
alloc(k) = min( cap , base × factor^k ) .
In practice the simulator changes size only when a leg ends and its PnL is known.
3) Equity update
Let r_t = close_t / close_{t-1} − 1 be the symbol’s bar return, d_{t−1} ∈ {+1, −1} the prior bar stance, and a_{t−1} the prior bar allocation fraction. The simulator compounds:
eq_t = eq_{t−1} × (1 + a_{t−1} × d_{t−1} × r_t) .
This is bar-based and avoids intrabar lookahead. Costs, slippage, and borrowing costs are not modeled.
Why traders experiment with martingale sizing
Mean-reversion contexts – if the signal often snaps back after a string of losses, adding size near the tail of a move can pull the average entry closer to the turn
Behavioral or microstructure edges – some rules have modest edge but frequent small whipsaws; size escalation may shorten time-to-recovery when the edge manifests
Exploration and stress testing – studying the relationship between streaks, caps, and drawdowns is instructive even if you do not deploy martingale sizing live
Why martingale is dangerous
Martingale concentrates capital when the strategy is performing worst. The main risks are structural, not cosmetic:
Loss streaks are inevitable – even with a 55 percent win rate you should expect multi-loss runs. The probability of at least one k-loss streak in N trades rises quickly with N.
Size explodes geometrically – with factor 2.0 and base 10 percent, the sequence is 10, 20, 40, 80, 100 (capped) after five losses. Without a strict cap, required size becomes infeasible.
No fixed payout – in gambling, one win at even odds resets PnL. In markets, there is no guaranteed bounce nor fixed profit multiple. Trends can extend and gaps can skip levels.
Correlation of losses – losses cluster in trends and in volatility bursts. A martingale tends to be largest just when volatility is highest.
Margin and liquidity constraints – leverage limits, margin calls, position limits, and widening spreads can force liquidation before a mean reversion occurs.
Fat tails and regime shifts – assumptions of independent, Gaussian returns can understate tail risk. Structural breaks can keep the signal wrong for much longer than expected.
The simulator exposes these dynamics in the equity curve, Max Drawdown, VaR and CVaR, and via Monte Carlo sketches of forward uncertainty.
Interpreting losing streaks with numbers
A rough intuition: if your per-trade win probability is p and loss probability is q=1−p , the chance of a specific run of k consecutive losses is q^k . Over many trades, the chance that at least one k-loss run occurs grows with the number of opportunities. As a sanity check:
If p=0.55 , then q=0.45 . A 6-loss run has probability q^6 ≈ 0.008 on any six-trade window. Across hundreds of trades, a 6 to 8-loss run is not rare.
If your size factor is 1.5 and your base is 10 percent, after 8 losses the requested size is 10% × 1.5^8 ≈ 25.6% . With factor 2.0 it would try to be 10% × 2^8 = 256% but your cap will stop it. The equity curve will still wear the compounded drawdown from the sequence that led to the cap.
This is why the cap setting is central. It does not remove tail risk, but it prevents the sizing rule from demanding impossible positions
Note: The p and q math is illustrative. In live data the win rate and distribution can drift over time, so real streaks can be longer or shorter than the simple q^k intuition suggests..
Using the simulator productively
Parameter studies
Start with conservative settings. Increase one element at a time and watch how the equity, Max Drawdown, and CVaR respond.
Initial allocation – lower base reduces volatility and drawdowns across the board
Increase factor – set modestly above 1.0 if you want the effect at all; doubling is aggressive
Max cap – the most important brake; many users keep it between 20 and 50 percent
Signal selection
Keep sizing fixed and rotate signals to see how streak patterns differ. Trend-following signals tend to produce long wrong-way streaks in choppy ranges. Mean-reversion signals do the opposite. Martingale sizing interacts very differently with each.
Diagnostics to watch
Use the built-in metrics to quantify risk:
Max Drawdown – worst peak-to-trough equity loss
Sharpe and Sortino – volatility and downside-adjusted return
VaR 95 percent and CVaR – tail risk measures from the realized distribution
Alpha and Beta – relationship to your chosen benchmark
If you would like to check out the original performance metrics script with multiple assets with a better explanation on all metrics please see
Monte Carlo exploration
When enabled, the forecast draws many synthetic paths from your realized daily returns:
Choose a horizon and a number of runs
Review the bands: p5 to p95 for a wide risk envelope; p16 to p84 for a narrower range; p50 as the median path
Use the table to read the expected return over the horizon and the tail outcomes
Remember it is a sketch based on your recent distribution, not a predictor
Concrete examples
Example A: Modest martingale
Base 10 percent, factor 1.25, cap 40 percent, RSI>50 signal. You will see small escalations on 2 to 4 loss runs and frequent resets. The equity curve usually remains smooth unless the signal enters a prolonged wrong-way regime. Max DD may rise moderately versus fixed sizing.
Example B: Aggressive martingale
Base 15 percent, factor 2.0, cap 60 percent, EMA cross signal. The curve can look stellar during favorable regimes, then a single extended streak pushes allocation to the cap, and a few more losses drive deep drawdown. CVaR and Max DD jump sharply. This is a textbook case of high tail risk.
Strengths
Bar-by-bar, transparent computation of equity from stance and size
Explicit handling of wins, losses, streaks, and caps
Portable signal inputs so you can A–B test ideas quickly
Risk diagnostics and forward uncertainty visualization in one place
Example, Rolling Max Drawdown
Limitations and important notes
Martingale sizing can escalate drawdowns rapidly. The cap limits position size but not the possibility of extended adverse runs.
No commissions, slippage, margin interest, borrow costs, or liquidity limits are modeled.
Signals are evaluated on closes. Real execution and fills will differ.
Monte Carlo assumes independent draws from your recent return distribution. Markets often have serial correlation, fat tails, and regime changes.
All results are hypothetical. Use this as an educational tool, not a production risk engine.
Practical tips
Prefer gentle factors such as 1.1 to 1.3. Doubling is usually excessive outside of toy examples.
Keep a strict cap. Many users cap between 20 and 40 percent of equity per leg.
Stress test with different start dates and subperiods. Long flat or trending regimes are where martingale weaknesses appear.
Compare to an anti-martingale (increase after wins, cut after losses) to understand the other side of the trade-off.
If you deploy sizing live, add external guardrails such as a daily loss cut, volatility filters, and a global max drawdown stop.
Settings recap
Backtest start date and initial capital
Initial allocation, increase-after-loss factor, max allocation cap
Signal source selector
Trading days per year and risk-free rate
Benchmark symbol for Alpha and Beta
UI toggles for equity, buy and hold, labels, metrics, PnL, and drawdown
Monte Carlo controls for enable, runs, horizon, and result table
Final thoughts
A martingale is not a free lunch. It is a way to tilt capital allocation toward losing streaks. If the signal has a real edge and mean reversion is common, careful and capped escalation can reduce time-to-recovery. If the signal lacks edge or regimes shift, the same rule can magnify losses at the worst possible moment. This simulator makes those trade-offs visible so you can calibrate parameters, understand tail risk, and decide whether the approach belongs anywhere in your research workflow.
POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV)
Version: PineScript™v6
📌Description
The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss.
POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously.
The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities.
🚀Points of Innovation
Micro-POC calculation using advanced OHLC-based volume distribution estimation
Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency
Persistence scoring system that quantifies directional consistency over multiple periods
Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts
Dynamic color-coded visualization system with intensity-based feedback
Comprehensive customization options for resolution, periods, and thresholds
🔧Core Components
POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms
Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization
Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration
Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting
Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation
Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships
🔥Key Features
Real-time POC calculation with 10-100 configurable price bands for optimal precision
Velocity tracking with customizable lookback periods from 5 to 50 bars
Acceleration measurement for detecting momentum changes in POC movement
Persistence scoring to validate signal strength and filter false signals
Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions
Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps
Adjustable information table displaying real-time metrics and current signals
Heat ribbon visualization showing price-POC relationship intensity
Multiple threshold settings for customizing signal sensitivity
Export capability for use with separate panel indicators
🎨Visualization
POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude
Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity
Signal Markers: Clear exhaustion top/bottom signals with labeled shapes
Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status
Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions
📖Usage Guidelines
POC Calculation Settings
POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar
Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation
POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise
Velocity Settings
Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity
Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration
Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals
Persistence Settings
Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation
Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals
Visual Settings
Show POC Connecting Lines: Toggle display of colored lines connecting POC levels
Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship
Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon
Alert Settings
Enable Continuation Alerts: Toggle alerts for continuation pattern detection
Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection
Enable POC Gap Alerts: Toggle alerts for significant POC gaps
Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts
✅Best Use Cases
Identifying trend continuation opportunities when POC velocity aligns with price direction
Spotting potential reversal points through exhaustion pattern detection
Confirming breakout validity by monitoring POC gap behavior
Adding volume-based context to traditional technical analysis
Managing position sizing based on POC-price basis strength
⚠️Limitations
POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution
Effectiveness may vary in low-volume or highly volatile market conditions
Requires complementary analysis tools for complete trading decisions
Signal frequency may be lower in ranging markets compared to trending conditions
Performance optimization needed for very short timeframes below 1-minute
💡What Makes This Unique
Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data
Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels
Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator
Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions
Persistence Validation: Unique scoring system to filter signals based on directional consistency
🔬How It Works
Volume Distribution Estimation:
Divides each bar into configurable price bands for volume analysis
Applies sophisticated weighting based on OHLC relationships and proximity to close
Identifies the price level with maximum estimated volume as the POC
Velocity and Acceleration Calculation:
Measures POC rate of change over specified lookback periods
Normalizes values using ATR for consistent cross-market performance
Calculates acceleration as the rate of change of velocity
Signal Generation Process:
Combines trend direction analysis using EMA crossovers
Applies velocity and persistence thresholds to filter signals
Generates continuation, exhaustion, and gap alerts based on specific criteria
💡Note:
This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions.
ATR SL/TPStop Loss Finder ATR
A Stop Loss Finder ATR indicator is a dynamic risk management tool leveraging the Average True Range (ATR) to identify and track optimal stop-loss levels based on current market volatility.
A stop hunt indicator is a technical tool designed to identify potential instances where large market participants, often referred to as "smart money," deliberately move the price to trigger a large number of stop-loss orders, creating a temporary price distortion before reversing the trend. These indicators aim to help traders detect these events to either avoid being stopped out or to enter trades in the direction of the anticipated reversal.
For example, a long wick below support with high volume may signal a bullish stop-hunt , indicating that the price has been driven down to trigger sell-stop orders before reversing upward. Conversely, a long wick above resistance with high volume may signal a bearish stop-hunt , suggesting the price was pushed up to trigger buy-stop orders before reversing downward. The presence of such wicks is often associated with candlestick patterns like hammers or shooting stars.
Unlike fixed stop-losses, this indicator adapts its distance from the current price using a customizable ATR multiplier, ensuring that stop-loss levels are neither too tight (prone to being triggered by normal market noise) nor too wide (exposing capital to excessive risk) . The core function calculates the true range—considering the current high-low range, gaps up, and gaps down—over a user-defined period (typically 14 bars), then applies a multiplier to generate a volatility-adjusted stop-loss distance . This approach allows the indicator to dynamically widen stops during high-volatility periods and tighten them during calm markets, providing a more responsive and context-aware exit strategy.
