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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.
Pine Script® indicator
by DCAUT
Background Trend Follower by exp3rtsThe Background Trend Follower indicator visually highlights the market’s daily directional bias using subtle background colors. It calculates the price change from the daily open and shades the chart background according to the current intraday momentum. 🟢 Green background → Price is significantly above the daily open (strong bullish trend) 🔴 Red background → Price is significantly below the daily open (strong bearish trend) 🟡 Yellow background → Price is trading near the daily open (neutral or consolidating phase) The script automatically detects each new trading day. It records the opening price at the start of the day. As the session progresses, it continuously measures how far the current price has moved from that open. When the move exceeds ±50 points (custom threshold), the background color adapts to reflect the trend strength. Perfect for traders who want a quick visual sense of intraday bias — bullish, bearish, or neutral — without cluttering the chart with extra indicators.
Pine Script® indicator
by exp3rts
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.
Pine Script® indicator
by DCAUT
Relative Strength Ratio • Leader Shift Signals## Overview This indicator computes a **Relative Strength (RS) ratio** between your chart’s symbol and a reference symbol (e.g. BTC or index), then overlays an EMA-based trend filter and detects **RS divergences** via RSI on that ratio. It highlights when your symbol is leading vs lagging, and spots potential turning points via bullish/negative divergences. No alerts are forced, you get visual cues (lines & labels) only. --- ## How It Works 1. **RS Ratio** = (base symbol price) ÷ (reference symbol price). 2. Two EMAs (fast & slow) filter trend context and help identify “leader shifts” (when ratio crosses the fast EMA under trend constraints). 3. **RSI on the ratio** is used to detect divergences. We find swing highs/lows in the *ratio* and compare their RSI values: * **Bearish RS divergence**: ratio makes a higher high, but RSI makes a lower high * **Bullish RS divergence**: ratio makes a lower low, but RSI makes a higher low 4. When divergence is confirmed, the script draws connecting lines (and optional markers) on the RS ratio pane to visually flag them. 5. You can customize pivot sensitivity, minimum separation, colors, and toggles for which graphics to show. --- ## Best Usage Suggestions * Use a **reference symbol** that is meaningfully related (e.g. BTC for altcoins, SPX for equities, or a sector index for a stock). The interpretive power comes from seeing relative strength vs a meaningful peer. * On **higher timeframes** (4H, daily), divergences tend to carry more weight. On lower intraday charts, tighten pivot settings to avoid noise. * Prefer divergence signals when the RS ratio is also in a favorable trend (e.g. above its EMA for bullish divergences, below for bearish). Using the trend filter EMAs helps reduce false signals. * Always confirm divergence signals with **price structure, volume, or other momentum indicators**. Divergence is a warning or a hint—not a standalone trigger. * Because RSI on ratio is subject to noise, avoid over-tuning pivots too tight; broader pivot widths give more robust divergence lines. --- ## Inputs & Customization * **Reference Symbol & Timeframe** for ratio comparison * **Fast EMA / Slow EMA lengths** and slope threshold (trend filter) * **RSI length** applied to the RS ratio * **Pivot left / right bars** and **min separation** to define sturdy swings * **Toggle lines / markers** visibility, and pick colors for divergence, ratio, EMAs * Optional “shade” or fill modes (if you have them) --- ## Limitations & Disclaimers * Divergence does **not guarantee** reversals—it often signals **weakening momentum or potential turning zones**, which may not always play out. * In extremely volatile or fast-moving markets, divergence lines may lag or fail. * The script relies on historical data (no future lookahead). Because pivots are confirmed after a few bars, some signals show with delay. * As always: combine with price action, structure, risk management. This is a tool—not a magic eight ball. ---
Pine Script® indicator
by Blk0ut
Adaptive Z-Momentum (AZM) [Blk0ut]Adaptive Z-Momentum (AZM) is a momentum indicator that expresses the normalized deviation of price from a dynamic anchor (VWAP or EMA) in standard-score (z-score) terms, with adaptive “extreme” thresholds, trend sensitivity, and optional regime filtering. The line color, background shading, and labels help you visually discern when momentum is mild, building, or overextended. --- ## Features & Concept * Computes **z = (price – anchor) / σ**, where the anchor is either Session VWAP (intraday) or EMA (non-intraday). * Uses exponential moving averages (EWMA) to adaptively estimate the running mean and variance, making the indicator responsive to regime changes. * Defines an **adaptive extreme threshold** (±z threshold) based on the chosen percentile of |z| over a lookback window (e.g. 90th percentile) — dynamically adjusting to volatility environment. * Colors the main z-line **differently when inside vs. outside the extreme thresholds**, giving immediate visual feedback. * Optionally shades the background when momentum is over the extremes (bullish or bearish). * Supports a **self-tuning mode** (ADX-aware) that tightens or relaxes lookback/smoothing in strong trend vs. chop regimes. * Regime filtering options (EMA slope or ADX threshold) let you filter signals in trend vs. non-trend markets. * Plots Δz (the change in z) in various styles to help detect acceleration or deceleration in momentum. * Adds optional thrust/fade labels to highlight when z crosses ±extreme zones, or when momentum stalls. --- ## How to Use * Look for **z crossing** above zero (bullish momentum) or below zero (bearish momentum). * When **z enters the extreme band**, it suggests strong momentum; when it exits, that may indicate exhaustion or reversal. * Watch **Δz** (momentum acceleration) for clues of weakening or strengthening momentum before z itself reacts. * Use the **regime filter** to enforce that signals only count in favorable directional markets. * Customize inputs: lookback window, smoothing length, extreme percentile, ADX/auto settings, colors, etc., to match your trading style and timeframe. *Use VWAP as the anchor on intraday/session charts — because it resets each session, it highlights deviations from session “fair value” and captures volume-flow bias. *Use EMA on swing or multi-day charts — it doesn’t reset, so it preserves trend structure and gives a smoother momentum baseline across sessions. *In trending markets, EMA tends to deliver more reliable momentum extremes; in range or mean-reversion regimes, VWAP often gives more intuitive reversal zones. --- ## Limitations & Disclaimers * Like all indicators, AZM is **lagging** (though adaptive) and should not be used as a standalone entry/exit trigger — always combine with price action, structure, or confirmation. * The extreme thresholds are **percentile-based**, meaning in very quiet or very noisy periods, “extreme” may shift rapidly; use your eyes alongside the indicator. * Because the script uses historical data and smoothing, earlier bars may differ from real-time behavior. * Past behavior is no guarantee of future performance. Use proper risk management and test ideas on historical data before trading live. --- ## Inputs & Customization * **Anchor** mode: Session VWAP (intraday) or EMA * **Lookback window** and **smoothing EMA** for computing z * **Extreme percentile** (e.g. 90) to define ±z thresholds * **Auto / ADX-based tuning** to allow dynamic parameter changes in trending vs chop markets * **Regime filter** (EMA slope or ADX) to restrict signals to trending conditions * **Color settings** for inside vs outside extremes, background shading, zero line, Δz style, labels, etc. * **Show/hide labels**, choose Δz style (columns, histogram, line, etc.) --- ## Why It’s Useful By combining standard-score normalization with adaptive thresholds and regime sensitivity, AZM helps you see **relative momentum extremes** in a way that adjusts to market regime shifts. The dual visual cues (line color + background) reduce ambiguity at a glance. ---
Pine Script® indicator
by Blk0ut
#MS Topping Tail DetectorShows potential Topping Tails. A topping tail is a candlestick pattern feature often seen on price charts that signals potential selling pressure or a reversal from an uptrend. Here’s how it works: 🔍 Definition A topping tail (also called an upper shadow or wick) is the thin line above the candlestick body showing how high the price went during a trading period before sellers pushed it back down. It indicates that buyers were in control early, but sellers took over, causing the price to fall from its high before the close.
Pine Script® indicator
by MatSeaburg
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.
Pine Script® indicator
by jcg3003
Short-Term Capitulation Oscillator (STCO, Diodato 2019)Description: This script is a faithful implementation of the Short-Term Capitulation Oscillator (STCO) from Chris Diodato's 2019 CMT paper, "Making The Most Of Panic". It's a tactical breadth and volume oscillator designed to "fish for market bottoms" by identifying short-term investor capitulation. What It Is The STCO combines the 10-day moving averages of NYSE up-volume and advancing issues. It measures the ratio of advancing momentum (in both volume and number of issues) relative to the total traded momentum. The result is a raw, un-normalized oscillator that typically ranges from 0 to 200. How to Interpret The STCO is a tactical tool for identifying near-term oversold conditions and potential bounces. Low Readings: Indicate that sellers have likely exhausted themselves in the short term, creating a potential entry point for a bounce. The paper found that readings below 90, 85, and 80 were often followed by strong market performance over the next 5-20 days. Overbought/Oversold Lines: Use the customizable overbought/oversold lines to define your own capitulation zones and potential entry areas. Settings Data Sources: Allows toggling the use of "Unchanged" issues/volume data. Thresholds: You can set the overbought and oversold levels based on the paper's research or your own testing.
Pine Script® indicator
by suresh789
Key Session Levels | Highs, Lows, OpensOverview Designed for scalping and intraday trading on ES, NQ, and other futures markets that trade around the clock, this indicator automatically plots key support/resistance levels: Session opens Session highs Session lows Overnight highs Overnight lows Session Definitions (America/New_York Time) Session (18:00 - 16:59 ET) Tracks complete trading cycle Plots: High, Low Represents true daily extremes of each session Overnight Session (18:00 - 9:30 ET) Captures Asian and European session price action Plots: Open, High, Low These levels can act as support/resistance during the NY session NY Session (9:30 - 16:59 ET) Optional background highlight for regular trading hours Helps visually distinguish active NY session from overnight action Key Features Flexible Extension Modes Same Day: Lines end at session close Next Day: Lines extend through the following session Full Chart: Lines extend indefinitely to the right Smart Line Management Optional extension of overnight levels through NY session Control how many historical sessions to display (1-250) Automatic cleanup of old lines Full Customization Individual color control for each level Line style options (solid, dotted, dashed) Line width adjustment (1px-4px) Show/hide any level independently Common Use Cases Support/Resistance Breakout/Break & Retest Strategy Wait for price to reach a key level Use Level 2 data to determine who's in control at the level (e.g. aggressive buyers vs. passive sellers) *this requires third-party software and a live data feed Enter long/short WITH institutional players, identified via Level 2 data Target areas/levels where the market may reverse Best Timeframes Works on any intraday timeframe, optimized for: 1m, 5m, 15m, 30m, 1H Notes All times are in America/New_York (Eastern Time) Requires intraday timeframe to detect specific session times Lines are semi-transparent by default for better chart visibility
Pine Script® indicator
by rdjxyz
BATOOT//@version=5 indicator('BATOOT', overlay=true) length = input.int(title='Length', minval=1, maxval=1000, defval=18) upBound = ta.highest(high, length) downBound = ta.lowest(low, length) LONG = ta.cross(high, upBound) SHORT = ta.cross(low, downBound) switch_1 = 0 setA = 0 setB = 0 if LONG and switch_1 == 0 switch_1 := 1 setA := 1 setB := 0 setB else if SHORT and switch_1 == 1 switch_1 := 0 setA := 0 setB := 1 setB else switch_1 := nz(switch_1 , 0) setA := 0 setB := 0 setB plotshape(setA, title='LONG', style=shape.triangleup, text='BUY', color=color.new(color.green, 0), textcolor=color.new(color.green, 0), location=location.belowbar, size=size.small) plotshape(setB, title='SHORT', style=shape.triangledown, text='SHORT', color=color.new(color.red, 0), textcolor=color.new(color.red, 0), location=location.abovebar, size=size.small) alertcondition(setA, title='LONG', message='LONG!') alertcondition(setB, title='SHORT', message='SHORT!') //Support and Resistance line_width = 3 sr_tf = input.timeframe('', title='S/R Timeframe') //Legacy RSI calc rsi_src = close len = 9 up1 = ta.rma(math.max(ta.change(rsi_src), 0), len) down1 = ta.rma(-math.min(ta.change(rsi_src), 0), len) legacy_rsi = down1 == 0 ? 100 : up1 == 0 ? 0 : 100 - 100 / (1 + up1 / down1) //CMO based on HMA length1 = 1 src1 = ta.hma(open, 5) // legacy hma(5) calculation gives a resul with one candle shift, thus use hma() src2 = ta.hma(close, 12) momm1 = ta.change(src1) momm2 = ta.change(src2) f1(m, n) => m >= n ? m : 0.0 f2(m, n) => m >= n ? 0.0 : -m m1 = f1(momm1, momm2) m2 = f2(momm1, momm2) sm1 = math.sum(m1, length1) sm2 = math.sum(m2, length1) percent(nom, div) => 100 * nom / div cmo_new = percent(sm1 - sm2, sm1 + sm2) //Legacy Close Pivots calcs. len5 = 2 h = ta.highest(len5) h1 = ta.dev(h, len5) ? na : h hpivot = fixnan(h1) l = ta.lowest(len5) l1 = ta.dev(l, len5) ? na : l lpivot = fixnan(l1) //Calc Values rsi_new = ta.rsi(close, 9) lpivot_new = lpivot hpivot_new = hpivot sup = rsi_new < 25 and cmo_new > 50 and lpivot_new res = rsi_new > 75 and cmo_new < -50 and hpivot_new calcXup() => var xup = 0.0 xup := sup ? low : xup xup calcXdown() => var xdown = 0.0 xdown := res ? high : xdown xdown //Lines drawing variables tf1 = request.security(syminfo.tickerid, sr_tf, calcXup(), lookahead=barmerge.lookahead_on) tf2 = request.security(syminfo.tickerid, sr_tf, calcXdown(), lookahead=barmerge.lookahead_on) //SR Line plotting var tf1_line = line.new(0, 0, 0, 0) var tf1_bi_start = 0 var tf1_bi_end = 0 tf1_bi_start := ta.change(tf1) ? bar_index : tf1_bi_start tf1_bi_end := ta.change(tf1) ? tf1_bi_start : bar_index if ta.change(tf1) tf1_line := line.new(tf1_bi_start, tf1, tf1_bi_end, tf1, color=color.green, width=line_width) tf1_line line.set_x2(tf1_line, tf1_bi_end) var tf2_line = line.new(0, 0, 0, 0) var tf2_bi_start = 0 var tf2_bi_end = 0 tf2_bi_start := ta.change(tf2) ? bar_index : tf2_bi_start tf2_bi_end := ta.change(tf2) ? tf2_bi_start : bar_index if ta.change(tf2) tf2_line := line.new(tf2_bi_start, tf2, tf2_bi_end, tf2, color=color.orange, width=line_width) tf2_line line.set_x2(tf2_line, tf2_bi_end)
Pine Script® indicator
by m00al