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Vortex Trend Matrix [JOAT]Vortex Trend Matrix - Multi-Factor Trend Confluence System Introduction and Purpose Vortex Trend Matrix is an open-source overlay indicator that combines Ichimoku-style equilibrium analysis with the Vortex Indicator to create a comprehensive trend confluence system. The core problem this indicator solves is that single trend indicators often give conflicting signals. Price might be above a moving average but momentum might be weakening. This indicator addresses that by combining five different trend factors into a single composite score, making it easy to identify when multiple factors align for high-probability trend trades. Why These Components Work Together Each component measures trend from a different perspective: 1. Cloud Position - Price above/below the equilibrium cloud indicates overall trend bias. The cloud acts as dynamic support/resistance. 2. TK Relationship - Conversion line vs Base line (like Tenkan/Kijun in Ichimoku). Conversion above Base = bullish momentum. 3. Lagging Span - Current price compared to price N bars ago. Confirms whether current move has follow-through. 4. Vortex Indicator - VI+ vs VI- measures directional movement strength. Provides momentum confirmation. 5. Base Direction - Whether the base line is rising or falling. Indicates medium-term trend direction. How the Trend Score Works float trendScore = 0.0 // Cloud position (+2/-2) trendScore += aboveCloud ? 2.0 : belowCloud ? -2.0 : 0.0 // TK relationship (+1/-1) trendScore += conversionLine > baseLine ? 1.0 : conversionLine < baseLine ? -1.0 : 0.0 // Lagging span (+1/-1) trendScore += laggingBull ? 1.0 : laggingBear ? -1.0 : 0.0 // Vortex (+1.5/-1.5) trendScore += vortexBull ? 1.5 : vortexBear ? -1.5 : 0.0 // Base direction (+0.5/-0.5) trendScore += baseDirection * 0.5 Score ranges from approximately -6 to +6: - +4 or higher = STRONG BULL - +2 to +4 = BULL - -2 to +2 = NEUTRAL - -4 to -2 = BEAR - -4 or lower = STRONG BEAR Signal Types TK Cross Up/Down - Conversion line crosses Base line (momentum shift) Base Direction Change - Base line changes direction (medium-term shift) Strong Bull/Bear Trend - Score reaches +4/-4 (high confluence) Dashboard Information Trend - Overall status with composite score Cloud - Price position (ABOVE/BELOW/INSIDE) TK Cross - Conversion vs Base relationship Lagging - Lagging span bias Vortex - VI+/VI- relationship VI+/VI- - Individual vortex values How to Use This Indicator For Trend Following: 1. Enter long when trend score reaches +4 or higher (STRONG BULL) 2. Enter short when trend score reaches -4 or lower (STRONG BEAR) 3. Use cloud as dynamic support/resistance for entries For Momentum Timing: 1. Watch for TK Cross signals for entry timing 2. Base direction changes indicate medium-term shifts 3. Vortex confirmation adds conviction For Risk Management: 1. Exit when trend score drops to neutral 2. Use cloud edges as stop-loss references 3. Reduce position when score weakens Input Parameters Conversion Period (9) - Fast equilibrium line Base Period (26) - Slow equilibrium line Lead Span Period (52) - Cloud projection period Displacement (26) - Cloud and lagging span offset Vortex Period (14) - Period for vortex calculation VI+ Strength (1.10) - Threshold for strong bullish vortex VI- Strength (0.90) - Threshold for strong bearish vortex Timeframe Recommendations 4H-Daily: Best for equilibrium-based analysis 1H: Good for intraday trend following Lower timeframes may require adjusted periods Limitations Equilibrium calculations have inherent lag Cloud displacement means signals are delayed Works best in trending markets May whipsaw in ranging conditions Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Trend analysis does not guarantee profitable trades. Always use proper risk management. - Made with passion by officialjackofalltrades
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Sentinel Market Structure [JOAT] Sentinel Market Structure - Smart Money Structure Analysis Introduction and Purpose Sentinel Market Structure is an open-source overlay indicator that identifies swing highs/lows, tracks market structure (HH/HL/LH/LL), detects Break of Structure (BOS) and Change of Character (CHoCH) signals, and marks order blocks. The core problem this indicator solves is that retail traders often miss structural shifts that smart money traders use to identify trend changes. This indicator addresses that by automatically tracking market structure and alerting traders to key structural breaks that often precede significant moves. Why These Components Work Together Each component provides different structural information: 1. Swing Detection - Identifies significant pivot highs and lows. These are the building blocks of market structure. 2. Structure Labels (HH/HL/LH/LL) - Classifies each swing relative to the previous swing. Higher Highs + Higher Lows = uptrend. Lower Highs + Lower Lows = downtrend. 3. Break of Structure (BOS) - Identifies when price breaks a swing level in the direction of the trend. This is a continuation signal. 4. Change of Character (CHoCH) - Identifies when price breaks a swing level against the trend. This is a potential reversal signal. 5. Order Blocks - Marks the last opposing candle before an impulse move. These zones often act as future support/resistance. How the Detection Works Swing Detection: bool swingHighDetected = high == ta.highest(high, swingLength * 2 + 1) bool swingLowDetected = low == ta.lowest(low, swingLength * 2 + 1) BOS vs CHoCH Logic: // BOS: Break in direction of trend (continuation) bool bullishBOS = close > lastSwingHigh and marketTrend >= 0 // CHoCH: Break against trend (reversal signal) bool bullishCHOCH = close > lastSwingHigh and marketTrend < 0 Order Block Detection: bool bullOB = close < open and // Previous candle bearish close > open and // Current candle bullish close > high and // Breaking above (high - low) > ta.atr(14) * 1.5 // Strong impulse Signal Types HH (Higher High) - Swing high above previous swing high (bullish structure) HL (Higher Low) - Swing low above previous swing low (bullish structure) LH (Lower High) - Swing high below previous swing high (bearish structure) LL (Lower Low) - Swing low below previous swing low (bearish structure) BOS↑/BOS↓ - Break of structure in trend direction (continuation) CHoCH↑/CHoCH↓ - Change of character against trend (potential reversal) Dashboard Information Trend - Current market bias (BULLISH/BEARISH/NEUTRAL) Swing High - Last swing high price with HH/LH label Swing Low - Last swing low price with HL/LL label Structure - Current structure state (HH+HL, LH+LL, etc.) Price - Price position relative to structure How to Use This Indicator For Trend Following: 1. Identify trend using structure (HH+HL = uptrend, LH+LL = downtrend) 2. Enter on BOS signals in trend direction 3. Use swing levels for stop placement For Reversal Trading: 1. Watch for CHoCH signals (break against trend) 2. Confirm with order block formation 3. Enter on retest of order block zone For Risk Management: 1. Place stops beyond swing highs/lows 2. Use structure lines as trailing stop references 3. Exit when CHoCH signals against your position Input Parameters Swing Detection Length (5) - Bars on each side for pivot detection Show Swing High/Low Points (true) - Toggle swing markers Show BOS/CHoCH (true) - Toggle structural break signals Show Structure Lines (true) - Toggle horizontal swing lines Show Order Blocks (true) - Toggle order block zones Zone Extension (50) - How far order block boxes extend Timeframe Recommendations 15m-1H: Good for intraday structure analysis 4H-Daily: Best for swing trading structure Lower timeframes require smaller swing detection length Limitations Swing detection has inherent lag (needs confirmation bars) Not all BOS/CHoCH signals lead to continuation/reversal Order block zones are simplified (not full ICT methodology) Structure analysis is subjective - different traders see different swings Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Market structure analysis does not guarantee trade outcomes. Always use proper risk management. - Made with passion by officialjackofalltrades
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Quantum Candle Scanner [JOAT] Quantum Candle Scanner - Advanced Multi-Pattern Recognition System Introduction and Purpose Quantum Candle Scanner is an open-source overlay indicator that detects multiple candlestick patterns including engulfing patterns, kicker patterns, inside bar setups, momentum candles, and higher-high/lower-low sequences. The core problem this indicator solves is that traders often miss patterns because they're looking for only one type. Different patterns work better in different market conditions. This indicator addresses that by scanning for five distinct pattern types simultaneously, giving traders a comprehensive view of price action signals. Why These Five Pattern Types Work Together Each pattern type identifies different market behavior: 1. Engulfing Patterns - Classic reversal signals where current candle completely engulfs the previous candle. Best for identifying potential turning points. 2. Kicker Patterns - Strong reversal signals with gap confirmation. The current candle opens beyond the previous candle's open with opposite direction. Best for identifying high-momentum reversals. 3. Inside Bar Patterns - Consolidation breakout signals where a candle's range is contained within the previous candle, followed by a breakout. Best for identifying compression before expansion. 4. Momentum Candles - Identifies the largest body candle over a lookback period. Best for spotting institutional activity. 5. HH/HL and LH/LL Sequences - Three-bar structure patterns showing trend continuation. Best for confirming trend direction. How the Detection Works Engulfing Pattern: bool engulfBullBase = open <= math.min(close , open ) and close >= math.max(close , open ) and isBullish(0) and getBodyPct(0) > bodyMinPct Kicker Pattern: bool kickerBull = isBearish(1) and isBullish(0) and open > open and low > low and getBodyPct(0) > 40 and getBodyPct(1) > 40 Inside Bar: bool insideBarSetup = low < low and high > high bool insideBarBull = insideBarSetup and isBullish(0) HH/HL Sequence: bool hhhlSeq = high > high and low > low and high > high and low > low and close > close Optional Filters ATR Filter - Only shows patterns where candle body exceeds ATR (strong candles only) Body Minimum % - Requires minimum body percentage for engulfing patterns Close Beyond Prior H/L - Requires engulfing candle to close beyond prior high/low Dashboard Information Engulfing - Total engulfing patterns detected Kicker - Kicker pattern count Inside Bar - Inside bar breakout count HH/LL Seq - Structure sequence count Total - Combined pattern count How to Use This Indicator For Reversal Trading: 1. Look for engulfing or kicker patterns at key support/resistance 2. Confirm with HH/HL or LH/LL sequence breaking 3. Enter with stop beyond the pattern For Breakout Trading: 1. Identify inside bar setups (consolidation) 2. Enter on breakout candle in direction of break 3. Use the inside bar range for stop placement For Trend Confirmation: 1. Use HH/HL sequences to confirm uptrend structure 2. Use LH/LL sequences to confirm downtrend structure 3. Momentum candles indicate institutional participation Input Parameters Detect Engulfing/Kicker/Inside Bar/Momentum/HHLL (all true) - Toggle each pattern type Min Body % for Engulfing (0) - Minimum body percentage ATR Filter (false) - Only show strong candles Engulf Must Close Beyond Prior H/L (true) - Stricter engulfing definition Compact Mode (false) - Shorter labels for cleaner charts Timeframe Recommendations 1H-Daily: Best for reliable pattern detection 15m-30m: More patterns but higher noise Use Compact Mode on lower timeframes Limitations Pattern detection is mechanical and does not consider context Not all patterns lead to successful trades Kicker patterns are rare but powerful Inside bar breakouts can fail (false breakouts) Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Pattern detection does not guarantee trade outcomes. Always use proper risk management. - Made with passion by officialjackofalltrades
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Pulse Volume Commitment [JOAT] Pulse Volume Commitment - Three-Dimensional Momentum Analysis Introduction and Purpose Pulse Volume Commitment is an open-source oscillator indicator that analyzes price action through three distinct dimensions: Quantity (candle count), Quality (body structure), and Commitment (volume-weighted quality). The core problem this indicator solves is that simple bullish/bearish candle counts miss important context. A market can have more green candles but still be weak if those candles have small bodies and low volume. This indicator addresses that by requiring all three dimensions to align before generating strong signals, filtering out weak moves that lack conviction. Why These Three Dimensions Work Together Each dimension measures a different aspect of market conviction: 1. Quantity - Counts bullish vs bearish candles over the lookback period. Tells you WHO is winning the candle count battle. 2. Quality - Scores candles by body size relative to total range. Full-bodied candles (small wicks) indicate stronger conviction than doji-like candles. Tells you HOW decisively price is moving. 3. Commitment - Weights quality scores by volume. High-quality candles on high volume indicate institutional participation. Tells you WHETHER smart money is involved. When all three align (e.g., more bullish candles + bullish quality + bullish commitment), the signal is significantly more reliable. How the Calculations Work Quantity Analysis: int greenCount = 0 int redCount = 0 for i = 0 to lookbackPeriod - 1 if close > open greenCount += 1 if close < open redCount += 1 bool quantityBull = greenCount > redCount Quality Analysis (body-to-range scoring): for i = 0 to lookbackPeriod - 1 float candleBody = close - open // Signed (positive = bull) float candleRange = high - low float bodyQuality = candleRange > 0 ? (candleBody / candleRange * 100) * candleRange : 0.0 sumBodyQuality += bodyQuality bool qualityBull = sumBodyQuality > 0 Signal Types FULL BULL - All three dimensions bullish (Quantity + Quality + Commitment) FULL BEAR - All three dimensions bearish LEAN BULL/BEAR - 2 of 3 dimensions agree MIXED - No clear consensus STRONG BUY/SELL - Full confluence + ADX confirms trending market ADX Integration The indicator includes ADX (Average Directional Index) to filter signals: - ADX >= 20 = TRENDING market (signals more reliable) - ADX < 20 = RANGING market (signals may whipsaw) Strong signals only trigger when full confluence occurs in a trending environment. Dashboard Information Quantity - BULL/BEAR/FLAT with green/red candle ratio Quality - Directional bias based on body quality scoring Commit - Volume-weighted commitment reading ADX - Trend strength (TRENDING/RANGING) Signal - Confluence status (FULL BULL/FULL BEAR/LEAN/MIXED) Action - STRONG BUY/STRONG SELL/WAIT How to Use This Indicator For High-Conviction Entries: 1. Wait for FULL BULL or FULL BEAR confluence 2. Confirm ADX shows TRENDING 3. Enter when Action shows STRONG BUY or STRONG SELL For Filtering Weak Setups: 1. Avoid entries when signal shows MIXED 2. Be cautious when ADX shows RANGING 3. Require at least 2 of 3 dimensions to agree For Divergence Analysis: 1. Watch for Quantity bullish but Commitment bearish (distribution) 2. Watch for Quantity bearish but Commitment bullish (accumulation) Input Parameters Lookback Period (9) - Bars to analyze for all three dimensions ADX Smoothing (14) - Period for ADX calculation ADX DI Length (14) - Period for directional indicators Timeframe Recommendations 15m-1H: Good for intraday momentum analysis 4H-Daily: Best for swing trading confluence Lookback period may need adjustment for different timeframes Limitations Lookback period affects signal responsiveness vs reliability tradeoff Volume data quality varies by exchange ADX filter may cause missed entries in early trends Works best on liquid instruments with consistent volume Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Confluence signals do not guarantee profitable trades. Always use proper risk management. - Made with passion by officialjackofalltrades
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Prism Band Dynamics [JOAT]Prism Band Dynamics - Bollinger-Style Bands with Force Detection Introduction and Purpose Prism Band Dynamics is an open-source overlay indicator that creates dynamic Bollinger-style bands with an innovative "force detection" system. The core problem this indicator solves is that standard Bollinger Bands show volatility but don't indicate directional momentum. When all three band components (upper, lower, basis) move in the same direction, it indicates strong directional force that standard bands don't highlight. This indicator addresses that by detecting when all band components align directionally, providing a clear signal of market force. Why Force Detection Matters Standard Bollinger Bands expand and contract based on volatility, but they don't tell you about directional momentum. Force detection adds this dimension: 1. Bullish Force - Upper band, lower band, AND basis all moving up together. This indicates strong upward momentum where even the lower support level is rising. 2. Bearish Force - Upper band, lower band, AND basis all moving down together. This indicates strong downward momentum where even the upper resistance level is falling. 3. Neutral - Mixed movement indicates consolidation or uncertainty. How Force Detection Works bool upperUp = upper > upper bool lowerUp = lower > lower bool basisUp = basis > basis int forceFull = if upperUp and lowerUp and basisUp 1 // Bullish force else if upperDn and lowerDn and basisDn -1 // Bearish force else 0 // Neutral Additional Features Squeeze Detection - Identifies when band width contracts below threshold, often preceding large moves Gradient Fills - Color intensity reflects force strength Direction Change Arrows - Visual markers when force direction shifts Dashboard Information Force - Current force status (BULLISH/BEARISH/NEUTRAL) Position - Price location within bands (Upper/Mid/Lower Zone) Band Width - Current width percentage with expansion/contraction label Volatility - Squeeze status (SQUEEZE/NORMAL) Force Count - Bars since last force change How to Use This Indicator For Trend Following: 1. Enter long when force turns BULLISH 2. Enter short when force turns BEARISH 3. Exit or reduce when force turns NEUTRAL For Squeeze Breakouts: 1. Watch for SQUEEZE status in dashboard 2. Prepare for breakout in either direction 3. Enter when force confirms direction after squeeze For Mean Reversion: 1. Only trade mean-reversion when force is NEUTRAL 2. Avoid fading moves when force is active 3. Use band touches as entry points during neutral force Input Parameters Length (20) - Period for basis and standard deviation Multiplier (2.0) - Standard deviation multiplier for bands MA Type (SMA) - Basis calculation method Squeeze Threshold (0.5) - Band width percentage for squeeze detection Timeframe Recommendations 4H-Daily: Cleanest force signals 1H: Good balance of signals and reliability 15m: More signals but more noise Limitations Force detection can lag during rapid reversals Squeeze breakouts can fail (false breakouts) Works best in markets with clear trending/ranging phases Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Force detection does not guarantee trend continuation. Always use proper risk management. - Made with passion by officialjackofalltrades
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Fractal Wave Hunter [JOAT] Fractal Wave Hunter - Multi-Method Fractal Detection System Introduction and Purpose Fractal Wave Hunter is an open-source overlay indicator that identifies key reversal patterns using multiple fractal detection methods. The core problem this indicator solves is that different fractal methods catch different types of reversals. Williams' classic 5-bar fractal is reliable but slow; Hougaard's 4-bar method is faster but noisier. Using only one method means missing valid signals that the other would catch. This indicator addresses that by combining both methods plus HOLP/LOHP detection, giving traders a comprehensive view of potential reversal points. Why These Methods Work Together Each fractal method has different characteristics: 1. 4-Bar Fractal (Hougaard Method) - Faster detection, identifies momentum shifts when close exceeds recent highs/lows. Best for catching early reversals. 2. Classic 5-Bar Fractal (Williams) - Traditional pivot detection requiring the middle bar to be the highest/lowest of 5 bars. Best for identifying significant swing points. 3. HOLP/LOHP - High of Low Period and Low of High Period signals identify when price makes a new extreme within a defined lookback. Best for trend exhaustion detection. By combining these methods, traders can: Use 4-bar fractals for early entry signals Use 5-bar fractals for confirmation and stop placement Use HOLP/LOHP for trend exhaustion warnings How the Detection Works 4-Bar Fractal (Hougaard): bool fractal4BuyBase = close > high and close > high bool fractal4SellBase = close < low and close < low Classic 5-Bar Fractal: bool fractalHigh = high > high and high > high and high > high and high > high bool fractalLow = low < low and low < low and low < low and low < low Signal Types 4B (4-Bar Buy) - Close exceeds high and high - early bullish signal 4S (4-Bar Sell) - Close below low and low - early bearish signal FH (Fractal High) - Classic 5-bar swing high - confirmed resistance FL (Fractal Low) - Classic 5-bar swing low - confirmed support HOLP - High of low period - potential bullish exhaustion LOHP - Low of high period - potential bearish exhaustion Dashboard Information 4-Bar Fractal - Count of bullish/bearish 4-bar fractals Classic Fractal - Count of 5-bar fractal highs/lows HOLP/LOHP - Reversal signal counts Total Signals - Combined pattern count How to Use This Indicator For Counter-Trend Entries: 1. Wait for 4-bar fractal signal at key support/resistance 2. Confirm with 5-bar fractal forming nearby 3. Enter with stop beyond the fractal point For Stop Placement: 1. Use 5-bar fractal highs/lows as stop-loss references 2. These represent confirmed swing points that should hold if trend continues For Trend Analysis: 1. Track swing structure using fractal highs and lows 2. Higher fractal lows = uptrend structure 3. Lower fractal highs = downtrend structure Input Parameters Show 4-Bar Fractals (true) - Toggle Hougaard method signals Show Classic Fractals (true) - Toggle Williams method signals Show HOLP/LOHP (true) - Toggle exhaustion signals ATR Filter (false) - Only show signals during volatile conditions Swing Lines (true) - Connect significant swing points Timeframe Recommendations 1H-Daily: Best for reliable fractal detection 15m-30m: More signals but higher noise Weekly: Fewer but more significant fractals Limitations 5-bar fractals have inherent 2-bar lag (need confirmation) 4-bar fractals can produce false signals in choppy markets HOLP/LOHP signals work best at trend extremes Not all fractals lead to significant reversals Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Fractal detection does not guarantee reversals. Always use proper risk management. - Made with passion by officialjackofalltrades
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Eclipse Multi-Oscillator [JOAT]Eclipse Multi-Oscillator - Unified Momentum Confluence System Introduction and Purpose Eclipse Multi-Oscillator is an open-source indicator that combines four classic oscillators (RSI, Stochastic, CCI, and Williams %R) into a single unified view with confluence detection. The core problem this indicator solves is oscillator disagreement: traders often see RSI oversold while Stochastic is neutral, or CCI overbought while Williams %R is mid-range. This creates confusion about the true momentum state. This indicator addresses that by displaying all four oscillators together and counting how many agree on overbought or oversold conditions, providing a clear confluence score that cuts through the noise. Why These Four Oscillators Work Together Each oscillator measures momentum differently, and their combination provides a more complete picture: 1. RSI (Relative Strength Index) - Measures the magnitude of recent price changes. Best at identifying momentum exhaustion. 2. Stochastic - Compares closing price to the high-low range. Best at identifying where price is within its recent range. 3. CCI (Commodity Channel Index) - Measures price deviation from statistical mean. Best at identifying unusual price movements. 4. Williams %R - Similar to Stochastic but inverted. Provides confirmation of Stochastic readings. When 3 or more of these oscillators agree on overbought or oversold, the signal is significantly more reliable than any single oscillator alone. How Confluence Scoring Works The indicator counts how many oscillators are in extreme territory: int obCount = 0 if rsi > rsiOB obCount += 1 if stochK > stochOB obCount += 1 if cci > cciOB obCount += 1 if willRScaled > stochOB obCount += 1 bool strongOverbought = obCount >= 3 bool strongOversold = osCount >= 3 The confluence score ranges from -4 (all oversold) to +4 (all overbought), with 0 being neutral. Signal Types Strong Oversold - 3+ oscillators below oversold threshold (potential bounce) Strong Overbought - 3+ oscillators above overbought threshold (potential pullback) OB/OS Exit - RSI leaving extreme zone with Stochastic confirmation (potential reversal) Divergence - Price makes new high/low while RSI does not (potential reversal warning) Dashboard Information RSI/Stoch K/CCI/Will %R - Current values with zone status (OB/OS/MID) Confluence - Overall bias (STRONG OS, STRONG OB, Lean Bull/Bear, Neutral) OB Count - How many oscillators are overbought (0-4) OS Count - How many oscillators are oversold (0-4) How to Use This Indicator For Reversal Trading: 1. Wait for Strong Oversold (3+ oscillators agree) 2. Look for bullish candlestick pattern or support level 3. Enter long with stop below recent low 4. Take profit when confluence returns to neutral or overbought For Trend Confirmation: 1. Check confluence direction matches your trade bias 2. Avoid longs when confluence is strongly overbought 3. Avoid shorts when confluence is strongly oversold For Divergence Trading: 1. Watch for "D" labels indicating RSI divergence 2. Bullish divergence at support = potential long 3. Bearish divergence at resistance = potential short Input Parameters RSI Length (14) - Period for RSI calculation Stochastic K/D Length (14/3) - Periods for Stochastic CCI Length (20) - Period for CCI Williams %R Length (14) - Period for Williams %R OB/OS Thresholds - Customizable levels for each oscillator Timeframe Recommendations 15m-1H: Good for intraday momentum analysis 4H-Daily: Best for swing trading confluence Very short timeframes may produce noisy signals Limitations All oscillators can remain in extreme territory during strong trends Confluence does not predict direction, only identifies extremes Divergence detection is simplified and may miss some patterns Works best in ranging or moderately trending markets Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied. This indicator does not constitute financial advice. Oscillator confluence does not guarantee reversals. Past performance does not guarantee future results. Always use proper risk management. - Made with passion by officialjackofalltrades
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Aurora Volatility Bands [JOAT]Aurora Volatility Bands - Dynamic ATR-Based Envelope System Introduction and Purpose Aurora Volatility Bands is an open-source overlay indicator that creates multi-layered volatility envelopes around price using ATR (Average True Range) calculations. The core problem this indicator solves is that static bands (like fixed percentage envelopes) fail to adapt to changing market conditions. During high volatility, static bands are too tight; during low volatility, they're too wide. This indicator addresses that by using ATR-based dynamic bands that automatically expand during volatile periods and contract during quiet periods, providing contextually appropriate support/resistance levels at all times. Why These Components Work Together The indicator combines three analytical approaches: 1. Triple-Layer Band System - Inner (1x ATR), Outer (2x ATR), and Extreme (3x ATR) bands provide graduated levels of significance 2. Volatility State Detection - Compares current ATR to historical average to classify market regime 3. Multiple MA Types - Allows customization of the center line calculation method These components complement each other: The triple-layer system gives traders multiple reference points - inner bands for normal moves, outer for significant moves, extreme for rare events Volatility state detection tells you WHEN bands are expanding or contracting, helping anticipate breakouts or mean-reversion MA type selection lets you match the indicator to your trading style (faster EMA vs smoother SMA) How the Calculation Works The bands are calculated using ATR multiplied by configurable factors: float atr = ta.atr(atrPeriod) float innerUpper = centerMA + (atr * innerMult) float outerUpper = centerMA + (atr * outerMult) float extremeUpper = centerMA + (atr * extremeMult) Volatility state is determined by comparing current ATR percentage to its historical average: float atrPercent = (atr / close) * 100 float avgAtrPercent = ta.sma(atrPercent, volatilityLookback) float volatilityRatio = atrPercent / avgAtrPercent bool isExpanding = volatilityRatio > 1.2 // 20%+ above average bool isContracting = volatilityRatio < 0.8 // 20%+ below average Signal Types Band Touch - Price reaches inner, outer, or extreme bands Mean Reversion - Price returns to center after touching outer/extreme bands Breakout - Sustained move beyond outer bands during volatility expansion Dashboard Information Volatility - Current state (EXPANDING/CONTRACTING/NORMAL) Vol Ratio - Current volatility vs average (e.g., 1.5x = 50% above average) ATR - Current ATR value ATR % - ATR as percentage of price Zone - Current price position (EXTREME HIGH/UPPER ZONE/CENTER ZONE/etc.) Position - Price position as percentage within band structure Width - Total band width as percentage of price Using SMA in settings: How to Use This Indicator For Mean-Reversion Trading: 1. Wait for price to touch outer or extreme bands 2. Check that volatility state is NORMAL or CONTRACTING (not expanding) 3. Look for reversal candlestick patterns at the band 4. Enter toward center MA with stop beyond the band For Breakout Trading: 1. Wait for volatility state to show EXPANDING 2. Look for price closing beyond outer bands 3. Enter in direction of breakout 4. Use the band as trailing stop reference For Volatility Analysis: 1. Monitor volatility ratio for regime changes 2. CONTRACTING often precedes large moves (squeeze) 3. EXPANDING confirms trend strength Using VWMA and Mean Reversion Signal/MR: Input Parameters ATR Period (14) - Period for ATR calculation Inner/Outer/Extreme Multipliers (1.0/2.0/3.0) - Band distance from center MA Type (EMA) - Center line calculation method MA Period (20) - Period for center line Volatility Comparison Period (20) - Lookback for volatility state Timeframe Recommendations 15m-1H: Good for intraday mean-reversion 4H-Daily: Best for swing trading and breakout identification Weekly: Useful for position trading and major level identification Limitations ATR-based bands lag during sudden volatility spikes Mean-reversion signals can fail in strong trends Breakout signals may whipsaw in ranging markets Works best on liquid instruments with consistent volatility patterns Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each component works. This indicator does not constitute financial advice. Band touches do not guarantee reversals. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses. - Made with passion by officialjackofalltrades
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Final Project Midpoint Package (4H / D / W) Layer 1This script runs based off of the higher timeframe candlesticks. (4HR and Daily) This strategy is simple and is based on your logic as well. I personally use all 5 strategies on one chart however those are being tested. As soon as you get it you will see allot on the screen , just open the setting and turn off the extra bands from the 4HR and the Daily. Fix your settings however you seem fit . Once the others are finished testing i will release those also. Will be adding updates as it progresses.
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Quantum Reversal Detector [JOAT] Quantum Reversal Detector - Multi-Factor Reversal Probability Analysis Introduction and Purpose Quantum Reversal Detector is an open-source overlay indicator that combines multiple reversal detection methods into a unified probability-based framework. The core problem this indicator addresses is the unreliability of single-factor reversal signals. A price touching support means nothing without momentum confirmation; an RSI oversold reading means nothing without price structure context. This indicator solves that by requiring multiple independent factors to align before generating reversal signals, then expressing the result as a probability score rather than a binary signal. Why These Components Work Together The indicator combines five analytical approaches, each addressing a different aspect of reversal detection: 1. RSI Extremes - Identifies momentum exhaustion (overbought/oversold) 2. MACD Crossovers - Confirms momentum direction change 3. Support/Resistance Proximity - Ensures price is at a significant level 4. Multi-Depth Momentum - Analyzes momentum across multiple timeframes 5. Statistical Probability - Quantifies reversal likelihood using Bayesian updating These components are not randomly combined. Each filter catches reversals that others miss: RSI catches momentum exhaustion but misses structural reversals MACD catches momentum shifts but lags price action S/R proximity catches structural levels but ignores momentum Multi-depth momentum catches divergences across timeframes Probability scoring combines all factors into actionable confidence levels How the Detection System Works Step 1: Pattern Detection The indicator first identifies potential reversal conditions: // Check if price is at support/resistance float lowestLow = ta.lowest(low, period) float highestHigh = ta.highest(high, period) bool atSupport = low <= lowestLow * 1.002 bool atResistance = high >= highestHigh * 0.998 // Check RSI conditions float rsi = ta.rsi(close, 14) bool oversold = rsi < 30 bool overbought = rsi > 70 // Check MACD crossover float macd = ta.ema(close, 12) - ta.ema(close, 26) float signal = ta.ema(macd, 9) bool macdBullish = ta.crossover(macd, signal) bool macdBearish = ta.crossunder(macd, signal) // Combine for reversal detection if atSupport and oversold and macdBullish bullishReversal := true Step 2: Multi-Depth Momentum Analysis The indicator calculates momentum across multiple periods to detect divergences: calculateQuantumMomentum(series float price, simple int period, simple int depth) => float totalMomentum = 0.0 for i = 0 to depth - 1 int currentPeriod = period * (i + 1) float momentum = ta.roc(price, currentPeriod) totalMomentum += momentum totalMomentum / depth This creates a composite momentum reading that smooths out noise while preserving genuine momentum shifts. Step 3: Bayesian Probability Calculation The indicator uses Bayesian updating to calculate reversal probability: bayesianProbability(series float priorProb, series float likelihood, series float evidence) => float posterior = evidence > 0 ? (likelihood * priorProb) / evidence : priorProb math.min(math.max(posterior, 0.0), 1.0) The prior probability starts at 50% and updates based on: RSI extreme readings increase likelihood MACD crossovers increase likelihood S/R proximity increases likelihood Momentum divergence increases likelihood Step 4: Confidence Intervals Using Monte Carlo simulation concepts, the indicator estimates price distribution: monteCarloSimulation(series float price, series float volatility, simple int iterations) => float sumPrice = 0.0 float sumSqDiff = 0.0 for i = 0 to iterations - 1 float randomFactor = (i % 10 - 5) / 10.0 float simulatedPrice = price + volatility * randomFactor sumPrice += simulatedPrice float avgPrice = sumPrice / iterations // Calculate standard deviation for confidence intervals This provides 95% and 99% confidence bands around the current price. Signal Classification Signals are classified by confirmation level: Confirmed Reversal : Pattern detected for N consecutive bars (default 3) High Probability : Confirmed + Bayesian probability > 70% Ultra High Probability : High probability + PDF above average Dashboard Information The dashboard displays: Bayesian Probability - Updated reversal probability (0-100%) Quantum Momentum - Multi-depth momentum average RSI - Current RSI value with overbought/oversold status Volatility - Current ATR as percentage of price Reversal Signal - BULLISH, BEARISH, or NONE Divergence - Momentum divergence detection MACD - Current MACD histogram value S/R Zone - AT SUPPORT, AT RESISTANCE, or NEUTRAL 95% Confidence - Price range with 95% probability Bull/Bear Targets - ATR-based reversal targets Visual Elements Quantum Bands - ATR-based upper and lower channels Probability Field - Circle layers showing probability distribution Confidence Bands - 95% and 99% confidence interval circles Reversal Labels - REV markers at confirmed reversals High Probability Markers - Star diamonds at high probability setups Reversal Zones - Boxes around confirmed reversal areas Divergence Markers - Triangles at momentum divergences How to Use This Indicator For Reversal Trading: 1. Wait for Bayesian Probability to exceed 70% 2. Confirm price is at S/R zone (dashboard shows AT SUPPORT or AT RESISTANCE) 3. Check that RSI is in extreme territory (oversold for longs, overbought for shorts) 4. Enter when REV label appears with high probability marker For Risk Management: 1. Use the 95% confidence band as a stop-loss reference 2. Use Bull/Bear Targets for take-profit levels 3. Higher probability readings warrant larger position sizes For Filtering False Signals: 1. Increase Confirmation Bars to require more consecutive signals 2. Only trade when probability exceeds 70% 3. Require divergence confirmation for highest conviction Input Parameters Reversal Period (21) - Lookback for S/R and momentum calculations Quantum Depth (5) - Number of momentum layers for multi-depth analysis Confirmation Bars (3) - Consecutive bars required for confirmation Detection Sensitivity (1.2) - Band width and target multiplier Bayesian Probability (true) - Enable probability calculation Monte Carlo Simulation (true) - Enable confidence interval calculation Normal Distribution (true) - Enable PDF calculation Confidence Intervals (true) - Enable confidence bands Timeframe Recommendations 1H-4H: Best for swing trading reversals Daily: Fewer but more significant reversal signals 15m-30m: More signals, requires higher probability threshold Limitations Statistical concepts are simplified implementations for Pine Script Monte Carlo uses deterministic pseudo-random factors, not true randomness Bayesian probability uses simplified prior/likelihood model Reversal detection does not guarantee actual reversals will occur Confirmation bars add lag to signal generation Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each component works. This indicator does not constitute financial advice. Reversal detection is probabilistic, not predictive. The probability scores represent statistical likelihood based on historical patterns, not guaranteed outcomes. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses. - Made with passion by officialjackofalltrades
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Photon Price Action Scanner [JOAT]Photon Price Action Scanner - Multi-Pattern Recognition with Adaptive Filtering Introduction and Purpose Photon Price Action Scanner is an open-source overlay indicator that automates the detection of 15+ candlestick patterns while filtering them through multiple confirmation layers. The core problem this indicator solves is pattern noise: raw candlestick pattern detection produces too many signals, most of which fail because they lack context. This indicator addresses that by combining pattern recognition with trend alignment, volume-weighted strength scoring, velocity confirmation, and an adaptive neural bias filter. The combination of these components is not arbitrary. Each filter addresses a specific weakness in standalone pattern detection: Trend alignment ensures patterns appear in favorable market structure Volume-weighted strength filters out weak patterns with low conviction Velocity confirmation identifies momentum behind the pattern Neural bias filter adapts to recent price behavior to avoid counter-trend signals What Makes This Indicator Original While candlestick pattern scanners exist, this indicator's originality comes from: 1. Multi-Layer Filtering System - Patterns must pass through trend, strength, velocity, and neural bias filters before generating signals. This dramatically reduces false positives compared to simple pattern detection. 2. Adaptive Neural Bias Filter - A custom momentum-adjusted EMA that learns from recent price action using a configurable learning rate. This is not a standard moving average but an adaptive filter that accelerates during trends and smooths during consolidation. 3. Pattern Strength Scoring - Each pattern receives a strength score based on volume ratio and body size, allowing traders to focus on high-conviction setups rather than every pattern occurrence. 4. Smart Cooldown System - Prevents signal overlap by enforcing minimum bar spacing between pattern labels, keeping charts clean even when "Show All Patterns" is enabled. How the Components Work Together Step 1: Pattern Detection The indicator scans for 15 candlestick patterns using precise mathematical definitions: // Example: Bullish Engulfing requires the current bullish candle to completely // engulf the previous bearish candle with a larger body isBullishEngulfing() => bool pattern = close < open and close > open and open <= close and close >= open and close - open > open - close pattern // Example: Three White Soldiers requires three consecutive bullish candles // with each opening within the previous body and closing higher isThreeWhiteSoldiers() => bool pattern = close > open and close > open and close > open and close < close and close < close and open > open and open < close and open > open and open < close pattern Step 2: Strength Calculation Each detected pattern receives a strength score combining volume and body size: float volRatio = avgVolume > 0 ? volume / avgVolume : 1.0 float bodySize = math.abs(close - open) / close float baseStrength = (volRatio + bodySize * 100) / 2 This ensures patterns with above-average volume and large bodies score higher than weak patterns on low volume. Step 3: Trend Alignment Patterns are checked against the trend direction using an EMA: float trendEMA = ta.ema(close, i_trendPeriod) int trendDir = close > trendEMA ? 1 : close < trendEMA ? -1 : 0 Bullish patterns in uptrends and bearish patterns in downtrends receive priority. Step 4: Neural Bias Filter The adaptive filter uses a momentum-adjusted EMA that responds to price changes: neuralEMA(series float src, simple int period, simple float lr) => var float neuralValue = na var float momentum = 0.0 if na(neuralValue) neuralValue := src float error = src - neuralValue float adjustment = error * lr momentum := momentum * 0.9 + adjustment * 0.1 neuralValue := neuralValue + adjustment + momentum neuralValue The learning rate (lr) controls how quickly the filter adapts. Higher values make it more responsive; lower values make it smoother. Step 5: Velocity Confirmation Price velocity (rate of change) must exceed the average velocity for strong signals: float velocity = ta.roc(close, i_trendPeriod) float avgVelocity = ta.sma(velocity, i_trendPeriod) bool velocityBull = velocity > avgVelocity * 1.5 Step 6: Signal Classification Signals are classified based on how many filters they pass: Strong Pattern : Pattern + strength threshold + trend alignment + neural bias + velocity Ultra Pattern : Strong pattern + gap in same direction + velocity confirmation Watch Pattern : Pattern detected but not all filters passed Detected Patterns Classic Reversal Patterns: Bullish/Bearish Engulfing - Complete body engulfment with larger body Hammer - Long lower wick (2x body), small upper wick, bullish context Shooting Star - Long upper wick (2x body), small lower wick, bearish context Morning Star - Three-bar bullish reversal with small middle body Evening Star - Three-bar bearish reversal with small middle body Piercing Line - Bullish candle closing above midpoint of previous bearish candle Dark Cloud Cover - Bearish candle closing below midpoint of previous bullish candle Bullish/Bearish Harami - Small body contained within previous larger body Doji - Body less than 10% of total range (indecision) Advanced Patterns (Optional): Three White Soldiers - Three consecutive bullish candles with rising closes Three Black Crows - Three consecutive bearish candles with falling closes Tweezer Top - Equal highs with reversal candle structure Tweezer Bottom - Equal lows with reversal candle structure Island Reversal - Gap isolation creating reversal structure Dashboard Information The dashboard displays real-time analysis: Pattern - Current detected pattern name or "SCANNING..." Bull/Bear Strength - Volume-weighted strength scores Trend - UPTREND, DOWNTREND, or SIDEWAYS based on EMA RSI - 14-period RSI for momentum context Momentum - 10-period momentum reading Volatility - ATR as percentage of price Neural Bias - BULLISH, BEARISH, or NEUTRAL from adaptive filter Action - ULTRA BUY/SELL, BUY/SELL, WATCH BUY/SELL, or WAIT Visual Elements Pattern Labels - Abbreviated codes (BE=Engulfing, H=Hammer, MS=Morning Star, etc.) Neural Bias Line - Adaptive trend line showing filter direction Gap Boxes - Cyan boxes highlighting price gaps Action Zones - Dashed boxes around strong pattern areas Velocity Markers - Small circles when velocity confirms direction Ultra Signals - Large labels for highest conviction setups How to Use This Indicator For Reversal Trading: 1. Wait for a pattern to appear at a key support/resistance level 2. Check that the Action shows "BUY" or "SELL" (not just "WATCH") 3. Confirm the Neural Bias aligns with your trade direction 4. Use the strength score to gauge conviction (higher is better) For Trend Continuation: 1. Identify the trend using the Trend row in the dashboard 2. Look for patterns that align with the trend (bullish patterns in uptrends) 3. Ultra signals indicate the strongest continuation setups For Filtering Noise: 1. Keep "Show All Patterns" disabled to see only filtered signals 2. Increase "Pattern Strength Filter" to see fewer, higher-quality patterns 3. Enable "Velocity Confirmation" to require momentum behind patterns Input Parameters Scan Sensitivity (1.0) - Overall detection sensitivity multiplier Pattern Strength Filter (3) - Minimum strength score for strong signals Trend Period (20) - EMA period for trend determination Show All Patterns (false) - Display all patterns regardless of filters Advanced Patterns (true) - Enable soldiers/crows/tweezer detection Gap Analysis (true) - Enable gap detection and boxes Velocity Confirmation (true) - Require velocity for strong signals Neural Bias Filter (true) - Enable adaptive trend filter Neural Period (50) - Lookback for neural bias calculation Neural Learning Rate (0.12) - Adaptation speed (0.01-0.5) Timeframe Recommendations 1H-4H: Best balance of signal frequency and reliability Daily: Fewer but more significant patterns 15m-30m: More signals, requires tighter filtering (increase strength threshold) Limitations Pattern detection is mechanical and does not consider fundamental context Neural bias filter may lag during rapid trend reversals Gap detection requires clean price data without after-hours gaps Strength scoring favors high-volume patterns, which may miss valid low-volume setups - Made with passion by officialjackofalltrades
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3
Dual Account Position Size CalculatorA quick and easy to use position sizing calculator for use on the daily TF only. inputs for two different account sizes and risk %. Calculates risk to low of day (plus a small buffer which can be changed based on ATR). Shows # of shares to buy, stop loss, portfolio %. Will show on smaller timeframes , but be aware that the stop level will no longer be low of day, so it will not calculate properly. Always use on the daily.
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Bifurcation Early WarningBifurcation Early Warning (BEW) — Chaos Theory Regime Detection OVERVIEW The Bifurcation Early Warning indicator applies principles from chaos theory and complex systems research to detect when markets are approaching critical transition points — moments where the current regime is likely to break down and shift to a new state. Unlike momentum or trend indicators that tell you what is happening, BEW tells you when something is about to change. It provides early warning of regime shifts before they occur, giving traders time to prepare for increased volatility or trend reversals. THE SCIENCE BEHIND IT In complex systems (weather, ecosystems, financial markets), major transitions don't happen randomly. Research has identified three universal warning signals that precede critical transitions: 1. Critical Slowing Down As a system approaches a tipping point, it becomes "sluggish" — small perturbations take longer to decay. In markets, this manifests as rising autocorrelation in returns. 2. Variance Amplification Short-term volatility begins expanding relative to longer-term baselines as the system destabilizes. 3. Flickering The system oscillates between two potential states before committing to one — visible as increased crossing of mean levels. BEW combines all three signals into a single composite score. COMPONENTS AR(1) Coefficient — Critical Slowing Down (Blue) Measures lag-1 autocorrelation of returns over a rolling window. • Rising toward 1.0: Market becoming "sticky," slow to mean-revert — transition approaching • Low values (<0.3): Normal mean-reverting behavior, stable regime Variance Ratio (Purple) Compares short-term variance to long-term variance. • Above 1.5: Short-term volatility expanding — energy building before a move • Near 1.0: Volatility stable, no unusual pressure Flicker Count (Yellow/Teal) Counts state changes (crossings of the dynamic mean) within the lookback period. • High count: Market oscillating between states — indecision before commitment • Low count: Price firmly in one regime INTERPRETING THE BEW SCORE 0–50 (STABLE): Normal market conditions. Existing strategies should perform as expected. 50–70 (WARNING): Elevated instability detected. Consider reducing exposure or tightening risk parameters. 70–85 (DANGER): High probability of regime change. Avoid initiating new positions; widen stops on existing ones. 85+ (CRITICAL): Bifurcation likely imminent or in progress. Expect large, potentially unpredictable moves. HOW TO USE As a Regime Filter • BEW < 50: Normal trading conditions — apply your standard strategies • BEW > 60: Elevated caution — reduce position sizes, avoid mean-reversion plays • BEW > 80: High alert — consider staying flat or hedging existing positions As a Preparation Signal BEW tells you when to pay attention, not which direction. When readings elevate: • Watch for confirmation from volume, order flow, or other directional indicators • Prepare for breakout scenarios in either direction • Adjust take-profit and stop-loss distances for larger moves For Volatility Adjustment High BEW periods correlate with larger candles. Use this to: • Widen stops during elevated readings • Adjust position sizing inversely to BEW score • Set more ambitious profit targets when entering during high-BEW breakouts Divergence Analysis • Price making new highs/lows while BEW stays low: Trend likely to continue smoothly • Price consolidating while BEW rises: Breakout incoming — direction uncertain but move will be significant SETTINGS GUIDE Core Settings • Lookback Period: General reference period (default: 50) • Source: Price source for calculations (default: close) Critical Slowing Down (AR1) • AR(1) Calculation Period: Bars used for autocorrelation (default: 100). Higher = smoother, slower. • AR(1) Warning Threshold: Level at which AR(1) is considered elevated (default: 0.85) Variance Growth • Variance Short Period: Fast variance window (default: 20) • Variance Long Period: Slow variance window (default: 100) • Variance Ratio Threshold: Level for maximum score contribution (default: 1.5) Regime Flickering • Flicker Detection Period: Window for counting state changes (default: 20) • Flicker Bandwidth: ATR multiplier for state detection — lower = more sensitive (default: 0.5) • Flicker Count Threshold: Number of crossings for maximum score (default: 4) TIMEFRAME RECOMMENDATIONS • 5m–15m: Use shorter periods (AR: 30–50, Var: 10/50). Expect more noise. • 1H: Balanced performance with default or slightly extended settings (AR: 100, Var: 20/100). • 4H–Daily: Extend periods further (AR: 100–150, Var: 30/150). Cleaner signals, less frequent. ALERTS Three alert conditions are included: • BEW Warning: Score crosses above 50 • BEW Danger: Score crosses above 70 • BEW Critical: Score crosses above 85 LIMITATIONS • No directional bias: BEW detects instability, not direction. Combine with trend or momentum indicators. • Not a timing tool: Elevated readings may persist for several bars before the actual move. • Parameter sensitive: Optimal settings vary by asset and timeframe. Backtest before live use. • Leading indicator trade-off: Early warning means some false positives are inevitable. CREDITS Inspired by research on early warning signals in complex systems: • Dakos et al. (2012) — "Methods for detecting early warnings of critical transitions" DISCLAIMER This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always conduct your own analysis and risk management. Use at your own risk.
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CryptoForMoney tarafından
Volume Based Ranges (VBR) [SS]Here is the Volume Based Ranges or VBR indicator. How it works The indicator works by: Sorting volume into buying and selling volume, then Calculating 2 independent Z-Scores for buying and selling data, then Identifying the high buying and selling nodes through the use of the Z-score threshold. Tracks the average target/move based on buying and selling nodes over a designated lookforward horizon (i.e. if you want to see the average move a high selling node happens over 20 candles, you can modify the lookforward horizon to 20). Calculates the composition from each volume node, displaying the composition information on each line (the % of buying and selling each node contains). How to Use it To use this indicator: Select the Z-Score length of assessment: By default, z-score is 75 and this is usually fine to leave. Identify the threshold trigger: This will need to be adjusted based on your timeframe. If you are using 1 minute, the data is noiser and you want more profound signals. Thresholds generally in this range should be between 5 - 7. For larger timeframes, you want to relax this threshold, to about 2 to 3. You can toggle in increments of 0.5 to find what works the best. Generally you want to see very rigorous volume node signals instead of tons of them. Determine what you want to see: You can turn of the support and resistance lines and just have the node identification signals and the return boxes. Or, you can just have the support and resistance lines and turn off the return boxes. You can customize the information the indicator displays in the settings menu to suit what you are most interested in. Let's look at some examples ' DIS on the hourly. We can see that the average up move from the high buying nodes has a target of 115.42, and in between there we can see the high selling and buying nodes and their compositions. High buying (100% of the high buying volume) is around the 112.61. This means, you would expect this to be an area of retracement. We can also see that high selling is just below that at 111.66, which can be a resistance area. Here is a closer look at the levels specifically: EPAM on the daily: You can see a successful retrace back to a high volume node. Concluding remarks That's the indicator! Its one that is best to get a feel for, play around and decide on the settings you like for your individual ticker. I have included tooltip descriptions for the settings within the indicator as well. I hope you enjoy it and find it helpful! Thanks for reading/checking it out and as always, safe trades!
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Steversteves tarafından
4
Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator Overview The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities. "Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY ### Key Features ✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics ✅ **Dynamic weighting**: Assets weighted by rolling correlation strength ✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro ✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9) ✅ **Visual transparency**: Live correlation panel, fair value bands, statistics ✅ **Non-repainting**: All calculations use confirmed historical data only ### What This Indicator Does - Builds a **synthetic macro composite** from traditional assets - Runs a **rolling regression** to predict BTC price from macro - Calculates **deviation z-score** (how far BTC is from macro fair value) - Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2) - Generates **exit signals** when BTC returns to fair value (dev > 0) ### What This Indicator Is NOT ❌ Not a high-frequency trading system (sparse signals by design) ❌ Not optimized for absolute returns (optimized for Sharpe ratio) ❌ Not suitable as standalone trading system (best as overlay/confirmation) ❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks) --- ## Core Concept ### The Premise Bitcoin doesn't trade in a vacuum. It's influenced by: - **Risk appetite** (equities: QQQ, SPX) - **Dollar strength** (DXY - inverse to risk assets) - **Safe haven flows** (Gold: XAUUSD) When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower. ### The Innovation Instead of looking at BTC in isolation, this indicator: 1. **Measures how strongly** BTC currently correlates with each macro asset 2. **Builds a weighted composite** of those macro returns (the "D" driver) 3. **Regresses BTC price on D** to estimate "macro fair value" 4. **Tracks the deviation** between actual price and fair value 5. **Signals mean reversion** when deviation becomes extreme ### The Edge The validated edge comes from: - **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars) - **Monotonic relationship** (more negative dev → higher forward returns) - **Works out-of-sample** (test Sharpe +83-87% better than training) - **Low correlation with buy & hold** (provides diversification value) --- ## Methodology ### Step 1: Macro Composite Driver D(t) The indicator builds a weighted composite of macro asset returns: **Process:** 1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD) 2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars 3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0 4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships 5. **Z-score normalize** each reference's returns over `fvWindow` 6. **Composite D(t)** = weighted sum of sign-adjusted z-scores **Formula:** ``` For each reference i: corr_i = correlation(BTC_returns, ref_i_returns, corrLen) weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0 sign_i = +1 if corr_i >= 0 else -1 z_i = (ref_i_returns - mean) / std contrib_i = sign_i * z_i * weight_i D(t) = sum(contrib_i) / sum(weight_i) ``` **Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way. --- ### Step 2: Fair Value Regression Uses rolling linear regression to predict BTC price from D(t): **Model:** ``` BTC_price(t) = α + β * D(t) ``` **Calculation (Pine Script approach):** ``` corr_CD = correlation(BTC_price, D, fvWindow) sd_price = stdev(BTC_price, fvWindow) sd_D = stdev(D, fvWindow) cov = corr_CD * sd_price * sd_D var_D = variance(D, fvWindow) β = cov / var_D α = mean(BTC_price) - β * mean(D) fair_value(t) = α + β * D(t) ``` **Result:** A time-varying "macro fair value" line that adapts as correlations change. --- ### Step 3: Deviation Oscillator Measures how far BTC price has deviated from fair value: **Calculation:** ``` residual(t) = BTC_price(t) - fair_value(t) residual_std = stdev(residual, normWindow) deviation(t) = residual(t) / residual_std ``` **Interpretation:** - `dev = 0` → BTC at fair value - `dev = -2` → BTC is 2 standard deviations **cheap** vs macro - `dev = +2` → BTC is 2 standard deviations **rich** vs macro --- ### Step 4: Signal Generation **Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro) **Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value) **No shorting** in default config (risk management choice - crypto volatility) --- ## How It Works ### Visual Components #### 1. Price Chart (Main Panel) **Fair Value Line (Orange):** - The estimated "macro-driven fair value" for BTC - Calculated from rolling regression on macro composite **Fair Value Bands:** - **±1σ** (light): 68% confidence zone - **±2σ** (medium): 95% confidence zone - **±3σ** (dark, dots): 99.7% confidence zone **Entry/Exit Markers:** - **Green "LONG" label** below bar: Entry signal (dev < -2) - **Red "EXIT" label** above bar: Exit signal (dev > 0) #### 2. Deviation Oscillator (Separate Pane) **Line plot:** - Shows current deviation z-score - **Green** when dev < -2 (cheap) - **Red** when dev > +2 (rich) - **Gray** when neutral **Histogram:** - Visual representation of deviation magnitude - Green bars = negative deviation (cheap) - Red bars = positive deviation (rich) **Threshold lines:** - **Green dashed at -2.0**: Entry threshold - **Red dashed at 0.0**: Exit threshold - **Gray solid at 0**: Fair value line #### 3. Correlation Panel (Top-Right) Shows live correlation and weighting for each macro asset: | Asset | Corr | Weight | |-------|------|--------| | QQQ | +0.45 | 0.45 | | DXY | -0.32 | 0.32 | | XAUUSD | +0.15 | 0.00 | | Avg \|Corr\| | 0.31 | 0.77 | **Reading:** - **Corr**: Current rolling correlation with BTC (-1 to +1) - **Weight**: How much this asset contributes to fair value (0 = excluded) - **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals) **Colors:** - Green/Red corr = positive/negative correlation - White weight = asset included, Gray = excluded (below minCorrAbs) #### 4. Statistics Label (Bottom-Right) ``` ━━━ BTC Macro FV ━━━ Dev: -2.34 Price: $103,192 FV: $110,500 Status: CHEAP ⬇ β: 103.52 ``` **Fields:** - **Dev**: Current deviation z-score - **Price**: Current BTC close price - **FV**: Current macro fair value estimate - **Status**: CHEAP (< -2), RICH (> +2), or FAIR - **β**: Current regression beta (sensitivity to macro) --- ## Installation & Setup ### TradingView Setup 1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.) 2. Open **Pine Editor** (bottom panel) 3. Click **"+ New"** → **"Blank indicator"** 4. **Delete** all default code 5. **Copy** the entire Pine Script from `GHPT_optimized.pine` 6. **Paste** into the editor 7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator" 8. Click **"Add to Chart"** ### Recommended Chart Settings **Timeframe:** 4h (validated timeframe) **Chart Type:** Candlestick or Heikin Ashi **Overlay:** Yes (indicator plots on price chart + separate pane) **Alternative Timeframes:** - Daily: Works but slower signals - 1h-2h: May work but not validated - < 1h: Not recommended (too noisy) ### Symbol Requirements **Primary:** BTC/USD or BTC/USDT on any exchange **Macro References:** Automatically fetched - QQQ (Nasdaq 100 ETF) - DXY (US Dollar Index) - XAUUSD (Gold spot) **Data Requirements:** - At least **90 bars** of history (warmup period) - Premium TradingView recommended for full historical data --- ## Reading the Indicator ### Identifying Signals #### Strong Long Signal (High Conviction) - ✅ Deviation < -2.0 (extreme undervaluation) - ✅ Avg |Corr| > 0.3 (strong macro relationships) - ✅ Price touching or below -2σ band - ✅ "LONG" label appears below bar **Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe). #### Moderate Long Signal (Lower Conviction) - ⚠️ Deviation between -1.5 and -2.0 - ⚠️ Avg |Corr| between 0.2-0.3 - ⚠️ Price approaching -2σ band **Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals. #### Exit Signal - 🔴 Deviation crosses above 0 (returns to fair value) - 🔴 "EXIT" label appears above bar **Interpretation:** Mean reversion complete. Close long positions. #### Strong Short/Avoid Signal - 🔴 Deviation > +2.0 (extreme overvaluation) - 🔴 Avg |Corr| > 0.3 - 🔴 Price touching or above +2σ band **Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure. ### Regime Detection **Strong Regime (Reliable Signals):** - Avg |Corr| > 0.3 - Multiple assets weighted > 0 - Fair value line tracking price reasonably well **Weak Regime (Unreliable Signals):** - Avg |Corr| < 0.2 - Most weights = 0 (grayed out) - Fair value line diverging wildly from price - **Action:** Ignore signals until correlations strengthen
Pine Script® göstergesi
popularGnuofls7 tarafından
SMT + CVD (NQ vs ES) w/ AlertsSMT + CVD (NQ vs ES) w/ Alerts This tool combines Smart Money Technique (SMT) and Cumulative Volume Delta (CVD) to highlight high-probability inflection points on NQ (primary) versus ES (secondary). How it works SMT condition: the primary breaks its most recent swing (High for bearish / Low for bullish) while the secondary does not break the corresponding swing within a small retest window. CVD confirmation: at the same time, the primary’s CVD shows divergence (higher price but lower/equal CVD for shorts, lower price but higher/equal CVD for longs). When both align, the script plots a marker/label and draws a line from the primary swing to the signal bar. Alerts are fired. Signals & Alerts Labels: “SMT+CVD DOWN/UP” on the signal bar. Lines: connects the primary swing → signal bar so you can see the structure that produced the signal. Alert names: “SMT+CVD Bearish” and “SMT+CVD Bullish.” Inputs Primary / Secondary symbols: defaults NQ & ES (you can change them). Resolution: use chart timeframe or specify one. Swing Left/Right Bars: pivot detection depth (higher = larger swings). Break Window Bars: how many bars the secondary has to not break for SMT to be valid. CVD Up/Down By: Close vs Previous Close (default) or Close vs Open. Anchor CVD Daily: resets CVD at session/day start. CVD Smoothing (EMA): smooths the CVD line (optional show). FAST Pivots (no future bars): left-only swing detection so signals appear sooner and behave well in Replay/live. Require Secondary Pivot: if ON, SMT checks wait for a confirmed secondary swing; if OFF, signals can appear while the secondary swing is still forming (useful for Replay/testing). Show CVD line: optional, may compress price scale. Non-repaint notes With FAST Pivots ON, swings are detected with no future bars (minimal latency = leftBars). With FAST Pivots OFF, standard pivots require rightBars future bars to confirm the swing (classic, but naturally delayed). Tips For intraday futures, keep leftBars/rightBars small (e.g., 3/3) and Break Window 1–3. In Replay, enable FAST Pivots and consider disabling Require Secondary Pivot if you want signals to appear as soon as the primary breaks. Combine with session filters, execution rules, or liquidity zones for context.
Pine Script® göstergesi
anthony32773 tarafından
RightFlow Universal Volume Profile - Any Market Any TimeframeSummary in one paragraph RightFlow is a right anchored microstructure volume profile for stocks, futures, FX, and liquid crypto on intraday and daily timeframes. It acts only when several conditions align inside a session window and presents the result as a compact right side profile with value area, POC, a bull bear mix by price bin, and a HUD of profile VWAP and pressure shares. It is original because it distributes each bar’s weight into multiple mid price slices, blends bull bear pressure per bin with a CLV based split, and grows the profile to the right so price action stays readable. Add to a clean chart, read the table, and use the visuals. For conservative workflows read on bar close. Scope and intent • Markets. Major FX pairs, index futures, large cap equities and ETFs, liquid crypto. • Timeframes. One minute to daily. • Default demo used in the publication. SPY on 15 minute. • Purpose. See where participation concentrates, which side dominated by price level, and how far price sits from VA and POC. Originality and usefulness • Unique fusion. Right anchored growth plus per bar slicing and CLV split, with weight modes Raw, Notional, and DeltaProxy. • Failure mode addressed. False reads from single bar direction and coarse binning. • Testability. All parts sit in Inputs and the HUD. • Portable yardstick. Value Area percent and POC are universal across symbols. • Protected scripts. Not applicable. Method and use are fully disclosed. Method overview in plain language Pick a scope Rolling or Today or This Week. Define a window and number of price bins. For each bar, split its range into small slices, assign each slice a weight from the selected mode, and split that weight by CLV or by bar direction. Accumulate totals per bin. Find the bin with the highest total as POC. Expand left and right until the chosen share of total volume is covered to form the value area. Compute profile VWAP for all, buyers, and sellers and show them with pressure shares. Base measures Range basis. High minus low and mid price samples across the bar window. Return basis. Not used. VWAP trio is price weighted by weights. Components • RightFlow Bins. Price histogram that grows to the right. • Bull Bear Split. CLV based 0 to 1 share or pure bar direction. • Weight Mode. Raw volume, notional volume times close, or DeltaProxy focus. • Value Area Engine. POC then outward expansion to target share. • HUD. Profile VWAP, Buy and Sell percent, winner delta, split and weight mode. • Session windows optional. Scope resets on day or week. Fusion rule Color of each bin is the convex blend of bull and bear shares. Value area shading is lighter inside and darker outside. Signal rule This is context, not a trade signal. A strong separation between buy and sell percent with price holding inside VA often confirms balance. Price outside VA with skewed pressure often marks initiative moves. What you will see on the chart • Right side bins with blended colors. • A POC line across the profile width. • Labels for POC, VAH, and VAL. • A compact HUD table in the top right. Table fields and quick reading guide • VWAP. Profile VWAP. • Buy and Sell. Pressure shares in percent. • Delta Winner. Winner side and margin in percent. • Split and Weight. The active modes. Reading tip. When Session scope is Today or This Week and Buy minus Sell is clearly positive or negative, that side often controls the day’s narrative. Inputs with guidance Setup • Profile scope. Rolling or session reset. Rolling uses window bars. • Rolling window bars. Typical 100 to 300. Larger is smoother. Binning • Price bins. Typical 32 to 128. More bins increase detail. • Slices per bar. Typical 3 to 7. Raising it smooths distribution. Weighting • Weight mode. Raw, Notional, DeltaProxy. Notional emphasizes expensive prints. • Bull Bear split. CLV or BarDir. CLV is more nuanced. • Value Area percent. Typical 68 to 75. View • Profile width in bars, color split toggle, value area shading, opacities, POC line, VA labels. Usage recipes Intraday trend focus • Scope Today, bins 64, slices 5, Value Area 70. • Split CLV, Weight Notional. Intraday mean reversion • Scope Today, bins 96, Value Area 75. • Watch fades back to POC after initiative pushes. Swing continuation • Scope Rolling 200 bars, bins 48. • Use Buy Sell skew with price relative to VA. Realism and responsible publication No performance claims. Shapes can move while a bar forms and settle on close. Education only. Honest limitations and failure modes Thin liquidity and data gaps can distort bin weights. Very quiet regimes reduce contrast. Session time is the chart venue time. Open source reuse and credits None. Legal Education and research only. Not investment advice. Test on history and simulation before live use.
Pine Script® göstergesi
exlux tarafından
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL Summary in one paragraph FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close. Scope and intent • Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs • Timeframes. One minute to daily • Default demo used in the publication. SPY on 30min • Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state • Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes • Testability. All windows and gains are inputs • Portable yardstick. Returns use natural log units and range is bar high minus low • Protected scripts. Not used. Method disclosed plainly here Method overview in plain language Base measures • Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion Components • Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized • Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression • Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves • Energy score. Z scores of the above form a single energy that controls the state gain • One bar projection. Current slope extended by one bar for anticipatory checks Fusion rule Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push. Signal rule • Long suggestion and order when close is below trend and the one bar projection is above the trend • Short suggestion and flip when close is above trend and the one bar projection is below the trend • WAIT is implicit when neither condition holds • In position states end on the opposite condition What you will see on the chart • Colored trendline teal for rising red for falling gray for flat • Optional projection line one bar ahead • Optional background can be enabled in code • Alerts on price cross and on slope flips Inputs with guidance Setup • Price source. Close by default Logic • Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips • Vol window. Typical range 30 to 120. Higher calms curvature • Energy window. Typical range 20 to 80. Higher slows regime changes • Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop UI • Show 1 bar projection. Colors for up down flat Properties visible in this publication • Initial capital 25000 • Base currency USD • Commission percent 0.03 • Slippage 5 • Default order size method percent of equity value 3% • Pyramiding 0 • Process orders on close off • Calc on every tick off • Recalculate after order is filled off Realism and responsible publication • No performance claims • Intrabar reminder. Shapes can move while a bar forms and settle on close • Strategy uses standard candles only Honest limitations and failure modes • Sudden gaps and thin liquidity can still produce fast flips • Very quiet regimes reduce contrast. Use larger windows and lower max gain • Session time uses the exchange time of the chart if you enable any windows later • Past results never guarantee future outcomes Open source reuse and credits • None
Pine Script® stratejisi
exlux tarafından
First X Days Of A YearFirst X-Day Indicator Overview The "First X-Day Indicator" is a powerful tool to visualize and analyze market sentiment during the crucial first trading days of each new year. It provides immediate visual feedback on whether the year is starting with positive or negative momentum compared to the previous year's close, a concept often related to market theories like the "January Effect" or the "First Five Days Rule." The indicator is designed to be clean, intuitive, and fully customizable to fit your charting style. Key Features Yearly Baseline: Automatically draws a horizontal line at the previous year's closing price. This line serves as a clear 0% reference for the current year's performance. Dynamic Background Coloring: For a user-defined number of days at the start of the year, the chart background is colored daily. Green indicates the close is above the previous year's close, while red indicates it's below. Final Performance Symbol: At the end of the analysis period (e.g., on the 5th day), a single summary symbol (like 👍 or 👎) appears. This symbol represents the final performance outcome of the initial trading period. Settings & Customization You have full control over all visual elements: Analysis Period: Define exactly how many days at the start of the year you want to analyze (e.g., 3, 5, or 10 days). Line Customization: Fully control the yearly baseline's appearance. You can change its color, width, and style (Solid, Dashed, or Dotted) or hide it completely. Symbol Customization: Choose any character or emoji for the positive and negative performance symbols. You can also adjust their size (Small, Normal, Large) or hide them. Background Control: Enable or disable the daily background coloring and select your preferred custom colors for positive and negative days.
Pine Script® göstergesi
michid2 tarafından
1
Timeframe LiquidityTimeframe Liquidity – Multi-Timeframe Highs & Lows by Timeframe Liquidity automatically plots previous day, week, month, and year highs and lows, key liquidity zones used by smart money and price-action traders. These levels extend into the future and can automatically stop once price wicks through, showing clear liquidity sweeps and tested zones. Perfect for traders using ICT / SMC concepts, liquidity theory, or market structure analysis. Instantly see where liquidity rests, where it’s been taken, and how price reacts at major support and resistance. Features: Auto-plots PDH/PDL, PWH/PWL, PMH/PML, PYH/PYL Custom line styles, colors, and label sizes Option to stop line on wick (liquidity sweep) Smart timeframe visibility (hides same-TF levels) Accurate UTC offset handling Identify liquidity pools fast, trade cleaner charts, and track where smart money hunts liquidity. Built for precision, clarity, and confluence.
Pine Script® göstergesi
archiedurrant tarafından
Triple-EMA Cloud (3× configurable EMAs + timeframe + fill)About This Script Name: Triple-EMA Cloud (3× configurable EMAs + timeframe + fill) What it does: The script plots three Exponential Moving Averages (EMAs) on your chart. You can set each EMA’s length (how many bars or days it averages over), source (for example, closing price, opening price, or the midpoint of high + low), and timeframe (you can have one EMA use daily data, another hourly data, etc.). The indicator draws a “cloud” or channel by shading the area between the outermost two EMAs of the three. This lets you see a band or zone that the price is moving in, defined by those EMAs. You also get full control over how each of the three EMA‐lines looks: color, thickness, transparency, and plot style (solid line, steps, circles, etc.). How to Use It (for Beginners) Here’s how a trader who’s new to charts can use this tool, especially when looking for pullbacks or undercut price action. Key Concepts Trend: Imagine the market price is generally going up or down. EMAs are a way to smooth out price movements so you can see the trend more clearly. Pullback: When a price has been going up (an uptrend), sometimes it dips down a little before going up again. That dip is the pullback. It’s a chance to enter or add to a position at a “better price.” Undercut: This is when price drops below an important level (for example an EMA) and then comes back up. It looks like it broke below, but then it recovers. That may show reverse pressure or strength building. How the Script Helps With Pullbacks & Undercuts Marking Trend Zones with the Cloud The cloud between the outer EMA lines gives you a zone of expected support/resistance. If the price is above the cloud, that zone can act like a “floor” in uptrends; if it is below, the cloud might act like a “ceiling” in downtrends. Watching Price vs the EMAs If the price pulls back toward the cloud (or toward one of the EMAs) and then bounces back up, that’s a signal that the uptrend might continue. If the price undercuts (goes a bit below) one of the EMAs or the cloud and then returns above it, that can also be a signal. It suggests that even though there was a temporary drop, buyers stepped in. Using the Three EMAs for Confirmation Because the script uses three EMAs, you can see how tightly or loosely they are spaced. If all three EMAs are broadly aligned (for example, in an uptrend: shorter length above longer length, each pulling from reliable price source), that gives more confidence in trend strength. If the middle EMA (or different source/timeframe) is holding up as support while others are above, it strengthens signal. Entry & Exit Points Entry: For example, after a pullback toward the cloud or “mid‐EMA”, wait for price to show a bounce up. That could be a better entry than buying at the top. Stop Loss / Risk: You might place a stop loss just below the cloud or the lowest of your selected EMAs so that if price breaks through, the idea is invalidated. Profit Target: Could be a recent high, resistance level, or a fixed reward-risk multiple (for example aiming to make twice what you risked). Practical Steps for New Traders Set up the EMAs Choose simple lengths like 10, 21, 50. For example, EMA #1 = length 10, source Close, timeframe “current chart”; EMA #2 = length 21, source (H+L)/2; EMA #3 = length 50, maybe timeframe daily. Observe the Price Action When price moves up, then dips, see if it comes back near the shaded cloud or one of the EMAs. See if the dip touches the EMAs lightly (not a big drop) and then price starts climbing again. Look for undercuts If price briefly goes below a line (or below cloud) and then closes back above, that’s undercut + recovery. That bounce back is often meaningful. Manage risk Only put in money you can afford to lose. Use small position size until you get comfortable. Use stop-loss (as mentioned) in case the price doesn’t bounce as expected. Practice Put this indicator on charts (stocks you follow) in past time periods. See how price behaved with pullbacks / undercuts relative to the EMAs & cloud. This helps you learn to see signals. What It Doesn’t Do (and What to Be Careful Of) It doesn’t predict the future — it simply shows zones and trends. Price can still break down through the cloud. In a “choppy” market (i.e. when price is going up and down without a clear trend), signals from EMAs / clouds are less reliable. You’ll get more “false bounces.” Under / overshoots & big news events can break through clean levels, so always watch for confirmation (volume, price behavior) before putting big money in.
Pine Script® göstergesi
Blk0ut tarafından