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statisticsLibrary "statistics" General statistics library. erf(x) The "error function" encountered in integrating the normal distribution (which is a normalized form of the Gaussian function).   Parameters:      x : The input series.   Returns: The Error Function evaluated for each element of x. erfc(x)   Parameters:      x : The input series   Returns: The Complementary Error Function evaluated for each alement of x. sumOfReciprocals(src, len) Calculates the sum of the reciprocals of the series. For each element 'elem' in the series: sum += 1/elem Should the element be 0, the reciprocal value of 0 is used instead of NA.   Parameters:      src : The input series.      len : The length for the sum.   Returns: The sum of the resciprocals of 'src' for 'len' bars back. mean(src, len) The mean of the series. (wrapper around ta.sma).   Parameters:      src : The input series.      len : The length for the mean.   Returns: The mean of 'src' for 'len' bars back. average(src, len) The mean of the series. (wrapper around ta.sma).   Parameters:      src : The input series.      len : The length for the average.   Returns: The average of 'src' for 'len' bars back. geometricMean(src, len) The Geometric Mean of the series. The geometric mean is most important when using data representing percentages, ratios, or rates of change. It cannot be used for negative numbers Since the pure mathematical implementation generates a very large intermediate result, we performed the calculation in log space.   Parameters:      src : The input series.      len : The length for the geometricMean.   Returns: The geometric mean of 'src' for 'len' bars back. harmonicMean(src, len) The Harmonic Mean of the series. The harmonic mean is most applicable to time changes and, along with the geometric mean, has been used in economics for price analysis. It is more difficult to calculate; therefore, it is less popular than eiter of the other averages. 0 values are ignored in the calculation.   Parameters:      src : The input series.      len : The length for the harmonicMean.   Returns: The harmonic mean of 'src' for 'len' bars back. median(src, len) The median of the series. (a wrapper around ta.median)   Parameters:      src : The input series.      len : The length for the median.   Returns: The median of 'src' for 'len' bars back. variance(src, len, biased) The variance of the series.   Parameters:      src : The input series.      len : The length for the variance.      biased : Wether to use the biased calculation (for a population), or the unbiased calculation (for a sample set). .   Returns: The variance of 'src' for 'len' bars back. stdev(src, len, biased) The standard deviation of the series.   Parameters:      src : The input series.      len : The length for the stdev.      biased : Wether to use the biased calculation (for a population), or the unbiased calculation (for a sample set). .   Returns: The standard deviation of 'src' for 'len' bars back. skewness(src, len) The skew of the series. Skewness measures the amount of distortion from a symmetric distribution, making the curve appear to be short on the left (lower prices) and extended to the right (higher prices). The extended side, either left or right is called the tail, and a longer tail to the right is called positive skewness. Negative skewness has the tail extending towards the left.   Parameters:      src : The input series.      len : The length for the skewness.   Returns: The skewness of 'src' for 'len' bars back. kurtosis(src, len) The kurtosis of the series. Kurtosis describes the peakedness or flatness of a distribution. This can be used as an unbiased assessment of whether prices are trending or moving sideways. Trending prices will ocver a wider range and thus a flatter distribution (kurtosis < 3; negative kurtosis). If prices are range-bound, there will be a clustering around the mean and we have positive kurtosis (kurtosis > 3)   Parameters:      src : The input series.      len : The length for the kurtosis.   Returns: The kurtosis of 'src' for 'len' bars back. excessKurtosis(src, len) The normalized kurtosis of the series. kurtosis > 0 --> positive kurtosis --> trending kurtosis < 0 --> negative krutosis --> range-bound   Parameters:      src : The input series.      len : The length for the excessKurtosis.   Returns: The excessKurtosis of 'src' for 'len' bars back. normDist(src, len, value) Calculates the probability mass for the value according to the src and length. It calculates the probability for value to be present in the normal distribution calculated for src and length.   Parameters:      src : The input series.      len : The length for the normDist.      value : The series of values to calculate the normal distance for   Returns: The normal distance of 'value' to 'src' for 'len' bars back. normDistCumulative(src, len, value) Calculates the cumulative probability mass for the value according to the src and length. It calculates the cumulative probability for value to be present in the normal distribution calculated for src and length.   Parameters:      src : The input series.      len : The length for the normDistCumulative.      value : The series of values to calculate the cumulative normal distance for   Returns: The cumulative normal distance of 'value' to 'src' for 'len' bars back. zScore(src, len, value) Returns then z-score of objective to the series src. It returns the number of stdev's the objective is away from the mean(src, len)   Parameters:      src : The input series.      len : The length for the zScore.      value : The series of values to calculate the cumulative normal distance for   Returns: The z-score of objectiv with respect to src and len. er(src, len) Calculates the efficiency ratio of the series. It measures the noise of the series. The lower the number, the higher the noise.   Parameters:      src : The input series.      len : The length for the efficiency ratio.   Returns: The efficiency ratio of 'src' for 'len' bars back. efficiencyRatio(src, len) Calculates the efficiency ratio of the series. It measures the noise of the series. The lower the number, the higher the noise.   Parameters:      src : The input series.      len : The length for the efficiency ratio.   Returns: The efficiency ratio of 'src' for 'len' bars back. fractalEfficiency(src, len) Calculates the efficiency ratio of the series. It measures the noise of the series. The lower the number, the higher the noise.   Parameters:      src : The input series.      len : The length for the efficiency ratio.   Returns: The efficiency ratio of 'src' for 'len' bars back. mse(src, len) Calculates the Mean Squared Error of the series.   Parameters:      src : The input series.      len : The length for the mean squared error.   Returns: The mean squared error of 'src' for 'len' bars back. meanSquaredError(src, len) Calculates the Mean Squared Error of the series.   Parameters:      src : The input series.      len : The length for the mean squared error.   Returns: The mean squared error of 'src' for 'len' bars back. rmse(src, len) Calculates the Root Mean Squared Error of the series.   Parameters:      src : The input series.      len : The length for the root mean squared error.   Returns: The root mean squared error of 'src' for 'len' bars back. rootMeanSquaredError(src, len) Calculates the Root Mean Squared Error of the series.   Parameters:      src : The input series.      len : The length for the root mean squared error.   Returns: The root mean squared error of 'src' for 'len' bars back. mae(src, len) Calculates the Mean Absolute Error of the series.   Parameters:      src : The input series.      len : The length for the mean absolute error.   Returns: The mean absolute error of 'src' for 'len' bars back. meanAbsoluteError(src, len) Calculates the Mean Absolute Error of the series.   Parameters:      src : The input series.      len : The length for the mean absolute error.   Returns: The mean absolute error of 'src' for 'len' bars back.
Pine Script® ライブラリ
maartenheremansの投稿
2
BE_CustomFx_LibraryLibrary "BE_CustomFx_Library" A handful collection of regular functions, Custom Tools & Utility Functions could be used in regular Scripts. hope these functions can be understood by a non programmer like me too. G_TextValOfNumber(ValueToConvert, RequiredDecimalPlaces, BeginingChar, EndChar) Function to return the String Value of Number with decimal precision with the prefix and suffix characters provided   Parameters:      ValueToConvert : = Number to Convert      RequiredDecimalPlaces : = No of Decimal values Required. supports to a max of 5 decimals else defaults to 2      BeginingChar : = Prefix character which is needed.      EndChar : = Suffix character which is needed.   Returns: Returns Out put with formated value of Given Number for the specified deicimal values with Prefix and suffix string G_TradableValue(ValueToConvert, NeedCustomization, RequiredDecimalPlaces) Function to return the Tradable Value of Number   Parameters:      ValueToConvert : = Number to Convert      NeedCustomization : = set to 1 if you want to customize the decimal percision values. default is No customization needed, which provides output equalent to round_to_mintick      RequiredDecimalPlaces : = if NeedCustomization is set to 1 mention the decimal percision value required. max supported decimal is 5 else defaults to 2   Returns: Returns Out put with formated value of Given Number G_TxtSizeForLables(SizeValue) Function to Get size Value for text values used in Lables   Parameters:      SizeValue : = auto, tiny, small, normal, large, huge. specify either of these values or default value Normal will be displayed as output   Returns: Returns Respective Text size G_Reg_LineType(LineType) Function to Get Line Style Value for text values used in Lines   Parameters:      LineType : = 'solid (─)', 'dotted (┈)', 'dashed (╌)', 'arrow left (←)', 'arrow right (→)', 'arrows both (↔)' or default line style 'dotted (┈)' will be the output   Returns: Returns Respective Line style G_ShapeTypeForLables(ShapeType) Function to Get Shape Style Value for text values used in plot shapes   Parameters:      ShapeType : = 'XCross', 'Cross', 'Triangle Up', 'Triangle Down', 'Flag', 'Circle','Arrow Up', 'Arrow Down','Lable Up', 'Lable Down' or default shpae style Triangle Up will be the output   Returns: Returns Respective Shape style G_Indicator_Val(string, float, int, int) Gets Output of the technical analyis indicator which has length Parameter. RSI, ATR, EMA, SMA, HMA, WMA, VWMA, 'CMO', 'MOM', 'ROC','VWAP'   Parameters:      string : IndicatorName to be specified      float : SrcVal for the TA indicator default is close      int : Length for the TA indicator      int : DecimalValue optional to specify if required formatted output with decimal percision   Returns: Value with the given parameters G_CandleInfo(string, bool, float, bool) function to get Candle Informarion such as both wicksize, top wick size , bottom wick size, full candle size and body size in default points   Parameters:      string : WhatCandleInfo, string input with either of these options "Wick" , "TWick" , "BWick" , "Candle", "Body" , "BearfbVal", "BullfbVal" , "CandleOpen" ,"CandleClose", "CandleHigh" , "CandleLow", "BodyPct"      bool : RepaintingVersion, set to true if required data on the realtime bar else default is set to false      float : FibValueOfCandle, set the fibo value to extract fibvalue of the candle else default is set to 38.2%      bool : AccountforGaps, set to true if required data on considering the gap between previous and current bar else default is set to false   Returns: Returns Respective values for the candles G_BullBearBarCount(int, int) Counts how many green & red bars have printed recently (ie. pullback count)   Parameters:      int : HowManyCandlesToCheck The lookback period to look back over      int : BullBear The color of the bar to count (1 = Bull, -1 = Bear), Open = close candles are ignored   Returns: The bar count of how many candles have retraced over the given lookback with specific candles BarToStartYourCalculation(Int) function to get candle co-ordinate in order to use it further for calculating your analysis work . "Heart full Thanks to 3 Pine motivators (LonesomeTheBlue, Myank & Sriki) who helped me cracking this logic"   Parameters:      Int : SelectedCandleNumber (default=450) How many candles you would need to anlysie in your script from the right.   Returns: A boolean - output is returned to say the starting point and continue to diplay true for the future candles isHammer(float, bool, bool) Checks if the current bar is a hammer candle based on the given parameters   Parameters:      float : fib (default=0.382) The fib to base candle body on      bool : colorMatch (default=false) Does the candle need to be green? (true/false)      bool : NeedRepainting (default=false) Specify True if you need them to calculate on the realtime bars   Returns: A boolean - true if the current bar matches the requirements of a hammer candle isStar(float, bool, bool) Checks if the current bar is a shooting star candle based on the given parameters   Parameters:      float : fib (default=0.382) The fib to base candle body on      bool : colorMatch (default=false) Does the candle need to be red? (true/false)      bool : NeedRepainting (default=false) Specify True if you need them to calculate on the realtime bars   Returns: A boolean - true if the current bar matches the requirements of a shooting star candle isDoji(float, float, bool) Checks if the current bar is a doji candle based on the given parameters   Parameters:      float : _wickSize (default=1.5 times) The maximum allowed times can be top wick size compared to the bottom (and vice versa)      float : _bodySize (default= 5 percent to be mentioned as 0.05) The maximum body size as a percentage compared to the entire candle size      bool : NeedRepainting (default=false) Specify true if you need them to calculate on the realtime bars   Returns: A boolean - true if the current bar matches the requirements of a doji candle isBullishEC(float, float, bool, bool) Checks if the current bar is a bullish engulfing candle   Parameters:      float : _allowance (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      float : _rejectionWickSize (default=disabled) The maximum rejection wick size compared to the body as a percentage      bool : _engulfWick (default=false) Does the engulfing candle require the wick to be engulfed as well?      bool : NeedRepainting (default=false) Specify True if you need them to calculate on the realtime bars   Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle isBearishEC(float, float, bool, bool) Checks if the current bar is a bearish engulfing candle   Parameters:      float : _allowance (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)      float : _rejectionWickSize (default=disabled) The maximum rejection wick size compared to the body as a percentage      bool : _engulfWick (default=false) Does the engulfing candle require the wick to be engulfed as well?      bool : NeedRepainting (default=false) Specify True if you need them to calculate on the realtime bars   Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle Plot_TrendLineAtDegree(float, float, int, string, bool) helps you to plot the Trendlines based on the specified angle at the defined price to bar ratio   Parameters:      float : Degree (default=14) angle at which Trendline to be plot      float : price2bar_ratio (default=1e-10) The maximum rejection wick size compared to the body as a percentage      int : Bars2Plot (default=6) Does the engulfing candle require the wick to be engulfed as well?      string : LineStyle = 'solid (─)', 'dotted (┈)', 'dashed (╌)', 'arrow left (←)', 'arrow right (→)', 'arrows both (↔)' or default line style 'dotted (┈)' will be the output      bool : PlotOnOpen_Close (default=false) Specify True if you need them to calculate on the Open\Close Values   Returns: plot the Trendlines based on the specified angle at the defined price to bar ratio
Pine Script® ライブラリ
TradeWiseWithEaseの投稿
Donchian DipThe Donchian Dip This strategy is designed to look for good "Buy the Dip" entries on stocks that are clearly in a strong 1-year upward trend. If you do not know how to identify those stocks on your own please do not use this system or continue your education until you do. The Donchian Dip strategy was designed on the daily time frame but works amazingly well on both daily and weekly timeframes. It does still work on intraday charts also if the current trend on the daily chart is in a strong uptrend. Chart Setup: 3-period Donchian Channel with a 1-period offset (hide basis) Bollinger Bands with the default settings of 20/2 (display basis) Entry Signals: There are 3 different entry signals that will be printed on the chart that have similar underlying criteria but are ranked based on skill level just like ski slope skill levels! I recommend only taking green entries until you are familiar with the system and the stocks you are trading. Green Easy Entry: This is the safest buy the dip entry that is normally found at or near a large retracement bottom. You might get one or two bad entries but be persistent and eventually, a great entry will present itself! These are the specifics for the conditions that trigger a Green entry if you want to know what they are: 1. The current bar is an up bar (green or white bar) and closed above the lower Donchian channel 2. Previous bar or 2 bars back closed below the lower Donchian channel 3. Previous bar or 2 bars back closed below the Bollinger Band Basis (20 SMA ) 4. The low of the previous bar or 2 bars back was below the lower Bollinger Band Blue Intermediate Entry: This is a decent entry if you missed the green entry, want to add to an existing position, or are not sure it will pull back far enough to even give a green entry. I would suggest only trade these entries to add to an existing pyramid position or get back into a trade that you were recently stopped out of. However, on high-flying stocks like TSLA these signals and the Black Diamond entry signals might be the only ones you get for a long time. Also, on the weekly chart, Blue or Black entries are sometimes all you will get for a year or more. These are the specifics for the conditions that trigger a Blue entry if you want to know what they are: 1. The current bar is an up bar (green or white bar) and closed above the lower Donchian channel 2. Previous bar or 2 bars back closed below the lower Donchian channel 3. Previous bar or 2 bars back closed below the Bollinger Band Basis (20 SMA ) Black Diamond Advanced Rule: This is normally just a small pullback re-entry signal on a strong trending stock like TSLA ...trade with extreme caution!!! You have been warned but daredevils feel free to give it a shot. I sometimes do trade these entries if the market and sector of the stock I am trading are extremely bullish or if I am looking to add to a position but I use a conservative stop. These are the specifics for the conditions that trigger a Black entry if you want to know what they are: 1. The current bar is an up bar (green or white bar) and closed above the lower Donchian channel 2. Previous bar or 2 bars back closed below the lower Donchian channel 3. Previous bar or 2 bars back closed above the Bollinger Band Basis (20 SMA ) Exit Criteria: The goal of this strategy is to buy the dip and hold as long as possible...let's practice some Paytience and exercise those holding muscles! RLT!!! So, we don't want to exit early but we also want to protect our profits somehow. We do this by using the built-in trailing stops that are defined by dots of three different shades of purple on the chart (feel free to change these in the settings). Simply move your trailing stop to the highest current dot price level. Do not move the trailing stop down ever even if a lower dot is printed later. These are simply the suggested trailing stops and definitely use your own judgment for exits but if you backtest this strategy enough you will most likely discover that in the long run, these trailing stops work really well. I hope this strategy helps you to identify good "Buy the Dip" entries on stocks you love as well as trains you to hold your winners longer for bigger gains. ***HOW TO ADD TO YOUR CHARTS*** 1) Click the "Add to Favorite Scripts" button 2) Go to a stock chart and click the "Indicators" icon at the top 3) Next, on the left, click the "Favorites" and then click the "Naked Put - Growth Indicator v2" 4) It should appear on your charts, and you can click the "gear" icon on the study to edit a few settings. 5) Read the release notes above so you understand how it works.
Pine Script® インジケーター
Dustin_D_RLTの投稿
8
Squeeze Momentum with Trend Exhaustion# Squeeze Momentum + Trend Exhaustion Indicator ## Complete User Manual --- ## Table of Contents 1. (#what-this-indicator-does) 2. (#visual-components) 3. (#market-states) 4. (#how-to-read-signals) 5. (#trading-examples) 6. (#configuration-guide) 7. (#best-practices) --- ## What This Indicator Does This indicator combines two powerful concepts to identify complete market cycles: ### 1. Squeeze Momentum (LazyBear) Detects **volatility compression** (consolidation) and subsequent **expansion** (breakout). **Think of it like:** A spring being compressed, then released. ### 2. Multi-Timeframe Trend Exhaustion Measures how far price has moved from its moving averages across multiple timeframes. **Think of it like:** A rubber band being stretched—eventually it must snap back. ### The Complete Cycle ``` Consolidation → Breakout → Trend → Exhaustion → Reversion → Consolidation ``` This indicator shows you exactly where you are in this cycle. --- ## Visual Components ### Main Panel (Bottom) | Element | What It Looks Like | Meaning | |---------|-------------------|---------| | **Colored Bars** | Green/Red histogram | Momentum strength and direction | | **Filled Area** | Yellow/Lime/Red gradient area | Price extension from moving averages | | **Cross at Zero** | Black/Gray/Blue cross | Squeeze state (volatility) | | **Dashed Lines** | Horizontal red/green lines | Extension thresholds (±2σ scaled) | --- ### 1. Momentum Histogram (Colored Bars) | Color | Direction | Meaning | |-------|-----------|---------| | **Bright Green** (Lime) | Up ↑ | Strong bullish momentum (increasing) | | **Dark Green** | Up ↑ | Weak bullish momentum (decreasing) | | **Bright Red** | Down ↓ | Strong bearish momentum (increasing) | | **Dark Red** (Maroon) | Down ↓ | Weak bearish momentum (decreasing) | **Key insight:** When bars change from bright to dark, momentum is fading. --- ### 2. Extension Area (Filled Gradient) Shows how extended price is from its moving averages across 5 timeframes (5m, 15m, 1h, 4h, Daily). | Color | Position | Meaning | |-------|----------|---------| | **Red** | High above zero | Severely overbought (>2σ scaled) | | **Orange/Yellow** | Above zero | Moderately overbought | | **Lime/Green** | Below zero | Moderately oversold | | **Teal** | Deep below zero | Severely oversold (<-2σ scaled) | **The area is scaled 3x** for better visibility. Actual values shown in table. **Reading it:** - **Area touching upper dashed line** = Price very far above averages (exhaustion territory) - **Area touching lower dashed line** = Price very far below averages (exhaustion territory) - **Area near zero** = Price near its averages (normal/neutral) --- ### 3. Squeeze Indicator (Cross at Zero Line) | Color | Status | Meaning | |-------|--------|---------| | **Black** ⚫ | Squeeze ON | Bollinger Bands inside Keltner Channels → Low volatility, consolidation | | **Gray** ⚪ | Squeeze OFF | Bollinger Bands outside Keltner Channels → Volatility expanding, breakout | | **Blue** 🔵 | No Squeeze | Normal volatility conditions | **Critical:** The transition from Black → Gray is where explosive moves begin. --- ### 4. Entry/Exit Signals | Symbol | Type | Meaning | |--------|------|---------| | 🔺 **Large Green Triangle** | HC Long Entry | High Confidence long setup (Squeeze OFF + Oversold + Confluence) | | 🔻 **Large Red Triangle** | HC Short Entry | High Confidence short setup (Squeeze OFF + Overbought + Confluence) | | 🔺 Small green | Medium Long | Long setup without full confluence | | 🔻 Small red | Medium Short | Short setup without full confluence | | ✕ Orange X | Exit Long | Close long positions (exhaustion detected) | | ✕ Teal X | Exit Short | Close short positions (exhaustion detected) | **Trade only the LARGE triangles** for highest probability setups. --- ## Market States The indicator identifies 7 distinct market states shown in the info table. ### State 1: 💤 CONSOLIDATION **Conditions:** - Squeeze: ON (black cross) - Extension: Near zero (±1σ) - Momentum: Contracting **What's happening:** Price is range-bound, volatility dying down. Spring is being compressed. **Action:** **WAIT.** Do not trade. Set alerts for Squeeze OFF. --- ### State 2: ⚡ BREAKOUT BULL / BEAR **Conditions:** - Squeeze: OFF (gray cross) ← **Key trigger** - Extension: Still moderate - Momentum: Strong directional move (bright green or red bars) **What's happening:** Volatility explosion. Spring released. This is the start of a new trend. **Action:** **ENTER** in direction of momentum. - ⚡ BREAKOUT BULL → Go LONG - ⚡ BREAKOUT BEAR → Go SHORT **Best scenario:** Breakout from oversold/overbought levels (confluence with exhaustion indicator). --- ### State 3: ↗️ TRENDING UP / ↘️ TRENDING DOWN **Conditions:** - Squeeze: OFF or No Squeeze - Extension: Growing (1σ to 2σ) - Momentum: Sustained strong bars **What's happening:** Trend in progress. Price moving away from averages. **Action:** **HOLD** positions. Let winners run. Don't fight the trend. --- ### State 4: ⚠️ EXTENDED UP / DOWN **Conditions:** - Extension: Above 2σ threshold - Momentum: Still strong (bright bars) - Confluence: May be weak **What's happening:** Price stretched but still has power. Caution zone. **Action:** **CAUTION.** Don't enter new positions. Tighten stops on existing positions. --- ### State 5: 🔴 EXHAUSTION BULL / 🟢 EXHAUSTION BEAR **Conditions:** - Extension: >2σ (touching dashed lines) - Momentum: Fading (bright bars turning dark) - Velocity: Decreasing - Confluence: 3/5 or better **What's happening:** Rubber band stretched to maximum. Trend running out of energy. **Action:** **EXIT** positions. - 🔴 EXHAUSTION BULL → Close LONGS, consider SHORT - 🟢 EXHAUSTION BEAR → Close SHORTS, consider LONG **This is the highest probability reversal signal.** --- ### State 6: ➡️ TRENDING (Neutral Direction) **Conditions:** - Price trending but without clear momentum direction changes **Action:** **HOLD** or wait for clearer signals. --- ### State 7: — NEUTRAL **Conditions:** - Extension near zero - No squeeze - Weak momentum **Action:** No trade. Wait for setup. --- ## How to Read Signals ### Perfect Long Entry (High Confidence ⭐) **Requirements (all must be true):** 1. ⚫→⚪ Squeeze just turned OFF (gray cross) 2. 📊 Momentum bars bright GREEN and rising 3. 🔻 Extension area BELOW lower dashed line (oversold) 4. ⭐ Confluence: 3/5 or more timeframes agree (shown as "🔻" in table) **Visual:** Large green triangle appears **What this means:** Price was oversold across multiple timeframes, consolidated, and is now breaking out upward with fresh momentum. **Entry:** Next candle after signal **Stop Loss:** Below recent consolidation low **Take Profit:** When extension area crosses back above zero, or when exit signal appears --- ### Perfect Short Entry (High Confidence ⭐) **Requirements (all must be true):** 1. ⚫→⚪ Squeeze just turned OFF (gray cross) 2. 📊 Momentum bars bright RED and falling 3. 🔺 Extension area ABOVE upper dashed line (overbought) 4. ⭐ Confluence: 3/5 or more timeframes agree (shown as "🔺" in table) **Visual:** Large red triangle appears **What this means:** Price was overbought across multiple timeframes, consolidated, and is now breaking down with fresh momentum. **Entry:** Next candle after signal **Stop Loss:** Above recent consolidation high **Take Profit:** When extension area crosses back below zero, or when exit signal appears --- ### Exit Signals #### Exit Long (Orange X) **Appears when:** - Extension area reaches upper dashed line (>2σ) - Momentum bars turning from bright green to dark green - Price losing upward velocity **Action:** Close 50-100% of position. Move stop to breakeven on remainder. #### Exit Short (Teal X) **Appears when:** - Extension area reaches lower dashed line (<-2σ) - Momentum bars turning from bright red to dark red - Price losing downward velocity **Action:** Close 50-100% of position. Move stop to breakeven on remainder. --- ### Medium Confidence Signals (Small Triangles) These appear when squeeze is OFF and momentum is directional, but: - Extension is only moderate (not extreme), OR - Confluence is weak (<3/5 timeframes) **How to trade:** - Use smaller position size (50% of normal) - Tighter stops - Only take if other factors align (support/resistance, volume, etc.) --- ## Trading Examples ### Example 1: Classic Squeeze Play into Trend ``` Step 1: CONSOLIDATION (💤) Chart: Price moving sideways for 10-20 candles Indicator: Black cross at zero (Squeeze ON) Extension: Yellow/Lime area near zero line Action: Set alert for Squeeze OFF Step 2: BREAKOUT (⚡) Chart: Strong green candle breaks resistance Indicator: Cross turns GRAY (Squeeze OFF) Bright GREEN momentum bars appear Extension area still near zero or slightly below Signal: Large green triangle appears Action: ENTER LONG Stop loss below consolidation Target: Extension upper line Step 3: TRENDING (↗️) Chart: Series of higher highs and higher lows Indicator: Momentum bars stay bright green Extension area rising toward upper line Area color transitions yellow → orange → red Action: HOLD, trailing stop Step 4: EXHAUSTION (🔴) Chart: Price makes new high but with smaller candle Indicator: Extension area touches upper dashed line Momentum bars turn DARK green (weakening) Orange X appears Table shows "EXHAUSTION BULL" Action: EXIT position Book profits Step 5: REVERSION Chart: Price falls back toward moving averages Indicator: Extension area shrinks back toward zero Red momentum bars appear Action: Wait for next setup ``` **Result:** Caught the entire trend from breakout to exhaustion. --- ### Example 2: Failed Breakout (What NOT to Trade) ``` Situation: - Squeeze OFF (gray cross) ✓ - Momentum bars bright green ✓ - BUT extension area ABOVE upper line (already overbought) ✗ - Confluence shows 1/5 (only one timeframe agrees) ✗ Indicator: Small green triangle (medium confidence) or no triangle What happens: Price makes small move up, then reverses Lesson: Don't chase extended moves even if squeeze fires. Wait for price to be on the RIGHT SIDE of the extension lines. ``` --- ### Example 3: Exhaustion Reversal Trade ``` Step 1: EXTENDED (⚠️) Chart: Strong uptrend for days Indicator: Extension area deep in red zone (>2σ) Momentum still bright green but starting to shorten Table: "EXTENDED UP" / "CAUTION LONG" Action: Watch closely, tighten stops Step 2: EXHAUSTION (🔴) Chart: Price makes final push but with decreasing volume Indicator: Momentum bars turn DARK green Orange X appears Table: "EXHAUSTION BULL" + "4/5 🔺" Action: CLOSE any longs Consider SHORT entry Step 3: SQUEEZE FORMS (Optional) Chart: Price starts consolidating Indicator: Cross turns BLACK (Squeeze ON) Extension area falling toward zero Action: Wait for Squeeze OFF to confirm reversal Step 4: BREAKOUT DOWN (⚡) Indicator: Cross turns GRAY Bright RED momentum bars Large red triangle appears Action: ENTER SHORT (reversal confirmed) ``` **Result:** Exited at the top, caught the reversal. --- ## Configuration Guide ### Recommended Settings by Timeframe #### For 4H Charts (Swing Trading) ``` Squeeze Settings: (defaults are fine) - BB Length: 20 - BB MultFactor: 2.0 - KC Length: 20 - KC MultFactor: 1.5 Exhaustion TFs: - TF1: 15m - TF2: 1h - TF3: 4h - TF4: 12h or Daily - TF5: Daily or Weekly Extension Threshold: 2.0σ Min Confluence: 3/5 ``` #### For 1H Charts (Day Trading) ``` Squeeze Settings: (defaults) Exhaustion TFs: - TF1: 5m - TF2: 15m - TF3: 1h - TF4: 4h - TF5: Daily Extension Threshold: 2.0σ Min Confluence: 3/5 ``` #### For 15m Charts (Scalping) ``` Squeeze Settings: - BB Length: 15 - KC Length: 15 Exhaustion TFs: - TF1: 1m - TF2: 5m - TF3: 15m - TF4: 1h - TF5: 4h Extension Threshold: 2.5σ (higher to avoid noise) Min Confluence: 4/5 (more strict) ``` --- ### Understanding the Table Located in top-right corner: | Row | Meaning | |-----|---------| | **Market State** | Current cycle phase (Consolidation/Breakout/Trending/Exhaustion) | | **Squeeze** | 🔴 ON / 🟢 OFF / 🔵 No | | **Momentum** | ↑ Bull / ↓ Bear / ~ Weak / — Neutral | | **Extension** | Actual value in standard deviations (σ) - NOT scaled | | **Confluence** | How many timeframes agree (X/5 🔺 or 🔻) | | **Velocity** | Speed of extension change (↑ increasing, ↓ decreasing) | | **ACTION** | What to do right now | **Most important rows:** 1. **Market State** - Quick glance at current cycle 2. **Confluence** - Determines signal quality 3. **ACTION** - Direct guidance --- ## Best Practices ### ✅ DO 1. **Wait for High Confidence signals** (large triangles) - Don't trade every small signal - Quality over quantity 2. **Use the complete cycle** - Enter on Breakout (⚡) - Hold through Trending (↗️/↘️) - Exit on Exhaustion (🔴/🟢) 3. **Respect confluence** - 4/5 or 5/5 = Excellent probability - 3/5 = Good probability - 1-2/5 = Skip 4. **Combine with price action** - Support/resistance levels - Volume confirmation - Candlestick patterns 5. **Set alerts** - "Squeeze OFF" - Don't miss breakouts - "HC Long Setup" / "HC Short Setup" - "Exit Long" / "Exit Short" 6. **Scale positions** - Enter 50% on signal - Add 25% if extension confirms - Add final 25% if momentum sustains 7. **Use proper risk management** - Stop loss: Below/above consolidation - Position size: 1-2% account risk - Take profit: Extension targets or signals --- ### ❌ DON'T 1. **Don't trade Consolidation state** - Black cross (Squeeze ON) = Wait mode - No signals during consolidation 2. **Don't chase Extended moves** - If extension already >2σ when Squeeze fires - Even if momentum looks good - Wait for reversion first 3. **Don't fight strong trends** - If extension is growing and momentum strong - Don't counter-trend trade - Wait for exhaustion signals 4. **Don't ignore velocity** - If velocity is ↑ and extension high = still dangerous - If velocity is ↓ and extension high = safer reversal 5. **Don't trade low confluence** - 1/5 or 2/5 = Different timeframes disagree - High chance of false signal 6. **Don't use blindly** - Check overall market context - Major news events can override signals - Trend on higher timeframe matters 7. **Don't overtrade** - Good setups are rare (that's why they work) - Wait for complete setup formation --- ## Quick Reference Card ### Signal Quality Checklist **⭐⭐⭐ PERFECT SETUP (Trade this)** - Squeeze just turned OFF (⚫→⚪) - Momentum bright and directional - Extension >2σ (OPPOSITE direction of entry) - Confluence ≥3/5 - Large triangle signal - Action says "LONG/SHORT ENTRY ⭐" **⭐⭐ GOOD SETUP (Trade with caution)** - Squeeze OFF - Momentum directional - Extension moderate - Confluence ≥3/5 - Small triangle or Action confirms **⭐ WEAK SETUP (Skip)** - Low confluence (<3/5) - Extension same direction as entry - Momentum weak or conflicting - Already in Extended/Exhaustion state --- ### State → Action Quick Guide | See This State | Do This | |---------------|---------| | 💤 CONSOLIDATION | Wait, set alerts | | ⚡ BREAKOUT | Enter in direction | | ↗️/↘️ TRENDING | Hold positions | | ⚠️ EXTENDED | Tighten stops, no new entries | | 🔴/🟢 EXHAUSTION | Exit, consider reversal | | — NEUTRAL | No trade | --- ## Troubleshooting **Q: Indicator shows Exhaustion but price keeps going** **A:** Check velocity and momentum. If still bright bars + velocity ↑, wait. True exhaustion needs momentum weakening. **Q: Too many false signals** **A:** Increase Min Confluence to 4/5. Use longer timeframe chart (4h instead of 1h). **Q: Missing good trades** **A:** Set alerts for "Squeeze OFF" and "HC Entry" signals. You can't watch charts 24/7. **Q: Extension area looks weird** **A:** Remember it's scaled 3x for visibility. Check table for actual values. **Q: Which timeframe is best?** **A:** 4H for swing trading, 1H for day trading. Lower = more signals but more noise. **Q: Can I use this with other indicators?** **A:** Yes! Combine with: - Volume profile - Support/resistance levels - Moving averages on chart - RSI for additional confirmation --- ## Final Thoughts This indicator gives you a complete picture of market structure: - **Where are we?** (Market State) - **Where are we going?** (Momentum) - **How far can it go?** (Extension) - **When will it reverse?** (Exhaustion) The key is **patience**. Wait for the complete setup: 1. Consolidation (⚫ Squeeze ON) 2. Breakout (⚪ Squeeze OFF) 3. Right extension direction (oversold for longs, overbought for shorts) 4. Strong confluence (3/5+) When all pieces align, you get high-probability trades with clear entries, targets, and exits. **Trade the cycle, not every wiggle.** --- ## Support & Updates For questions or suggestions, refer to the original script documentation or TradingView community. **Remember:** No indicator is perfect. Always use proper risk management and combine multiple forms of analysis. **Good trading! 📈**
Pine Script® インジケーター
Marianodipietraの投稿
MFI Volume Profile [Kodexius]The MFI Volume Profile indicator blends a classic volume profile with the Money Flow Index so you can see not only where volume traded, but also how strong the buying or selling pressure was at those prices. Instead of showing a simple horizontal histogram of volume, this tool adds a money flow dimension and turns the profile into a price volume momentum heat map. The script scans a user controlled lookback window and builds a set of price levels between the lowest and highest price in that period. For every bar inside that window, its volume is distributed across the price levels that the bar actually touched, and that volume is combined with the bar’s MFI value. This creates a volume weighted average MFI for each price level, so every row of the profile knows both how much volume traded there and what the typical money flow condition was when that volume appeared. On the chart, the indicator plots a stack of horizontal boxes to the right of current price. The length of each box represents the relative amount of volume at that price, while the color represents the average MFI there. Levels with stronger positive money flow will lean toward warmer shades, and levels with weaker or negative money flow will lean toward cooler or more neutral shades inside the configured MFI band. Each row is also labeled in the format Volume , so you can instantly read the exact volume and money flow value at that level instead of guessing. This gives you a detailed map of where the market really cared about price, and whether that interest came with strong inflow or outflow. It can help you spot areas of accumulation, distribution, absorption, or exhaustion, and it does so in a compact visual that sits next to price without cluttering the candles themselves. Features Combined volume profile and MFI weighting The indicator builds a volume profile over a user selected lookback and enriches each price row with a volume weighted average MFI. This lets you study both participation and money flow at the same price level. Volume distributed across the bar price range For every bar in the window, volume is not assigned to a single price. Instead, it is proportionally distributed across all price rows between the bar low and bar high. This creates a smoother and more realistic profile of where trading actually happened. MFI based color gradient between 30 and 70 Each price row is colored according to its average MFI. The gradient is anchored between MFI values of 30 and 70, which covers typical oversold, neutral and overbought zones. This makes strong demand or distribution areas easier to spot visually. Configurable structure resolution and depth Main user inputs are the lookback length, the number of rows, the width of the profile in bars, and the label text size. You can quickly switch between coarse profiles for a big picture and higher resolution profiles for detailed structure. Numeric labels with volume and MFI per row Every box is labeled with the total volume at that level and the average MFI for that level, in the format Volume . This gives you exact values while still keeping the visual profile clean and compact. Calculations Money Flow Index calculation currentMfi is calculated once using ta.mfi(hlc3, mfiLen) as usual, Creation of the profileBins array The script creates an array named profileBins that will hold one VPBin element per price row. Each VPBin contains volume which is the total volume accumulated at that price row mfiProduct which is the sum of volume multiplied by MFI for that row The loop; for i = 0 to rowCount - 1 by 1 array.push(profileBins, VPBin.new(0.0, 0.0)) pre allocates a clean structure with zero values for all rows. Finding highest and lowest price across the lookback The script starts from the current bar high and low, then walks backward through the lookback window for i = 0 to lookback - 1 by 1 highestPrice := math.max(highestPrice, high ) lowestPrice := math.min(lowestPrice, low ) After this loop, highestPrice and lowestPrice define the full price range covered by the chosen lookback. Price range and step size for rows The code computes float rangePrice = highestPrice - lowestPrice rangePrice := rangePrice == 0 ? syminfo.mintick : rangePrice float step = rangePrice / rowCount rangePrice is the total height of the profile in price terms. If the range is zero, the script replaces it with the minimum tick size for the symbol. Then step is the price height of each row. This step size is used to map any price into a row index. Processing each bar in the lookback For every bar index i inside the lookback, the script checks that currentMfi is not missing. If it is valid, it reads the bar high, low, volume and MFI float barTop = high float barBottom = low float barVol = volume float barMfi = currentMfi Mapping bar prices to bin indices The bar high and low are converted into row indices using the known lowestPrice and step int indexTop = math.floor((barTop - lowestPrice) / step) int indexBottom = math.floor((barBottom - lowestPrice) / step) Then the indices are clamped into valid bounds so they stay between zero and rowCount - 1. This ensures that every bar contributes only inside the profile range Splitting bar volume across all covered bins Once the top and bottom indices are known, the script calculates how many rows the bar spans int coveredBins = indexTop - indexBottom + 1 float volPerBin = barVol / coveredBins float mfiPerBin = volPerBin * barMfi Here the total bar volume is divided equally across all rows that the bar touches. For each of those rows, the same fraction of volume and volume times MFI is used. Accumulating into each VPBin Finally, a nested loop iterates from indexBottom to indexTop and updates the corresponding VPBin for k = indexBottom to indexTop by 1 VPBin binData = array.get(profileBins, k) binData.volume := binData.volume + volPerBin binData.mfiProduct := binData.mfiProduct + mfiPerBin Over all bars in the lookback window, each row builds up total volume at that price range total volume times MFI at that price range Later, during the drawing stage, the script computes avgMfi = bin.mfiProduct / bin.volume for each row. This is the volume weighted average MFI used both for coloring the box and for the numeric MFI value shown in the label Volume .
Pine Script® インジケーター
Kodexiusの投稿
Dimensional Resonance ProtocolDimensional Resonance Protocol 🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states. The Complexity Hypothesis: Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics. Takens' Embedding Theorem (1981): A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation. Mathematical Foundation: From single observable x(t), create embedding vectors: X(t) = Where: • d = Embedding dimension (default 5) • τ = Time delay (default 3 bars) • x(t) = Price or return at time t Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series. Why This Matters: Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect: • Stable regions : Predictable behavior (trade opportunities) • Chaotic regions : Unpredictable behavior (avoid trading) • Critical transitions : Phase changes between regimes Phase Space Magnitude Calculation: phase_magnitude = sqrt(Σ ² for i = 0 to d-1) This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation. 📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA) Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states? Recurrence Plot Foundation: A recurrence occurs when two phase space points are closer than threshold ε: R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0 This creates a binary matrix showing when the system revisits similar states. Key RQA Metrics: 1. Recurrence Rate (RR): RR = (Number of recurrent points) / (Total possible pairs) • RR near 0: System never repeats (highly stochastic) • RR = 0.1-0.3: Moderate recurrence (tradeable patterns) • RR > 0.5: System stuck in attractor (ranging market) • RR near 1: System frozen (no dynamics) Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck. 2. Determinism (DET): Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths). DET = (Recurrence points on diagonals) / (Total recurrence points) • DET < 0.3: Random dynamics • DET = 0.3-0.7: Moderate determinism (patterns with noise) • DET > 0.7: Strong determinism (technical patterns reliable) Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck). Threshold Selection (ε): Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns. 🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns. Algorithm (Bandt & Pompe, 2002): 1. Take overlapping windows of length n (default n=4) 2. For each window, record the rank order pattern Example: → pattern (ranks from lowest to highest) 3. Count frequency of each possible pattern 4. Calculate Shannon entropy of pattern distribution Mathematical Formula: H_perm = -Σ p(π) · ln(p(π)) Where π ranges over all n! possible permutations, p(π) is the probability of pattern π. Normalized to : H_norm = H_perm / ln(n!) Interpretation: • H < 0.3 : Very ordered, crystalline structure (strong trending) • H = 0.3-0.5 : Ordered regime (tradeable with patterns) • H = 0.5-0.7 : Moderate complexity (mixed conditions) • H = 0.7-0.85 : Complex dynamics (challenging to trade) • H > 0.85 : Maximum entropy (nearly random, avoid) Entropy Regime Classification: DRP classifies markets into five entropy regimes: • CRYSTALLINE (H < 0.3): Maximum order, persistent trends • ORDERED (H < 0.5): Clear patterns, momentum strategies work • MODERATE (H < 0.7): Mixed dynamics, adaptive required • COMPLEX (H < 0.85): High entropy, mean reversion better • CHAOTIC (H ≥ 0.85): Near-random, minimize trading Why Permutation Entropy? Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy: • Works directly on time series • Robust to monotonic transformations • Computationally efficient • Captures temporal structure, not just distribution • Immune to outliers (uses ranks, not values) ⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos. Physical Meaning: Two trajectories starting infinitely close will diverge at exponential rate e^(λt): Distance(t) ≈ Distance(0) × e^(λt) Interpretation: • λ > 0 : Positive Lyapunov exponent = CHAOS - Small errors grow exponentially - Long-term prediction impossible - System is sensitive, unpredictable - AVOID TRADING • λ ≈ 0 : Near-zero = CRITICAL STATE - Edge of chaos - Transition zone between order and disorder - Moderate predictability - PROCEED WITH CAUTION • λ < 0 : Negative Lyapunov exponent = STABLE - Small errors decay - Trajectories converge - System is predictable - OPTIMAL FOR TRADING Estimation Method: DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars): For each bar i in window: δ₀ = |x - x | (initial separation) δ₁ = |x - x | (previous separation) if δ₁ > 0: ratio = δ₀ / δ₁ log_ratios += ln(ratio) λ ≈ average(log_ratios) Stability Classification: • STABLE : λ < 0 (negative growth rate) • CRITICAL : |λ| < 0.1 (near neutral) • CHAOTIC : λ > 0.2 (strong positive growth) Signal Filtering: By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down. 📐 HIGUCHI FRACTAL DIMENSION Fractal dimension measures self-similarity and complexity of the price trajectory. Theoretical Background: A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve): • D ≈ 1.0 : Smooth, persistent trending • D ≈ 1.5 : Random walk (Brownian motion) • D ≈ 2.0 : Highly irregular, space-filling Higuchi Method (1988): For a time series of length N, construct k different curves by taking every k-th point: L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k) For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k): D = slope of log(L) vs log(1/k) Market Interpretation: • D < 1.35 : Strong trending, persistent (Hurst > 0.5) - TRENDING regime - Momentum strategies favored - Breakouts likely to continue • D = 1.35-1.45 : Moderate persistence - PERSISTENT regime - Trend-following with caution - Patterns have meaning • D = 1.45-1.55 : Random walk territory - RANDOM regime - Efficiency hypothesis holds - Technical analysis least reliable • D = 1.55-1.65 : Anti-persistent (mean-reverting) - ANTI-PERSISTENT regime - Oscillator strategies work - Overbought/oversold meaningful • D > 1.65 : Highly complex, choppy - COMPLEX regime - Avoid directional bets - Wait for regime change Signal Filtering: Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning. 🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer. Schreiber's Definition (2000): Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future: TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past) Where H is Shannon entropy. Key Properties: 1. Directional : TE(X→Y) ≠ TE(Y→X) in general 2. Non-linear : Detects complex causal relationships 3. Model-free : No assumptions about functional form 4. Lag-independent : Captures delayed causal effects Three Causal Flows Measured: 1. Volume → Price (TE_V→P): Measures how much volume patterns predict price changes. • TE > 0 : Volume provides predictive information about price - Institutional participation driving moves - Volume confirms direction - High reliability • TE ≈ 0 : No causal flow (weak volume/price relationship) - Volume uninformative - Caution on signals • TE < 0 (rare): Suggests price leading volume - Potentially manipulated or thin market 2. Volatility → Momentum (TE_σ→M): Does volatility expansion predict momentum changes? • Positive TE : Volatility precedes momentum shifts - Breakout dynamics - Regime transitions 3. Structure → Price (TE_S→P): Do support/resistance patterns causally influence price? • Positive TE : Structural levels have causal impact - Technical levels matter - Market respects structure Net Causal Flow: Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P • Net > +0.1 : Bullish causal structure • Net < -0.1 : Bearish causal structure • |Net| < 0.1 : Neutral/unclear causation Causal Gate: For signal confirmation, NEXUS requires: • Buy signals : TE_V→P > 0 AND Net_Flow > 0.05 • Sell signals : TE_V→P > 0 AND Net_Flow < -0.05 This ensures volume is actually driving price (causal support exists), not just correlated noise. Implementation Note: Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner. 🌊 HILBERT PHASE COHERENCE Phase coherence measures synchronization across market dimensions using Hilbert transform analysis. Hilbert Transform Theory: For a signal x(t), the Hilbert transform H (t) creates an analytic signal: z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t)) Where: • A(t) = Instantaneous amplitude • φ(t) = Instantaneous phase Instantaneous Phase: φ(t) = arctan(H (t) / x(t)) The phase represents where the signal is in its natural cycle—analogous to position on a unit circle. Four Dimensions Analyzed: 1. Momentum Phase : Phase of price rate-of-change 2. Volume Phase : Phase of volume intensity 3. Volatility Phase : Phase of ATR cycles 4. Structure Phase : Phase of position within range Phase Locking Value (PLV): For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization: PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩| Where ⟨·⟩ is time average over window. Interpretation: • PLV = 0 : Completely random phase relationship (no synchronization) • PLV = 0.5 : Moderate phase locking • PLV = 1 : Perfect synchronization (phases locked) Pairwise PLV Calculations: • PLV_momentum-volume : Are momentum and volume cycles synchronized? • PLV_momentum-structure : Are momentum cycles aligned with structure? • PLV_volume-structure : Are volume and structural patterns in phase? Overall Phase Coherence: Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3 Signal Confirmation: Emergence signals require coherence ≥ threshold (default 0.70): • Below 0.70: Dimensions not synchronized, no coherent market state • Above 0.70: Dimensions in phase, coherent behavior emerging Coherence Direction: The summed phase angles indicate whether synchronized dimensions point bullish or bearish: Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure) • Direction > 0 : Phases pointing upward (bullish synchronization) • Direction < 0 : Phases pointing downward (bearish synchronization) 🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence. Eight Components with Weights: 1. Phase Coherence (20%): Direct contribution: coherence × 0.20 Measures dimensional synchronization. 2. Entropy Regime (15%): Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0 Rewards low entropy (ordered, predictable states). 3. Lyapunov Stability (12%): • λ < 0 (stable): +0.12 • |λ| < 0.1 (critical): +0.08 • λ > 0.2 (chaotic): +0.0 Requires stable, predictable dynamics. 4. Fractal Dimension Trending (12%): Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0 Rewards trending fractal structure (D < 1.45). 5. Dimensional Resonance (12%): Contribution: |dimensional_resonance| × 0.12 Measures alignment across momentum, volume, structure, volatility dimensions. 6. Causal Flow Strength (9%): Contribution: |net_causal_flow| × 0.09 Rewards strong causal relationships. 7. Phase Space Embedding (10%): Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0 Rewards strong trajectory in reconstructed phase space. 8. Recurrence Quality (10%): Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8 Rewards deterministic patterns with moderate recurrence. Total Emergence Score: E = Σ(components) ∈ Capped at 1.0 maximum. Emergence Direction: Separate calculation determining bullish vs bearish: • Dimensional resonance sign • Net causal flow sign • Phase magnitude correlation with momentum Signal Threshold: Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals. Why Emergence Matters: Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order. These are the highest-probability trade opportunities because the entire system is resonating in the same direction. 🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE DRP generates two tiers of signals with different requirements: TIER 1: EMERGENCE SIGNALS (Primary) Requirements: 1. Emergence score ≥ threshold (default 0.75) 2. Phase coherence ≥ threshold (default 0.70) 3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish) 4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction 5. Stability zone (if enabled): λ < 0 or |λ| < 0.1 6. Price confirmation: Close > open (bulls) or close < open (bears) 7. Cooldown satisfied: bars_since_signal ≥ cooldown_period EMERGENCE BUY: • All above conditions met with bullish direction • Market has achieved coherent bullish state • Multiple dimensions synchronized upward EMERGENCE SELL: • All above conditions met with bearish direction • Market has achieved coherent bearish state • Multiple dimensions synchronized downward Premium Emergence: When signal_quality (emergence_score × phase_coherence) > 0.7: • Displayed as ★ star symbol • Highest conviction trades • Maximum dimensional alignment Standard Emergence: When signal_quality 0.5-0.7: • Displayed as ◆ diamond symbol • Strong signals but not perfect alignment TIER 2: RESONANCE SIGNALS (Secondary) Requirements: 1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish) 2. Fractal dimension < 1.5 (trending/persistent regime) 3. Price confirmation matches direction 4. NOT in chaotic regime (λ < 0.2) 5. Cooldown satisfied 6. NO emergence signal firing (resonance is fallback) RESONANCE BUY: • Dimensional alignment without full emergence • Trending fractal structure • Moderate conviction RESONANCE SELL: • Dimensional alignment without full emergence • Bearish resonance with trending structure • Moderate conviction Displayed as small ▲/▼ triangles with transparency. Signal Hierarchy: IF emergence conditions met: Fire EMERGENCE signal (★ or ◆) ELSE IF resonance conditions met: Fire RESONANCE signal (▲ or ▼) ELSE: No signal Cooldown System: After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions. Cooldown tracks using bar_index: bars_since_signal = current_bar_index - last_signal_bar_index cooldown_ok = bars_since_signal >= cooldown_period 🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY DRP provides rich visual feedback across four distinct layers: LAYER 1: COHERENCE FIELD (Background) Colored background intensity based on phase coherence: • No background : Coherence < 0.5 (incoherent state) • Faint glow : Coherence 0.5-0.7 (building coherence) • Stronger glow : Coherence > 0.7 (coherent state) Color: • Cyan/teal: Bullish coherence (direction > 0) • Red/magenta: Bearish coherence (direction < 0) • Blue: Neutral coherence (direction ≈ 0) Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible. LAYER 2: STABILITY/CHAOS ZONES Background color indicating Lyapunov regime: • Green tint (95% transparent): λ < 0, STABLE zone - Safe to trade - Patterns meaningful • Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone - Edge of chaos - Moderate risk • Red tint (85% transparent): λ > 0.2, CHAOTIC zone - Avoid trading - Unpredictable behavior LAYER 3: DIMENSIONAL RIBBONS Three EMAs representing dimensional structure: • Fast ribbon : EMA(8) in cyan/teal (fast dynamics) • Medium ribbon : EMA(21) in blue (intermediate) • Slow ribbon : EMA(55) in red/magenta (slow dynamics) Provides visual reference for multi-scale structure without cluttering with raw phase space data. LAYER 4: CAUSAL FLOW LINE A thicker line plotted at EMA(13) colored by net causal flow: • Cyan/teal : Net_flow > +0.1 (bullish causation) • Red/magenta : Net_flow < -0.1 (bearish causation) • Gray : |Net_flow| < 0.1 (neutral causation) Shows real-time direction of information flow. EMERGENCE FLASH: Strong background flash when emergence signals fire: • Cyan flash for emergence buy • Red flash for emergence sell • 80% transparency for visibility without obscuring price 📊 COMPREHENSIVE DASHBOARD Real-time monitoring of all complexity metrics: HEADER: • 🌀 DRP branding with gold accent CORE METRICS: EMERGENCE: • Progress bar (█ filled, ░ empty) showing 0-100% • Percentage value • Direction arrow (↗ bull, ↘ bear, → neutral) • Color-coded: Green/gold if active, gray if low COHERENCE: • Progress bar showing phase locking value • Percentage value • Checkmark ✓ if ≥ threshold, circle ○ if below • Color-coded: Cyan if coherent, gray if not COMPLEXITY SECTION: ENTROPY: • Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC) • Numerical value (0.00-1.00) • Color: Green (ordered), gold (moderate), red (chaotic) LYAPUNOV: • State (STABLE/CRITICAL/CHAOTIC) • Numerical value (typically -0.5 to +0.5) • Status indicator: ● stable, ◐ critical, ○ chaotic • Color-coded by state FRACTAL: • Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX) • Dimension value (1.0-2.0) • Color: Cyan (trending), gold (random), red (complex) PHASE-SPACE: • State (STRONG/ACTIVE/QUIET) • Normalized magnitude value • Parameters display: d=5 τ=3 CAUSAL SECTION: CAUSAL: • Direction (BULL/BEAR/NEUTRAL) • Net flow value • Flow indicator: →P (to price), P← (from price), ○ (neutral) V→P: • Volume-to-price transfer entropy • Small display showing specific TE value DIMENSIONAL SECTION: RESONANCE: • Progress bar of absolute resonance • Signed value (-1 to +1) • Color-coded by direction RECURRENCE: • Recurrence rate percentage • Determinism percentage display • Color-coded: Green if high quality STATE SECTION: STATE: • Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING • Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning) • Color-coded by state SIGNALS: • E: count of emergence signals • R: count of resonance signals ⚙️ KEY PARAMETERS EXPLAINED Phase Space Configuration: • Embedding Dimension (3-10, default 5): Reconstruction dimension - Low (3-4): Simple dynamics, faster computation - Medium (5-6): Balanced (recommended) - High (7-10): Complex dynamics, more data needed - Rule: d ≥ 2D+1 where D is true dimension • Time Delay (τ) (1-10, default 3): Embedding lag - Fast markets: 1-2 - Normal: 3-4 - Slow markets: 5-10 - Optimal: First minimum of mutual information (often 2-4) • Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity - Tight (0.01-0.05): Very similar states only - Medium (0.08-0.15): Balanced - Loose (0.20-0.50): Liberal matching Entropy & Complexity: • Permutation Order (3-7, default 4): Pattern length - Low (3): 6 patterns, fast but coarse - Medium (4-5): 24-120 patterns, balanced - High (6-7): 720-5040 patterns, fine-grained - Note: Requires window >> order! for stability • Entropy Window (15-100, default 30): Lookback for entropy - Short (15-25): Responsive to changes - Medium (30-50): Stable measure - Long (60-100): Very smooth, slow adaptation • Lyapunov Window (10-50, default 20): Stability estimation window - Short (10-15): Fast chaos detection - Medium (20-30): Balanced - Long (40-50): Stable λ estimate Causal Inference: • Enable Transfer Entropy (default ON): Causality analysis - Keep ON for full system functionality • TE History Length (2-15, default 5): Causal lookback - Short (2-4): Quick causal detection - Medium (5-8): Balanced - Long (10-15): Deep causal analysis • TE Discretization Bins (4-12, default 6): Binning granularity - Few (4-5): Coarse, robust, needs less data - Medium (6-8): Balanced - Many (9-12): Fine-grained, needs more data Phase Coherence: • Enable Phase Coherence (default ON): Synchronization detection - Keep ON for emergence detection • Coherence Threshold (0.3-0.95, default 0.70): PLV requirement - Loose (0.3-0.5): More signals, lower quality - Balanced (0.6-0.75): Recommended - Strict (0.8-0.95): Rare, highest quality • Hilbert Smoothing (3-20, default 8): Phase smoothing - Low (3-5): Responsive, noisier - Medium (6-10): Balanced - High (12-20): Smooth, more lag Fractal Analysis: • Enable Fractal Dimension (default ON): Complexity measurement - Keep ON for full analysis • Fractal K-max (4-20, default 8): Scaling range - Low (4-6): Faster, less accurate - Medium (7-10): Balanced - High (12-20): Accurate, slower • Fractal Window (30-200, default 50): FD lookback - Short (30-50): Responsive FD - Medium (60-100): Stable FD - Long (120-200): Very smooth FD Emergence Detection: • Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence - Sensitive (0.5-0.65): More signals - Balanced (0.7-0.8): Recommended - Strict (0.85-0.95): Rare signals • Require Causal Gate (default ON): TE confirmation - ON: Only signal when causality confirms - OFF: Allow signals without causal support • Require Stability Zone (default ON): Lyapunov filter - ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical) - OFF: Allow signals in chaotic regimes (risky) • Signal Cooldown (1-50, default 5): Minimum bars between signals - Fast (1-3): Rapid signal generation - Normal (4-8): Balanced - Slow (10-20): Very selective - Ultra (25-50): Only major regime changes Signal Configuration: • Momentum Period (5-50, default 14): ROC calculation • Structure Lookback (10-100, default 20): Support/resistance range • Volatility Period (5-50, default 14): ATR calculation • Volume MA Period (10-50, default 20): Volume normalization Visual Settings: • Customizable color scheme for all elements • Toggle visibility for each layer independently • Dashboard position (4 corners) and size (tiny/small/normal) 🎓 PROFESSIONAL USAGE PROTOCOL Phase 1: System Familiarization (Week 1) Goal: Understand complexity metrics and dashboard interpretation Setup: • Enable all features with default parameters • Watch dashboard metrics for 500+ bars • Do NOT trade yet Actions: • Observe emergence score patterns relative to price moves • Note coherence threshold crossings and subsequent price action • Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC) • Correlate Lyapunov state with signal reliability • Track which signals appear (emergence vs resonance frequency) Key Learning: • When does emergence peak? (usually before major moves) • What entropy regime produces best signals? (typically ORDERED or MODERATE) • Does your instrument respect stability zones? (stable λ = better signals) Phase 2: Parameter Optimization (Week 2) Goal: Tune system to instrument characteristics Requirements: • Understand basic dashboard metrics from Phase 1 • Have 1000+ bars of history loaded Embedding Dimension & Time Delay: • If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2) • If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5) • Sweet spot: 4-8 emergence signals per 100 bars Coherence Threshold: • Check dashboard: What's typical coherence range? • If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65 • If coherence often >0.80: Can raise threshold to 0.75-0.80 • Goal: Signals fire during top 20-30% of coherence values Emergence Threshold: • If too few signals: Lower to 0.65-0.70 • If too many signals: Raise to 0.80-0.85 • Balance with coherence threshold—both must be met Phase 3: Signal Quality Assessment (Weeks 3-4) Goal: Verify signals have edge via paper trading Requirements: • Parameters optimized per Phase 2 • 50+ signals generated • Detailed notes on each signal Paper Trading Protocol: • Take EVERY emergence signal (★ and ◆) • Optional: Take resonance signals (▲/▼) separately to compare • Use simple exit: 2R target, 1R stop (ATR-based) • Track: Win rate, average R-multiple, maximum consecutive losses Quality Metrics: • Premium emergence (★) : Should achieve >55% WR • Standard emergence (◆) : Should achieve >50% WR • Resonance signals : Should achieve >45% WR • Overall : If <45% WR, system not suitable for this instrument/timeframe Red Flags: • Win rate <40%: Wrong instrument or parameters need major adjustment • Max consecutive losses >10: System not working in current regime • Profit factor <1.0: No edge despite complexity analysis Phase 4: Regime Awareness (Week 5) Goal: Understand which market conditions produce best signals Analysis: • Review Phase 3 trades, segment by: - Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC) - Lyapunov state (STABLE vs CRITICAL vs CHAOTIC) - Fractal regime (TRENDING vs RANDOM vs COMPLEX) Findings (typical patterns): • Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal • Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal • Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these) Optimization: • If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70 • If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic • If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic Phase 5: Micro Live Testing (Weeks 6-8) Goal: Validate with minimal capital at risk Requirements: • Paper trading shows: WR >48%, PF >1.2, max DD <20% • Understand complexity metrics intuitively • Know which regimes work best from Phase 4 Setup: • 10-20% of intended position size • Focus on premium emergence signals (★) only initially • Proper stop placement (1.5-2.0 ATR) Execution Notes: • Emergence signals can fire mid-bar as metrics update • Use alerts for signal detection • Entry on close of signal bar or next bar open • DO NOT chase—if price gaps away, skip the trade Comparison: • Your live results should track within 10-15% of paper results • If major divergence: Execution issues (slippage, timing) or parameters changed Phase 6: Full Deployment (Month 3+) Goal: Scale to full size over time Requirements: • 30+ micro live trades • Live WR within 10% of paper WR • Profit factor >1.1 live • Max drawdown <15% • Confidence in parameter stability Progression: • Months 3-4: 25-40% intended size • Months 5-6: 40-70% intended size • Month 7+: 70-100% intended size Maintenance: • Weekly dashboard review: Are metrics stable? • Monthly performance review: Segmented by regime and signal type • Quarterly parameter check: Has optimal embedding/coherence changed? Advanced: • Consider different parameters per session (high vs low volatility) • Track phase space magnitude patterns before major moves • Combine with other indicators for confluence 💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS The Phase Space Revelation: Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D. The Permutation Entropy Discovery: Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering. The Lyapunov Filter Breakthrough: Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself. The Transfer Entropy Challenge: Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters. The Phase Coherence Insight: Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason. The Eight-Component Emergence Formula: Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it. The Cooldown Necessity: Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency. 🚨 LIMITATIONS & CRITICAL ASSUMPTIONS What This System IS NOT: • NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude. • NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty. • NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data. • NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections. • NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off. Core Assumptions: 1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly). 2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong. 3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise). 4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets). 5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive). 6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT). Performs Best On: • ES, NQ, RTY (major US index futures - high liquidity, clean volume data) • Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis) • Liquid commodities: CL (crude oil), GC (gold), NG (natural gas) • Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure) • Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation) Performs Poorly On: • Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis • Exotic forex pairs - erratic spreads, thin volume • Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis • Pre-market/after-hours - gappy, thin, different dynamics • Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions • Highly manipulated instruments - spoofing and layering create false coherence Known Weaknesses: • Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed. • Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument. • Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable. • Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive. • False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through. • Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this. • Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues. ⚠️ RISK DISCLOSURE Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results. The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless. Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals. Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size. The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it. Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe. The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic. Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations. Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up. Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk. The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes. By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses. 📁 DOCUMENTATION The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research: Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory. Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics. Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data. Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions. Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales. Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory. The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?). This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor. Multiple oscillator-type calculations contribute to dimensional analysis: Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection. Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized. Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed. Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional. The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states. While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space. Volatility analysis permeates the system: ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score. Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility). Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory. Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable. Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions. The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator. CLOSING STATEMENT DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence . This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity. When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance . These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state. Most indicators see shadows on the wall. DRP reconstructs the cave. "In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
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DskyzInvestmentsの投稿
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Luxy Super-Duper SuperTrend Predictor Engine and Buy/Sell signalA professional trend-following grading system that analyzes historical trend patterns to provide statistical duration estimates using advanced similarity matching and k-nearest neighbors analysis. Combines adaptive Supertrend with intelligent duration statistics, multi-timeframe confluence, volume confirmation, and quality scoring to identify high-probability setups with data-driven target ranges across all timeframes. Note: All duration estimates are statistical calculations based on historical data, not guarantees of future performance. WHAT MAKES THIS DIFFERENT Unlike traditional SuperTrend indicators that only tell you trend direction, this system answers the critical question: "What is the typical duration for trends like this?" The Statistical Analysis Engine: • Analyzes your chart's last 15+ completed SuperTrend trends (bullish and bearish separately) • Uses k-nearest neighbors similarity matching to find historically similar setups • Calculates statistical duration estimates based on current market conditions • Learns from estimation errors and adapts over time (Advanced mode) • Displays visual duration analysis box showing median, average, and range estimates • Tracks Statistical accuracy with backtest statistics Complete Trading System: • Statistical trend duration analysis with three intelligence levels • Adaptive Supertrend with dynamic ATR-based bands • Multi-timeframe confluence analysis (6 timeframes: 5M to 1W) • Volume confirmation with spike detection and momentum tracking • Quality scoring system (0-70 points) rating each setup • One-click preset optimization for all trading styles • Anti-repaint guarantee on all signals and duration estimates METHODOLOGY CREDITS This indicator's approach is inspired by proven trading methodologies from respected market educators: • Mark Minervini - Volatility Contraction Pattern (VCP) and pullback entry techniques • William O'Neil - Volume confirmation principles and institutional buying patterns (CANSLIM methodology) • Dan Zanger - Volatility expansion entries and momentum breakout strategies Important: These are educational references only. This indicator does not guarantee any specific trading results. Always conduct your own analysis and risk management. KEY FEATURES 1. TREND DURATION ANALYSIS SYSTEM - The Core Innovation The statistical analysis engine is what sets this indicator apart from standard SuperTrend systems. It doesn't just identify trend changes - it provides statistical analysis of potential duration. How It Works: Step 1: Historical Tracking • Automatically records every completed SuperTrend trend (duration in bars) • Maintains separate databases for bullish trends and bearish trends • Stores up to 15 most recent trends of each type • Captures market conditions at each trend flip: volume ratio, ATR ratio, quality score, price distance from SuperTrend, proximity to support/resistance Step 2: Similarity Matching (k-Nearest Neighbors) • When new trend begins, system compares current conditions to ALL historical flips • Calculates similarity score based on: - Volume similarity (30% weight) - Is volume behaving similarly? - Volatility similarity (30% weight) - Is ATR/volatility similar? - Quality similarity (20% weight) - Is setup strength comparable? - Distance similarity (10% weight) - Is price distance from ST similar? - Support/Resistance proximity (10% weight) - Similar structural context? • Selects the 15 MOST SIMILAR historical trends (not just all trends) • This is like asking: "When conditions looked like this before, how long did trends last?" Step 3: Statistical Analysis • Calculates median duration (most common outcome) • Calculates average duration (mean of similar trends) • Determines realistic range (min to max of similar trends) • Applies exponential weighting (recent trends weighted more heavily) • Outputs confidence-weighted statistical estimate Step 4: Advanced Intelligence (Advanced Mode Only) The Advanced mode applies five sophisticated multipliers to refine estimates: A) Market Structure Multiplier (±30%): • Detects nearby support/resistance levels using pivot detection • If flip occurs NEAR a key level: Estimate adjusted -30% (expect bounce/rejection) • If flip occurs in open space: Estimate adjusted +30% (clear path for continuation) • Uses configurable lookback period and ATR-based proximity threshold B) Asset Type Multiplier (±40%): • Adjusts duration estimates based on asset volatility characteristics • Small Cap / Biotech: +40% (explosive, extended moves) • Tech Growth: +20% (momentum-driven, longer trends) • Blue Chip / Large Cap: 0% (baseline, steady trends) • Dividend / Value: -20% (slower, grinding trends) • Cyclical: Variable based on macro regime • Crypto / High Volatility: +30% (parabolic potential) C) Flip Strength Multiplier (±20%): • Analyzes the QUALITY of the trend flip itself • Strong flip (high volume + expanding ATR + quality score 60+): +20% • Weak flip (low volume + contracting ATR + quality score under 40): -20% • Logic: Historical data shows that powerful flips tend to be followed by longer trends D) Error Learning Multiplier (±15%): • Tracks Statistical accuracy over last 10 completed trends • Calculates error ratio: (estimated duration / Actual Duration) • If system consistently over-estimates: Apply -15% correction • If system consistently under-estimates: Apply +15% correction • Learns and adapts to current market regime E) Regime Detection Multiplier (±20%): • Analyzes last 3 trends of SAME TYPE (bull-to-bull or bear-to-bear) • Compares recent trend durations to historical average • If recent trends 20%+ longer than average: +20% adjustment (trending regime detected) • If recent trends 20%+ shorter than average: -20% adjustment (choppy regime detected) • Detects whether market is in trending or mean-reversion mode Three analysis modes: SIMPLE MODE - Basic Statistics • Uses raw median of similar trends only • No multipliers, no adjustments • Best for: Beginners, clean trending markets • Fastest calculations, minimal complexity STANDARD MODE - Full Statistical Analysis • Similarity matching with k-nearest neighbors • Exponential weighting of recent trends • Median, average, and range calculations • Best for: Most traders, general market conditions • Balance of accuracy and simplicity ADVANCED MODE - Statistics + Intelligence • Everything in Standard mode PLUS • All 5 advanced multipliers (structure, asset type, flip strength, learning, regime) • Highest Statistical accuracy in testing • Best for: Experienced traders, volatile/complex markets • Maximum intelligence, most adaptive Visual Duration Analysis Box: When a new trend begins (SuperTrend flip), a box appears on your chart showing: • Analysis Mode (Simple / Standard / Advanced) • Number of historical trends analyzed • Median expected duration (most likely outcome) • Average expected duration (mean of similar trends) • Range (minimum to maximum from similar trends) • Advanced multipliers breakdown (Advanced mode only) • Backtest accuracy statistics (if available) The box extends from the flip bar to the estimated endpoint based on historical data, giving you a visual target for trend duration. Box updates in real-time as trend progresses. Backtest & Accuracy Tracking: • System backtests its own duration estimates using historical data • Shows accuracy metrics: how well duration estimates matched actual durations • Tracks last 10 completed duration estimates separately • Displays statistics in dashboard and duration analysis boxes • Helps you understand statistical reliability on your specific symbol/timeframe Anti-Repaint Guarantee: • duration analysis boxes only appear AFTER bar close (barstate.isconfirmed) • Historical duration estimates never disappear or change • What you see in history is exactly what you would have seen real-time • No future data leakage, no lookahead bias 2. INTELLIGENT PRESET CONFIGURATIONS - One-Click Optimization Unlike indicators that require tedious parameter tweaking, this system includes professionally optimized presets for every trading style. Select your approach from the dropdown and ALL parameters auto-configure. "AUTO (DETECT FROM TF)" - RECOMMENDED The smartest option: automatically selects optimal settings based on your chart timeframe. • 1m-5m charts → Scalping preset (ATR: 7, Mult: 2.0) • 15m-1h charts → Day Trading preset (ATR: 10, Mult: 2.5) • 2h-4h-D charts → Swing Trading preset (ATR: 14, Mult: 3.0) • W-M charts → Position Trading preset (ATR: 21, Mult: 4.0) Benefits: • Zero configuration - works immediately • Always matched to your timeframe • Switch timeframe = automatic adjustment • Perfect for traders who use multiple timeframes "SCALPING (1-5M)" - Ultra-Fast Signals Optimized for: 1-5 minute charts, high-frequency trading, quick profits Target holding period: Minutes to 1-2 hours maximum Best markets: High-volume stocks, major crypto pairs, active futures Parameter Configuration: • Supertrend: ATR 7, Multiplier 2.0 (very sensitive) • Volume: MA 10, High 1.8x, Spike 3.0x (catches quick surges) • Volume Momentum: AUTO-DISABLED (too restrictive for fast scalping) • Quality minimum: 40 points (accepts more setups) • Duration Analysis: Uses last 15 trends with heavy recent weighting Trading Logic: Speed over precision. Short ATR period and low multiplier create highly responsive SuperTrend. Volume momentum filter disabled to avoid missing fast moves. Quality threshold relaxed to catch more opportunities in rapid market conditions. Signals per session: 5-15 typically Hold time: Minutes to couple hours Best for: Active traders with fast execution "DAY TRADING (15M-1H)" - Balanced Approach Optimized for: 15-minute to 1-hour charts, intraday moves, session-based trading Target holding period: 30 minutes to 8 hours (within trading day) Best markets: Large-cap stocks, major indices, established crypto Parameter Configuration: • Supertrend: ATR 10, Multiplier 2.5 (balanced) • Volume: MA 20, High 1.5x, Spike 2.5x (standard detection) • Volume Momentum: 5/20 periods (confirms intraday strength) • Quality minimum: 50 points (good setups preferred) • Duration Analysis: Balanced weighting of recent vs historical Trading Logic: The most balanced configuration. ATR 10 with multiplier 2.5 provides steady trend following that avoids noise while catching meaningful moves. Volume momentum confirms institutional participation without being overly restrictive. Signals per session: 2-5 typically Hold time: 30 minutes to full day Best for: Part-time and full-time active traders "SWING TRADING (4H-D)" - Trend Stability Optimized for: 4-hour to Daily charts, multi-day holds, trend continuation Target holding period: 2-15 days typically Best markets: Growth stocks, sector ETFs, trending crypto, commodity futures Parameter Configuration: • Supertrend: ATR 14, Multiplier 3.0 (stable) • Volume: MA 30, High 1.3x, Spike 2.2x (accumulation focus) • Volume Momentum: 10/30 periods (trend stability) • Quality minimum: 60 points (high-quality setups only) • Duration Analysis: Favors consistent historical patterns Trading Logic: Designed for substantial trend moves while filtering short-term noise. Higher ATR period and multiplier create stable SuperTrend that won't flip on minor corrections. Stricter quality requirements ensure only strongest setups generate signals. Signals per week: 2-5 typically Hold time: Days to couple weeks Best for: Part-time traders, swing style "POSITION TRADING (D-W)" - Long-Term Trends Optimized for: Daily to Weekly charts, major trend changes, portfolio allocation Target holding period: Weeks to months Best markets: Blue-chip stocks, major indices, established cryptocurrencies Parameter Configuration: • Supertrend: ATR 21, Multiplier 4.0 (very stable) • Volume: MA 50, High 1.2x, Spike 2.0x (long-term accumulation) • Volume Momentum: 20/50 periods (major trend confirmation) • Quality minimum: 70 points (excellent setups only) • Duration Analysis: Heavy emphasis on multi-year historical data Trading Logic: Conservative approach focusing on major trend changes. Extended ATR period and high multiplier create SuperTrend that only flips on significant reversals. Very strict quality filters ensure signals represent genuine long-term opportunities. Signals per month: 1-2 typically Hold time: Weeks to months Best for: Long-term investors, set-and-forget approach "CUSTOM" - Advanced Configuration Purpose: Complete manual control for experienced traders Use when: You understand the parameters and want specific optimization Best for: Testing new approaches, unusual market conditions, specific instruments Full control over: • All SuperTrend parameters • Volume thresholds and momentum periods • Quality scoring weights • analysis mode and multipliers • Advanced features tuning Preset Comparison Quick Reference: Chart Timeframe: Scalping (1M-5M) | Day Trading (15M-1H) | Swing (4H-D) | Position (D-W) Signals Frequency: Very High | High | Medium | Low Hold Duration: Minutes | Hours | Days | Weeks-Months Quality Threshold: 40 pts | 50 pts | 60 pts | 70 pts ATR Sensitivity: Highest | Medium | Lower | Lowest Time Investment: Highest | High | Medium | Lowest Experience Level: Expert | Advanced | Intermediate | Beginner+ 3. QUALITY SCORING SYSTEM (0-70 Points) Every signal is rated in real-time across three dimensions: Volume Confirmation (0-30 points): • Volume Spike (2.5x+ average): 30 points • High Volume (1.5x+ average): 20 points • Above Average (1.0x+ average): 10 points • Below Average: 0 points Volatility Assessment (0-30 points): • Expanding ATR (1.2x+ average): 30 points • Rising ATR (1.0-1.2x average): 15 points • Contracting/Stable ATR: 0 points Volume Momentum (0-10 points): • Strong Momentum (1.2x+ ratio): 10 points • Rising Momentum (1.0-1.2x ratio): 5 points • Weak/Neutral Momentum: 0 points Score Interpretation: 60-70 points - EXCELLENT: • All factors aligned • High conviction setup • Maximum position size (within risk limits) • Primary trading opportunities 45-59 points - STRONG: • Multiple confirmations present • Above-average setup quality • Standard position size • Good trading opportunities 30-44 points - GOOD: • Basic confirmations met • Acceptable setup quality • Reduced position size • Wait for additional confirmation or trade smaller Below 30 points - WEAK: • Minimal confirmations • Low probability setup • Consider passing • Only for aggressive traders in strong trends Only signals meeting your minimum quality threshold (configurable per preset) generate alerts and labels. 4. MULTI-TIMEFRAME CONFLUENCE ANALYSIS The system can simultaneously analyze trend alignment across 6 timeframes (optional feature): Timeframes analyzed: • 5-minute (scalping context) • 15-minute (intraday momentum) • 1-hour (day trading bias) • 4-hour (swing context) • Daily (primary trend) • Weekly (macro trend) Confluence Interpretation: • 5-6/6 aligned - Very strong multi-timeframe agreement (highest confidence) • 3-4/6 aligned - Moderate agreement (standard setup) • 1-2/6 aligned - Weak agreement (caution advised) Dashboard shows real-time alignment count with color-coding. Higher confluence typically correlates with longer, stronger trends. 5. VOLUME MOMENTUM FILTER - Institutional Money Flow Unlike traditional volume indicators that just measure size, Volume Momentum tracks the RATE OF CHANGE in volume: How it works: • Compares short-term volume average (fast period) to long-term average (slow period) • Ratio above 1.0 = Volume accelerating (money flowing IN) • Ratio above 1.2 = Strong acceleration (institutional participation likely) • Ratio below 0.8 = Volume decelerating (money flowing OUT) Why it matters: • Confirms trend with actual money flow, not just price • Leading indicator (volume often leads price) • Catches accumulation/distribution before breakouts • More intuitive than complex mathematical filters Integration with signals: • Optional filter - can be enabled/disabled per preset • When enabled: Only signals with rising volume momentum fire • AUTO-DISABLED in Scalping mode (too restrictive for fast trading) • Configurable fast/slow periods per trading style 6. ADAPTIVE SUPERTREND MULTIPLIER Traditional SuperTrend uses fixed ATR multiplier. This system dynamically adjusts the multiplier (0.8x to 1.2x base) based on: • Trend Strength: Price correlation over lookback period • Volume Weight: Current volume relative to average Benefits: • Tighter bands in calm markets (less premature exits) • Wider bands in volatile conditions (avoids whipsaws) • Better adaptation to biotech, small-cap, and crypto volatility • Optional - can be disabled for classic constant multiplier 7. VISUAL GRADIENT RIBBON 26-layer exponential gradient fill between price and SuperTrend line provides instant visual trend strength assessment: Color System: • Green shades - Bullish trend + volume confirmation (strongest) • Blue shades - Bullish trend, normal volume • Orange shades - Bearish trend + volume confirmation • Red shades - Bearish trend (weakest) Opacity varies based on: • Distance from SuperTrend (farther = more opaque) • Volume intensity (higher volume = stronger color) The ribbon provides at-a-glance trend strength without cluttering your chart. Can be toggled on/off. 8. INTELLIGENT ALERT SYSTEM Two-tier alert architecture for flexibility: Automatic Alerts: • Fire automatically on BUY and SELL signals • Include full context: quality score, volume state, volume momentum • One alert per bar close (alert.freq_once_per_bar_close) • Message format: "BUY: Supertrend bullish + Quality: 65/70 | Volume: HIGH | Vol Momentum: STRONG (1.35x)" Customizable Alert Conditions: • Appear in TradingView's "Create Alert" dialog • Three options: BUY Signal Only, SELL Signal Only, ANY Signal (BUY or SELL) • Use TradingView placeholders: {{ticker}}, {{interval}}, {{close}}, {{time}} • Fully customizable message templates All alerts use barstate.isconfirmed - Zero repaint guarantee. 9. ANTI-REPAINT ARCHITECTURE Every component guaranteed non-repainting: • Entry signals: Only appear after bar close • duration analysis boxes: Created only on confirmed SuperTrend flips • Informative labels: Wait for bar confirmation • Alerts: Fire once per closed bar • Multi-timeframe data: Uses lookahead=barmerge.lookahead_off What you see in history is exactly what you would have seen in real-time. No disappearing signals, no changed duration estimates. HOW TO USE THE INDICATOR QUICK START - 3 Steps to Trading: Step 1: Select Your Trading Style Open indicator settings → "Quick Setup" section → Trading Style Preset dropdown Options: • Auto (Detect from TF) - RECOMMENDED: Automatically configures based on your chart timeframe • Scalping (1-5m) - For 1-5 minute charts, ultra-fast signals • Day Trading (15m-1h) - For 15m-1h charts, balanced approach • Swing Trading (4h-D) - For 4h-Daily charts, trend stability • Position Trading (D-W) - For Daily-Weekly charts, long-term trends • Custom - Manual configuration (advanced users only) Choose "Auto" and you're done - all parameters optimize automatically. Step 2: Understand the Signals BUY Signal (Green Triangle Below Price): • SuperTrend flipped bullish • Quality score meets minimum threshold (varies by preset) • Volume confirmation present (if filter enabled) • Volume momentum rising (if filter enabled) • duration analysis box shows expected trend duration SELL Signal (Red Triangle Above Price): • SuperTrend flipped bearish • Quality score meets minimum threshold • Volume confirmation present (if filter enabled) • Volume momentum rising (if filter enabled) • duration analysis box shows expected trend duration Duration Analysis Box: • Appears at SuperTrend flip (start of new trend) • Shows median, average, and range duration estimates • Extends to estimated endpoint based on historical data visually • Updates mode-specific intelligence (Simple/Standard/Advanced) Step 3: Use the Dashboard for Context Dashboard (top-right corner) shows real-time metrics: • Row 1 - Quality Score: Current setup rating (0-70) • Row 2 - SuperTrend: Direction and current level • Row 3 - Volume: Status (Spike/High/Normal/Low) with color • Row 4 - Volatility: State (Expanding/Rising/Stable/Contracting) • Row 5 - Volume Momentum: Ratio and trend • Row 6 - Duration Statistics: Accuracy metrics and track record Every cell has detailed tooltip - hover for full explanations. SIGNAL INTERPRETATION BY QUALITY SCORE: Excellent Setup (60-70 points): • Quality Score: 60-70 • Volume: Spike or High • Volatility: Expanding • Volume Momentum: Strong (1.2x+) • MTF Confluence (if enabled): 5-6/6 • Action: Primary trade - maximum position size (within risk limits) • Statistical reliability: Highest - duration estimates most accurate Strong Setup (45-59 points): • Quality Score: 45-59 • Volume: High or Above Average • Volatility: Rising • Volume Momentum: Rising (1.0-1.2x) • MTF Confluence (if enabled): 3-4/6 • Action: Standard trade - normal position size • Statistical reliability: Good - duration estimates reliable Good Setup (30-44 points): • Quality Score: 30-44 • Volume: Above Average • Volatility: Stable or Rising • Volume Momentum: Neutral to Rising • MTF Confluence (if enabled): 3-4/6 • Action: Cautious trade - reduced position size, wait for additional confirmation • Statistical reliability: Moderate - duration estimates less certain Weak Setup (Below 30 points): • Quality Score: Below 30 • Volume: Low or Normal • Volatility: Contracting or Stable • Volume Momentum: Weak • MTF Confluence (if enabled): 1-2/6 • Action: Pass or wait for improvement • Statistical reliability: Low - duration estimates unreliable USING duration analysis boxES FOR TRADE MANAGEMENT: Entry Timing: • Enter on SuperTrend flip (signal bar close) • duration analysis box appears simultaneously • Note the median duration - this is your expected hold time Profit Targets: • Conservative: Use MEDIAN duration as profit target (50% probability) • Moderate: Use AVERAGE duration (mean of similar trends) • Aggressive: Aim for MAX duration from range (best historical outcome) Position Management: • Scale out at median duration (take partial profits) • Trail stop as trend extends beyond median • Full exit at average duration or SuperTrend flip (whichever comes first) • Re-evaluate if trend exceeds estimated range analysis mode Selection: • Simple: Clean trending markets, beginners, minimal complexity • Standard: Most markets, most traders (recommended default) • Advanced: Volatile markets, complex instruments, experienced traders seeking highest accuracy Asset Type Configuration (Advanced Mode): If using Advanced analysis mode, configure Asset Type for optimal accuracy: • Small Cap: Stocks under $2B market cap, low liquidity • Biotech / Speculative: Clinical-stage pharma, penny stocks, high-risk • Blue Chip / Large Cap: S&P 500, mega-cap tech, stable large companies • Tech Growth: High-growth tech (TSLA, NVDA, growth SaaS) • Dividend / Value: Dividend aristocrats, value stocks, utilities • Cyclical: Energy, materials, industrials (macro-driven) • Crypto / High Volatility: Bitcoin, altcoins, highly volatile assets Correct asset type selection improves Statistical accuracy by 15-20%. RISK MANAGEMENT GUIDELINES: 1. Stop Loss Placement: Long positions: • Place stop below recent swing low OR • Place stop below SuperTrend level (whichever is tighter) • Use 1-2 ATR distance as guideline • Recommended: SuperTrend level (built-in volatility adjustment) Short positions: • Place stop above recent swing high OR • Place stop above SuperTrend level (whichever is tighter) • Use 1-2 ATR distance as guideline • Recommended: SuperTrend level 2. Position Sizing by Quality Score: • Excellent (60-70): Maximum position size (2% risk per trade) • Strong (45-59): Standard position size (1.5% risk per trade) • Good (30-44): Reduced position size (1% risk per trade) • Weak (Below 30): Pass or micro position (0.5% risk - learning trades only) 3. Exit Strategy Options: Option A - Statistical Duration-Based Exit: • Exit at median estimated duration (conservative) • Exit at average estimated duration (moderate) • Trail stop beyond average duration (aggressive) Option B - Signal-Based Exit: • Exit on opposite signal (SELL after BUY, or vice versa) • Exit on SuperTrend flip (trend reversal) • Exit if quality score drops below 30 mid-trend Option C - Hybrid (Recommended): • Take 50% profit at median estimated duration • Trail stop on remaining 50% using SuperTrend as trailing level • Full exit on SuperTrend flip or quality collapse 4. Trade Filtering: For higher win-rate (fewer trades, better quality): • Increase minimum quality score (try 60 for swing, 50 for day trading) • Enable volume momentum filter (ensure institutional participation) • Require higher MTF confluence (5-6/6 alignment) • Use Advanced analysis mode with appropriate asset type For more opportunities (more trades, lower quality threshold): • Decrease minimum quality score (40 for day trading, 35 for scalping) • Disable volume momentum filter • Lower MTF confluence requirement • Use Simple or Standard analysis mode SETTINGS OVERVIEW Quick Setup Section: • Trading Style Preset: Auto / Scalping / Day Trading / Swing / Position / Custom Dashboard & Display: • Show Dashboard (ON/OFF) • Dashboard Position (9 options: Top/Middle/Bottom + Left/Center/Right) • Text Size (Auto/Tiny/Small/Normal/Large/Huge) • Show Ribbon Fill (ON/OFF) • Show SuperTrend Line (ON/OFF) • Bullish Color (default: Green) • Bearish Color (default: Red) • Show Entry Labels - BUY/SELL signals (ON/OFF) • Show Info Labels - Volume events (ON/OFF) • Label Size (Auto/Tiny/Small/Normal/Large/Huge) Supertrend Configuration: • ATR Length (default varies by preset: 7-21) • ATR Multiplier Base (default varies by preset: 2.0-4.0) • Use Adaptive Multiplier (ON/OFF) - Dynamic 0.8x-1.2x adjustment • Smoothing Factor (0.0-0.5) - EMA smoothing applied to bands • Neutral Bars After Flip (0-10) - Hide ST immediately after flip Volume Momentum: • Enable Volume Momentum Filter (ON/OFF) • Fast Period (default varies by preset: 3-20) • Slow Period (default varies by preset: 10-50) Volume Analysis: • Volume MA Length (default varies by preset: 10-50) • High Volume Threshold (default: 1.5x) • Spike Threshold (default: 2.5x) • Low Volume Threshold (default: 0.7x) Quality Filters: • Minimum Quality Score (0-70, varies by preset) • Require Volume Confirmation (ON/OFF) Trend Duration Analysis: • Show Duration Analysis (ON/OFF) - Display duration analysis boxes • analysis mode - Simple / Standard / Advanced • Asset Type - 7 options (Small Cap, Biotech, Blue Chip, Tech Growth, Dividend, Cyclical, Crypto) • Use Exponential Weighting (ON/OFF) - Recent trends weighted more • Decay Factor (0.5-0.99) - How much more recent trends matter • Structure Lookback (3-30) - Pivot detection period for support/resistance • Proximity Threshold (xATR) - How close to level qualifies as "near" • Enable Error Learning (ON/OFF) - System learns from estimation errors • Memory Depth (3-20) - How many past errors to remember Box Visual Settings: • duration analysis box Border Color • duration analysis box Background Color • duration analysis box Text Color • duration analysis box Border Width • duration analysis box Transparency Multi-Timeframe (Optional Feature): • Enable MTF Confluence (ON/OFF) • Minimum Alignment Required (0-6) • Individual timeframe enable/disable toggles • Custom timeframe selection options All preset configurations override manual inputs except when "Custom" is selected. ADVANCED FEATURES 1. Scalpel Mode (Optional) Advanced pullback entry system that waits for healthy retracements within established trends before signaling entry: • Monitors price distance from SuperTrend levels • Requires pullback to configurable range (default: 30-50%) • Ensures trend remains intact before entry signal • Reduces whipsaw and false breakouts • Inspired by Mark Minervini's VCP pullback entries Best for: Swing traders and day traders seeking precision entries Scalpers: Consider disabling for faster entries 2. Error Learning System (Advanced analysis mode Only) The system learns from its own estimation errors: • Tracks last 10-20 completed duration estimates (configurable memory depth) • Calculates error ratio for each: estimated duration / Actual Duration • If system consistently over-estimates: Applies negative correction (-15%) • If system consistently under-estimates: Applies positive correction (+15%) • Adapts to current market regime automatically This self-correction mechanism improves accuracy over time as the system gathers more data on your specific symbol and timeframe. 3. Regime Detection (Advanced analysis mode Only) Automatically detects whether market is in trending or choppy regime: • Compares last 3 trends to historical average • Recent trends 20%+ longer → Trending regime (+20% to estimates) • Recent trends 20%+ shorter → Choppy regime (-20% to estimates) • Applied separately to bullish and bearish trends Helps duration estimates adapt to changing market conditions without manual intervention. 4. Exponential Weighting Option to weight recent trends more heavily than distant history: • Default decay factor: 0.9 • Recent trends get higher weight in statistical calculations • Older trends gradually decay in importance • Rationale: Recent market behavior more relevant than old data • Can be disabled for equal weighting 5. Backtest Statistics System backtests its own duration estimates using historical data: • Walks through past trends chronologically • Calculates what duration estimate WOULD have been at each flip • Compares to actual duration that occurred • Displays accuracy metrics in duration analysis boxes and dashboard • Helps assess statistical reliability on your specific chart Note: Backtest uses only data available AT THE TIME of each historical flip (no lookahead bias). TECHNICAL SPECIFICATIONS • Pine Script Version: v6 • Indicator Type: Overlay (draws on price chart) • Max Boxes: 500 (for duration analysis box storage) • Max Bars Back: 5000 (for comprehensive historical analysis) • Security Calls: 1 (for MTF if enabled - optimized) • Repainting: NO - All signals and duration estimates confirmed on bar close • Lookahead Bias: NO - All HTF data properly offset, all duration estimates use only historical data • Real-time Updates: YES - Dashboard and quality scores update live • Alert Capable: YES - Both automatic alerts and customizable alert conditions • Multi-Symbol: Works on stocks, crypto, forex, futures, indices Performance Optimization: • Conditional calculations (duration analysis can be disabled to reduce load) • Efficient array management (circular buffers for trend storage) • Streamlined gradient rendering (26 layers, can be toggled off) • Smart label cooldown system (prevents label spam) • Optimized similarity matching (analyzes only relevant trends) Data Requirements: • Minimum 50-100 bars for initial duration analysis (builds historical database) • Optimal: 500+ bars for robust statistical analysis • Longer history = more accurate duration estimates • Works on any timeframe from 1 minute to monthly KNOWN LIMITATIONS • Trending Markets Only: Performs best in clear trends. May generate false signals in choppy/sideways markets (use quality score filtering and regime detection to mitigate) • Lagging Nature: Like all trend-following systems, signals occur AFTER trend establishment, not at exact tops/bottoms. Use duration analysis boxes to set realistic profit targets. • Initial Learning Period: Duration analysis system requires 10-15 completed trends to build reliable historical database. Early duration estimates less accurate (first few weeks on new symbol/timeframe). • Visual Load: 26-layer gradient ribbon may slow performance on older devices. Disable ribbon if experiencing lag. • Statistical accuracy Variables: Duration estimates are statistical estimates, not guarantees. Accuracy varies by: - Market regime (trending vs choppy) - Asset volatility characteristics - Quality of historical pattern matches - Timeframe traded (higher TF = more reliable) • Not Best Suitable For: - Ultra-short-term scalping (sub-1-minute charts) - Mean-reversion strategies (designed for trend-following) - Range-bound trading (requires trending conditions) - News-driven spikes (estimates based on technical patterns, not fundamentals) FREQUENTLY ASKED QUESTIONS Q: Does this indicator repaint? A: Absolutely not. All signals, duration analysis boxes, labels, and alerts use barstate.isconfirmed checks. They only appear after the bar closes. What you see in history is exactly what you would have seen in real-time. Zero repaint guarantee. Q: How accurate are the trend duration estimates? A: Accuracy varies by mode, market conditions, and historical data quality: • Simple mode: 60-70% accuracy (within ±20% of actual duration) • Standard mode: 70-80% accuracy (within ±20% of actual duration) • Advanced mode: 75-85% accuracy (within ±20% of actual duration) Best accuracy achieved on: • Higher timeframes (4H, Daily, Weekly) • Trending markets (not choppy/sideways) • Assets with consistent behavior (Blue Chip, Large Cap) • After 20+ historical trends analyzed (builds robust database) Remember: All duration estimates are statistical calculations based on historical patterns, not guarantees. Q: Which analysis mode should I use? A: • Simple: Beginners, clean trending markets, want minimal complexity • Standard: Most traders, general market conditions (RECOMMENDED DEFAULT) • Advanced: Experienced traders, volatile/complex markets (biotech, small-cap, crypto), seeking maximum accuracy Advanced mode requires correct Asset Type configuration for optimal results. Q: What's the difference between the trading style presets? A: Each preset optimizes ALL parameters for a specific trading approach: • Scalping: Ultra-sensitive (ATR 7, Mult 2.0), more signals, shorter holds • Day Trading: Balanced (ATR 10, Mult 2.5), moderate signals, intraday holds • Swing Trading: Stable (ATR 14, Mult 3.0), fewer signals, multi-day holds • Position Trading: Very stable (ATR 21, Mult 4.0), rare signals, week/month holds Auto mode automatically selects based on your chart timeframe. Q: Should I use Auto mode or manually select a preset? A: Auto mode is recommended for most traders. It automatically matches settings to your timeframe and re-optimizes if you switch charts. Only use manual preset selection if: • You want scalping settings on a 15m chart (overriding auto-detection) • You want swing settings on a 1h chart (more conservative than auto would give) • You're testing different approaches on same timeframe Q: Can I use this for scalping and day trading? A: Absolutely! The preset system is specifically designed for all trading styles: • Select "Scalping (1-5m)" for 1-5 minute charts • Select "Day Trading (15m-1h)" for 15m-1h charts • Or use "Auto" mode and it configures automatically Volume momentum filter is auto-disabled in Scalping mode for faster signals. Q: What is Volume Momentum and why does it matter? A: Volume Momentum compares short-term volume (fast MA) to long-term volume (slow MA). It answers: "Is money flowing into this asset faster now than historically?" Why it matters: • Volume often leads price (early warning system) • Confirms institutional participation (smart money) • No lag like price-based indicators • More intuitive than complex mathematical filters When the ratio is above 1.2, you have strong evidence that institutions are accumulating (bullish) or distributing (bearish). Q: How do I set up alerts? A: Two options: Option 1 - Automatic Alerts: 1. Right-click on chart → Add Alert 2. Condition: Select this indicator 3. Choose "Any alert() function call" 4. Configure notification method (app, email, webhook) 5. You'll receive detailed alerts on every BUY and SELL signal Option 2 - Customizable Alert Conditions: 1. Right-click on chart → Add Alert 2. Condition: Select this indicator 3. You'll see three options in dropdown: - "BUY Signal" (long signals only) - "SELL Signal" (short signals only) - "ANY Signal" (both BUY and SELL) 4. Choose desired option and customize message template 5. Uses TradingView placeholders: {{ticker}}, {{close}}, {{time}}, etc. All alerts fire only on confirmed bar close (no repaint). Q: What is Scalpel Mode and should I use it? A: Scalpel Mode waits for healthy pullbacks within established trends before signaling entry. It reduces whipsaws and improves entry timing. Recommended ON for: • Swing traders (want precision entries on pullbacks) • Day traders (willing to wait for better prices) • Risk-averse traders (prefer fewer but higher-quality entries) Recommended OFF for: • Scalpers (need immediate entries, can't wait for pullbacks) • Momentum traders (want to enter on breakout, not pullback) • Aggressive traders (prefer more opportunities over precision) Q: Why do some duration estimates show wider ranges than others? A: Range width reflects historical trend variability: • Narrow range: Similar historical trends had consistent durations (high confidence) • Wide range: Similar historical trends had varying durations (lower confidence) Wide ranges often occur: • Early in analysis (fewer historical trends to learn from) • In volatile/choppy markets (inconsistent trend behavior) • On lower timeframes (more noise, less consistency) The median and average still provide useful targets even when range is wide. Q: Can I customize the dashboard position and appearance? A: Yes! Dashboard settings include: • Position: 9 options (Top/Middle/Bottom + Left/Center/Right) • Text Size: Auto, Tiny, Small, Normal, Large, Huge • Show/Hide: Toggle entire dashboard on/off Choose position that doesn't overlap important price action on your specific chart. Q: Which timeframe should I trade on? A: Depends on your trading style and time availability: • 1-5 minute: Active scalping, requires constant monitoring • 15m-1h: Day trading, check few times per session • 4h-Daily: Swing trading, check once or twice daily • Daily-Weekly: Position trading, check weekly General principle: Higher timeframes produce: • Fewer signals (less frequent) • Higher quality setups (stronger confirmations) • More reliable duration estimates (better statistical data) • Less noise (clearer trends) Start with Daily chart if new to trading. Move to lower timeframes as you gain experience. Q: Does this work on all markets (stocks, crypto, forex)? A: Yes, it works on all markets with trending characteristics: Excellent for: • Stocks (especially growth and momentum names) • Crypto (BTC, ETH, major altcoins) • Futures (indices, commodities) • Forex majors (EUR/USD, GBP/USD, etc.) Best results on: • Trending markets (not range-bound) • Liquid instruments (tight spreads, good fills) • Volatile assets (clear trend development) Less effective on: • Range-bound/sideways markets • Ultra-low volatility instruments • Illiquid small-caps (use caution) Configure Asset Type (in Advanced analysis mode) to match your instrument for best accuracy. Q: How many signals should I expect per day/week? A: Highly variable based on: By Timeframe: • 1-5 minute: 5-15 signals per session • 15m-1h: 2-5 signals per day • 4h-Daily: 2-5 signals per week • Daily-Weekly: 1-2 signals per month By Market Volatility: • High volatility = more SuperTrend flips = more signals • Low volatility = fewer flips = fewer signals By Quality Filter: • Higher threshold (60-70) = fewer but better signals • Lower threshold (30-40) = more signals, lower quality By Volume Momentum Filter: • Enabled = Fewer signals (only volume-confirmed) • Disabled = More signals (all SuperTrend flips) Adjust quality threshold and filters to match your desired signal frequency. Q: What's the difference between entry labels and info labels? A: Entry Labels (BUY/SELL): • Your primary trading signals • Based on SuperTrend flip + all confirmations (quality, volume, momentum) • Include quality score and confirmation icons • These are actionable entry points Info Labels (Volume Spike): • Additional market context • Show volume events that may support or contradict trend • 8-bar cooldown to prevent spam • NOT necessarily entry points - contextual information only Control separately: Can show entry labels without info labels (recommended for clean charts). Q: Can I combine this with other indicators? A: Absolutely! This works well with: • RSI: For divergences and overbought/oversold conditions • Support/Resistance: Confluence with key levels • Fibonacci Retracements: Pullback targets in Scalpel Mode • Price Action Patterns: Flags, pennants, cup-and-handle • MACD: Additional momentum confirmation • Bollinger Bands: Volatility context This indicator provides trend direction and duration estimates - complement with other tools for entry refinement and additional confluence. Q: Why did I get a low-quality signal? Can I filter them out? A: Yes! Increase the Minimum Quality Score in settings. If you're seeing signals with quality below your preference: • Day Trading: Set minimum to 50 • Swing Trading: Set minimum to 60 • Position Trading: Set minimum to 70 Only signals meeting the threshold will appear. This reduces frequency but improves win-rate. Q: How do I interpret the MTF Confluence count? A: Shows how many of 6 timeframes agree with current trend: • 6/6 aligned: Perfect agreement (extremely rare, highest confidence) • 5/6 aligned: Very strong alignment (high confidence) • 4/6 aligned: Good alignment (standard quality setup) • 3/6 aligned: Moderate alignment (acceptable) • 2/6 aligned: Weak alignment (caution) • 1/6 aligned: Very weak (likely counter-trend) Higher confluence typically correlates with longer, stronger trends. However, MTF analysis is optional - you can disable it and rely solely on quality scoring. Q: Is this suitable for beginners? A: Yes, but requires foundational knowledge: You should understand: • Basic trend-following concepts (higher highs, higher lows) • Risk management principles (position sizing, stop losses) • How to read candlestick charts • What volume and volatility mean Beginner-friendly features: • Auto preset mode (zero configuration) • Quality scoring (tells you signal strength) • Dashboard tooltips (hover for explanations) • duration analysis boxes (visual profit targets) Recommended for beginners: 1. Start with "Auto" or "Swing Trading" preset on Daily chart 2. Use Standard Analysis Mode (not Advanced) 3. Set minimum quality to 60 (fewer but better signals) 4. Paper trade first for 2-4 weeks 5. Study methodology references (Minervini, O'Neil, Zanger) Q: What is the Asset Type setting and why does it matter? A: Asset Type (in Advanced analysis mode) adjusts duration estimates based on volatility characteristics: • Small Cap: Explosive moves, extended trends (+30-40%) • Biotech / Speculative: Parabolic potential, news-driven (+40%) • Blue Chip / Large Cap: Baseline, steady trends (0% adjustment) • Tech Growth: Momentum-driven, longer trends (+20%) • Dividend / Value: Slower, grinding trends (-20%) • Cyclical: Macro-driven, variable (±10%) • Crypto / High Volatility: Parabolic potential (+30%) Correct configuration improves Statistical accuracy by 15-20%. Using Blue Chip settings on a biotech stock may underestimate trend length (you'll exit too early). Q: Can I backtest this indicator? A: Yes! TradingView's Strategy Tester works with this indicator's signals. To backtest: 1. Note the entry conditions (SuperTrend flip + quality threshold + filters) 2. Create a strategy script using same logic 3. Run Strategy Tester on historical data Additionally, the indicator includes BUILT-IN duration estimate validation: • System backtests its own duration estimates • Shows accuracy metrics in dashboard and duration analysis boxes • Helps assess reliability on your specific symbol/timeframe Q: Why does Volume Momentum auto-disable in Scalping mode? A: Scalping requires ultra-fast entries to catch quick moves. Volume Momentum filter adds friction by requiring volume confirmation before signaling, which can cause missed opportunities in rapid scalping. Scalping preset is optimized for speed and frequency - the filter is counterproductive for that style. It remains enabled for Day Trading, Swing Trading, and Position Trading presets where patience improves results. You can manually enable it in Custom mode if desired. Q: How much historical data do I need for accurate duration estimates? A: Minimum: 50-100 bars (indicator will function but duration estimates less reliable) Recommended: 500+ bars (robust statistical database) Optimal: 1000+ bars (maximum Statistical accuracy) More history = more completed trends = better pattern matching = more accurate duration estimates. New symbols or newly-switched timeframes will have lower Statistical accuracy initially. Allow 2-4 weeks for the system to build historical database. IMPORTANT DISCLAIMERS No Guarantee of Profit: This indicator is an educational tool and does not guarantee any specific trading results. All trading involves substantial risk of loss. Duration estimates are statistical calculations based on historical patterns and are not guarantees of future performance. Past Performance: Historical backtest results and Statistical accuracy statistics do not guarantee future performance. Market conditions change constantly. What worked historically may not work in current or future markets. Not Financial Advice: This indicator provides technical analysis signals and statistical duration estimates only. It is not financial, investment, or trading advice. Always consult with a qualified financial advisor before making investment decisions. Risk Warning: Trading stocks, options, futures, forex, and cryptocurrencies involves significant risk. You can lose all of your invested capital. Never trade with money you cannot afford to lose. Only risk capital you can lose without affecting your lifestyle. Testing Required: Always test this indicator on a demo account or with paper trading before risking real capital. Understand how it works in different market conditions. Verify Statistical accuracy on your specific instruments and timeframes before trusting it with real money. User Responsibility: You are solely responsible for your trading decisions. The developer assumes no liability for trading losses, incorrect duration estimates, software errors, or any other damages incurred while using this indicator. Statistical Estimation Limitations: Trend Duration estimates are statistical estimates based on historical pattern matching. They are NOT guarantees. Actual trend durations may differ significantly from duration estimates due to unforeseen news events, market regime changes, or lack of historical precedent for current conditions. CREDITS & ACKNOWLEDGMENTS Methodology Inspiration: • Mark Minervini - Volatility Contraction Pattern (VCP) concepts and pullback entry techniques • William O'Neil - Volume analysis principles and CANSLIM institutional buying patterns • Dan Zanger - Momentum breakout strategies and volatility expansion entries Technical Components: • SuperTrend calculation - Classic ATR-based trend indicator (public domain) • Statistical analysis - Standard median, average, range calculations • k-Nearest Neighbors - Classic machine learning similarity matching concept • Multi-timeframe analysis - Standard request.security implementation in Pine Script For questions, feedback, or support, please comment below or send a private message. Happy Trading!
Pine Script® インジケーター
orenluxyの投稿
42
Chop + MSS/FVG Retest (Ace v1.6) – IndicatorWhat this indicator does Name: Chop + MSS/FVG Retest (Ace v1.6) – Indicator This is an entry model helper, not just a BOS/MSS marker. It looks for clean trend-side setups by combining: MSS (Market Structure Shift) using swing highs/lows 3-bar ICT Fair Value Gaps (FVG) First retest back into the FVG A built-in chop / trend filter based on ATR and a moving average When everything lines up, it plots: L below the candle = Long candidate S above the candle = Short candidate You pair this with a higher-timeframe filter (like the Chop Meter 1H/30M/15M) to avoid pressing the button in garbage environments. How it works (simple explanation) Chop / Trend filter Computes ATR and compares each bar’s range to ATR. If the bar is small vs ATR → more likely CHOP. If the bar is big vs ATR → more likely TREND. Uses a moving average: Above MA + TREND → trendLong zone Below MA + TREND → trendShort zone MSS (Market Structure Shift) Uses swing highs/lows (left/right bars) to track the last significant high/low. Bullish MSS: close breaks above last swing high with displacement. Bearish MSS: close breaks below last swing low with displacement. Those events are marked as tiny triangles (MSS up/down). A MSS only stays “valid” for a certain number of bars (Bars after MSS allowed). 3-bar ICT FVG Bullish FVG: low > high → gap between bar 3 high and bar 2 low. Bearish FVG: high < low → gap between bar 3 low and bar 2 high. The indicator stores the FVG boundaries (top/bottom). Retest of FVG Watches for price to trade back into that gap (first touch). That retest is the “entry zone” after the MSS. Final Long / Short condition Long (L) prints when: Recent bullish MSS Bullish FVG has formed Price retests the bullish FVG Environment = trendLong (ATR + above MA) Not CHOP Short (S) prints when: Recent bearish MSS Bearish FVG has formed Price retests the bearish FVG Environment = trendShort (ATR + below MA) Not CHOP So the L/S markers are “model-approved entry candles”, not just any random BOS. Inputs / Settings Key inputs you’ll see: ATR length (chop filter) How many bars to use for ATR in the chop / trend filter. Lower = more sensitive, twitchy Higher = smoother, slower to change Max chop ratio If barRange / ATR is below this → treat as CHOP. Min trend ratio If barRange / ATR is above this → treat as TREND. Hide MSS/BOS marks in CHOP? ON = MSS triangles disappear when the bar is classified as CHOP Keeps your chart cleaner in consolidation Swing left / right bars Controls how tight or wide the swing highs/lows are for MSS: Smaller = more sensitive, more MSS points Larger = fewer, more significant swings Bars after MSS allowed How many bars after a MSS the indicator will still allow FVG entries. Small value (e.g. 10) = MSS must deliver quickly or it’s ignored. Larger (e.g. 20) = MSS idea stays “in play” longer. Visual RR (for info only) Just for plotting relative risk-reward in your head. This is not a strategy tester; it doesn’t manage positions. What you see on the chart Small green triangle up = Bullish MSS Small red triangle down = Bearish MSS “L” triangle below a bar = Long idea (MSS + FVG retest + trendLong + not chop) “S” triangle above a bar = Short idea (MSS + FVG retest + trendShort + not chop) Faint circle plots on price: When the filter sees CHOP When it sees Trend Long zone When it sees Trend Short zone You do not have to trade every L or S. They’re there to show “this is where the model would have considered an entry.” How to use it in your trading 1. Use it with a higher-timeframe filter Best practice: Use this with the Chop Meter 1H/30M/15M or some other HTF filter. Only consider L/S when: Chop Meter = TRADE / NORMAL, and This indicator prints L or S in the right location (premium/discount, near OB/FVG, etc.) If higher-timeframe says NO TRADE, you ignore all L/S. 2. Location > Signal Treat L/S as confirmation, not the whole story. For shorts (S): Look for premium zones (previous highs, OBs, fair value ranges above mid). Want purge / raid of liquidity + MSS down + bearish FVG retest → then S. For longs (L): Look for discount zones (previous lows, OBs/FVGs below mid). Want stop raid / purge low + MSS up + bullish FVG retest → then L. If you see L/S firing in the middle of a bigger range, that’s where you skip and let it go. 3. Instrument presets (example) You can tune the ATR/chop settings per instrument: MNQ (noisy, 1m chart): ATR length: 21 Max chop ratio: 0.90 Min trend ratio: 1.40 Bars after MSS allowed: 10 GOLD (cleaner, 3m chart): ATR length: 14 Max chop ratio: 0.80 Min trend ratio: 1.30 Bars after MSS allowed: 20 You can save those as presets in the TV settings for quick switching. 4. How to practice with it Open replay on a couple of days. Check Chop Meter → if NO TRADE, just observe. When Chop Meter says TRADE: Mark where L/S printed. Ask: Was this in premium/discount? Was there SMT / purge on HTF? Did the move actually deliver, or did it die? Screenshot the A+ L/S and the ugly ones; refine: ATR length Chop / trend thresholds MSS lookback Your goal is to get it to where: The L/S marks show up mostly in the same places your eye already likes, and you ignore the rest.
Pine Script® インジケーター
TIMEANDPRICEPRの投稿
1
ATH대비 지정하락률에 도착 시 매수 - 장기홀딩 선물 전략(ATH Drawdown Re-Buy Long Only)본 스크립트는 과거 하락 데이터를 이용하여, 정해진 하락 %가 발생하는 경우 자기 자본의 정해진 %만큼을 진입하게 설계되어진 스트레티지입니다. 레버리지를 사용할 수 있으며 기본적으로 셋팅해둔 값이 내장되어있습니다.(자유롭게 바꿔서 쓰시면 됩니다.) 추가적으로 2번의 진입 외에도 다른 진입 기준, 진입 %를 설정하실 수 있으며 - ChatGPT에게 요청하면 수정해줄 것입니다. 실제 사용용도로는 KillSwitch 기능을 꺼주세요. 바 돋보기 기능을 켜주세요. ATH Drawdown Re-Buy Long Only 전략 설명 1. 전략 개요 ATH Drawdown Re-Buy Long Only 전략은 자산의 역대 최고가(ATH, All-Time High)를 기준으로 한 하락폭(드로우다운)을 활용하여, 특정 구간마다 단계적으로 롱 포지션을 구축하는 자동 재매수(Long Only) 전략입니다. 본 전략은 다음과 같은 목적을 가지고 설계되었습니다. 급격한 조정 구간에서 체계적인 분할 매수 및 레버리지 활용 ATH를 기준으로 한 명확한 진입 규칙 제공 실시간으로 평단가 레버리지 청산가 추정 계좌 MDD 수익률 등을 시각적으로 제공하여 리스크와 포지션 상태를 직관적으로 확인할 수 있도록 지원 ※ 본 전략은 교육·연구·백테스트 용도로 제공되며, 어떠한 형태의 투자 권유 또는 수익을 보장하지 않습니다. 2. 전략의 핵심 개념 2-1. ATH(역대 최고가) 기준 드로우다운 전략은 차트 상에서 항상 가장 높은 고가(High)를 ATH로 기록합니다. 새로운 고점이 형성될 때마다 ATH를 갱신하고, 해당 ATH를 기준으로 다음을 계산합니다. 현재 바의 저가(Low)가 ATH에서 몇 % 하락했는지 현재 바의 종가(Close)가 ATH에서 몇 % 하락했는지 그리고 사전에 설정한 두 개의 드로우다운 구간에서 매수를 수행합니다. 1차 진입 구간: ATH 대비 X% 하락 시 2차 진입 구간: ATH 대비 Y% 하락 시 각 구간은 ATH가 새로 갱신될 때마다 한 번씩만 작동하며, 새로운 ATH가 생성되면 다시 “1차 / 2차 진입 가능 상태”로 초기화됩니다. 2-2. 첫 포지션 100% / 300% 특수 규칙 이 전략의 중요한 특징은 **“첫 포지션 진입 시의 예외 규칙”**입니다. 전략이 현재 어떠한 포지션도 들고 있지 않은 상태에서 최초로 롱 포지션을 진입하는 시점(첫 포지션)에 대해: 기본적으로는 **자산의 100%**를 기준으로 포지션을 구축하지만, 만약 그 순간의 가격이 ATH 대비 설정값 이상(예: 약 –72.5% 이상 하락한 상황) 이라면 → 자산의 300% 규모로 첫 포지션을 진입하도록 설계되어 있습니다. 이 규칙은 다음과 같이 동작합니다. 첫 진입이 1차 드로우다운 구간에서 발생하든, 첫 진입이 2차 드로우다운 구간에서 발생하든, 현재 하락폭이 설정된 기준 이상(예: –72.5% 이상) 이라면 → “이 정도 하락이면 첫 진입부터 더 공격적으로 들어간다”는 의미로 300% 규모로 진입 그 이하의 하락폭이라면 → 첫 진입은 100% 규모로 제한 즉, 전략은 다음 두 가지 모드로 동작합니다. 일반적인 상황의 첫 진입: 자산의 100% 심각한 드로우다운 구간에서의 첫 진입: 자산의 300% 이 특수 규칙은 깊은 하락에서는 공격적으로, 평소에는 상대적으로 보수적으로 진입하도록 설계된 것입니다. 3. 전략 동작 구조 3-1. 매수 조건 차트 상 High 기준으로 ATH를 추적합니다. 각 바마다 해당 ATH에서의 하락률을 계산합니다. 사용자가 설정한 두 개의 드로우다운 구간(예시): 1차 구간: 예를 들어 ATH – 50% 2차 구간: 예를 들어 ATH – 72.5% 각 구간에 대해 다음과 같은 조건을 확인합니다. “이번 ATH 구간에서 아직 해당 구간 매수를 한 적이 없는 상태”이고, 현재 바의 저가(Low)가 해당 구간 가격 이하를 찍는 순간 → 해당 바에서 매수 조건 충족으로 간주 실제 주문은: 해당 구간 가격에 맞춰 롱 포지션 진입(리밋/시장가 기반 시뮬레이션) 으로 처리됩니다. 3-2. ATH 갱신과 진입 기회 리셋 차트 상에서 새로운 고점(High)이 기존 ATH를 넘어서는 순간, ATH가 갱신되고, 1차 / 2차 진입 여부를 나타내는 내부 플래그가 초기화됩니다. 이를 통해, 시장이 새로운 고점을 돌파해 나갈 때마다, 해당 구간에서 다시 한 번씩 1차·2차 드로우다운 진입 기회를 갖게 됩니다. 4. 포지션 사이징 및 레버리지 4-1. 계좌 자산(Equity) 기준 포지션 크기 결정 전략은 현재 계좌 자산을 다음과 같이 정의하여 사용합니다. 현재 자산 = 초기 자본 + 실현 손익 + 미실현 손익 각 진입 구간에서의 포지션 가치는 다음과 같이 결정됩니다. 1차 진입 구간: “자산의 몇 %를 사용할지”를 설정값으로 입력 설정된 퍼센트를 계좌 자산에 곱한 뒤, 다시 전략 내 레버리지 배수(Leverage) 를 곱하여 실제 포지션 가치를 계산 2차 진입 구간: 동일한 방식으로, 독립된 퍼센트 설정값을 사용 즉, 포지션 가치는 다음과 같이 계산됩니다. 포지션 가치 = 현재 자산 × (해당 구간 설정 % / 100) × 레버리지 배수 그리고 이를 해당 구간의 진입 가격으로 나누어 실제 수량(토큰 단위) 를 산출합니다. 4-2. 첫 포지션의 예외 처리 (100% / 300%) 첫 포지션에 대해서는 위의 일반적인 퍼센트 설정 대신, 다음과 같은 고정 비율이 사용됩니다. 기본: 자산의 100% 규모로 첫 포지션 진입 단, 진입 시점의 ATH 대비 하락률이 설정값 이상(예: –72.5% 이상) 일 경우 → 자산의 300% 규모로 첫 포지션 진입 이때 역시 다음 공식을 사용합니다. 포지션 가치 = 현재 자산 × (100% 또는 300%) × 레버리지 그리고 이를 가격으로 나누어 실제 진입 수량을 계산합니다. 이 규칙은: 첫 진입이 1차 구간이든 2차 구간이든 동일하게 적용되며, “충분히 깊은 하락 구간에서는 첫 진입부터 더 크게, 평소에는 비교적 보수적으로” 라는 운용 철학을 반영합니다. 4-3. 실레버리지(Real Leverage)의 추적 전략은 각 바 단위로 다음을 추적합니다. 바가 시작할 때의 기존 포지션 크기 해당 바에서 새로 진입한 수량 이를 바탕으로, 진입이 발생한 시점에 다음을 계산합니다. 실제 레버리지 = (포지션 가치 / 현재 자산) 그리고 차트 상에 예를 들어: Lev 2.53x 와 같은 형식의 레이블로 표시합니다. 이를 통해, 매수 시점마다 실제 계좌 레버리지가 어느 정도였는지를 직관적으로 확인할 수 있습니다. 5. 시각화 및 모니터링 요소 5-1. 차트 상 시각 요소 전략은 차트 위에 다음과 같은 정보를 직접 표시합니다. ATH 라인 High 기준으로 계산된 역대 최고가를 주황색 선으로 표시 평단가(평균 진입가) 라인 현재 보유 포지션이 있을 때, 해당 포지션의 평균 진입가를 노란색 선으로 표시 추정 청산가(고정형 청산가) 라인 포지션 수량이 변화하는 시점을 감지하여, 당시의 평단가와 실제 레버리지를 이용해 근사적인 청산가를 계산 이를 빨간색 선으로 차트에 고정 표시 포지션이 없거나 레버리지가 1배 이하인 경우에는 청산가 라인을 제거 매수 마커 및 레이블 1차/2차 매수 조건이 충족될 때마다 해당 지점에 매수 마커를 표시 "Buy XX% @ 가격", "Lev XXx" 형태의 라벨로 진입 비율과 당시 레버리지를 함께 시각화 레이블의 위치는 설정에서 선택 가능: 바 아래 (Below Bar) 바 위 (Above Bar) 실제 가격 위치 (At Price) 5-2. 우측 상단 정보 테이블 차트 우측 상단에는 현재 계좌·포지션 상태를 요약한 정보 테이블이 표시됩니다. 대표적으로 다음 항목들이 포함됩니다. Pos Qty (Token) 현재 보유 중인 포지션 수량(토큰 기준, 절대값 기준) Pos Value (USDT) 현재 포지션의 시장 가치 (수량 × 현재 가격) Leverage (Now) 현재 실레버리지 (포지션 가치 / 현재 자산) DD from ATH (%) 현재 가격 기준, 최근 ATH에서의 하락률(%) Avg Entry 현재 포지션의 평균 진입 가격 PnL (%) 현재 포지션 기준 미실현 손익률(%) Max DD (Equity %) 전략 전체 기간 동안 기록된 계좌 기준 최대 손실(MDD, Max Drawdown) Last Entry Price 가장 최근에 포지션을 추가로 진입한 직후의 평균 진입 가격 Last Entry Lev 위 “Last Entry Price” 시점에서의 실레버리지 Liq Price (Fixed) 위에서 설명한 고정형 추정 청산가 Return from Start (%) 전략 시작 시점(초기 자본) 대비 현재 계좌 자산의 총 수익률(%) 이 테이블을 통해 사용자는: 현재 계좌와 포지션의 상태 리스크 수준 누적 성과 를 직관적으로 파악할 수 있습니다. 6. 시간 필터 및 라벨 옵션 6-1. 전략 동작 기간 설정 전략은 옵션으로 특정 기간에만 전략을 동작시키는 시간 필터를 제공합니다. “Use Date Range” 옵션을 활성화하면: 시작 시각과 종료 시각을 지정하여 해당 구간에 한해서만 매매가 발생하도록 제한 옵션을 비활성화하면: 전략은 전체 차트 구간에서 자유롭게 동작 6-2. 진입 라벨 위치 설정 사용자는 매수/레버리지 라벨의 위치를 선택할 수 있습니다. 바 아래 (Below Bar) 바 위 (Above Bar) 실제 가격 위치 (At Price) 이를 통해 개인 취향 및 차트 가독성에 맞추어 시각화 방식을 유연하게 조정할 수 있습니다. 7. 활용 대상 및 사용 예시 본 전략은 다음과 같은 목적에 적합합니다. 현물 또는 선물 롱 포지션 기준 장기·스윙 관점 추매 전략 백테스트 “고점 대비 하락률”을 기준으로 한 규칙 기반 운용 아이디어 검증 레버리지 사용 시 계좌 레버리지·청산가·MDD를 동시에 모니터링하고자 하는 경우 특정 자산에 대해 “새로운 고점이 형성될 때마다 일정한 규칙으로 깊은 조정 구간에서만 분할 진입하고자 할 때” 실거래에 그대로 적용하기보다는, 전략 아이디어 검증 및 리스크 프로파일 분석, 자신의 성향에 맞는 파라미터 탐색 용도로 사용하는 것을 권장합니다. 8. 한계 및 유의사항 백테스트 결과는 미래 성과를 보장하지 않습니다. 과거 데이터에 기반한 시뮬레이션일 뿐이며, 실제 시장에서는 유동성 슬리피지 수수료 체계 강제청산 규칙 등 다양한 변수가 존재합니다. 청산가는 단순화된 공식에 따른 추정치입니다. 거래소별 실제 청산 규칙, 유지 증거금, 수수료, 펀딩비 등은 본 전략의 계산과 다를 수 있으며, 청산가 추정 라인은 참고용 지표일 뿐입니다. 레버리지 및 진입 비율 설정에 따라 손실 폭이 매우 커질 수 있습니다. 특히 **“첫 포지션 300% 진입”**과 같이 매우 공격적인 설정은 시장 급락 시 계좌 손실과 청산 리스크를 크게 증가시킬 수 있으므로 신중한 검토가 필요합니다. 실거래 연동 시에는 별도의 리스크 관리가 필수입니다. 개별 손절 기준 포지션 상한선 전체 포트폴리오 내 비중 관리 등 본 전략 외부에서 추가적인 안전장치가 필요합니다. 9. 결론 ATH Drawdown Re-Buy Long Only 전략은 단순한 “저가 매수”를 넘어서, ATH 기준으로 드로우다운을 구조적으로 활용하고, 첫 포지션에 대한 **특수 규칙(100% / 300%)**을 적용하며, 레버리지·청산가·MDD·수익률을 통합적으로 시각화함으로써, 하락 구간에서의 규칙 기반 롱 포지션 구축과 리스크 모니터링을 동시에 지원하는 전략입니다. 사용자는 본 전략을 통해: 자신의 시장 관점과 리스크 허용 범위에 맞는 드로우다운 구간 진입 비율 레버리지 설정 다양한 시나리오에 대한 백테스트와 분석 을 수행할 수 있습니다. 다시 한 번 강조하지만, 본 전략은 연구·학습·백테스트를 위한 도구이며, 실제 투자 판단과 책임은 전적으로 사용자 본인에게 있습니다. /ENG Version. This script is designed to use historical drawdown data and automatically enter positions when a predefined percentage drop from the all-time high occurs, using a predefined percentage of your account equity. You can use leverage, and default parameter values are provided out of the box (you can freely change them to suit your style). In addition to the two main entry levels, you can add more entry conditions and custom entry percentages – just ask ChatGPT to modify the script. For actual/live usage, please turn OFF the KillSwitch function and turn ON the Bar Magnifier feature. ATH Drawdown Re-Buy Long Only Strategy 1. Strategy Overview The ATH Drawdown Re-Buy Long Only strategy is an automatic re-buy (Long Only) system that builds long positions step-by-step at specific drawdown levels, based on the asset’s all-time high (ATH) and its subsequent drawdown. This strategy is designed with the following goals: Systematic scaled buying and leverage usage during sharp correction periods Clear, rule-based entry logic using drawdowns from ATH Real-time visualization of: Average entry price Leverage Estimated liquidation price Account MDD (Max Drawdown) Return / performance This allows traders to intuitively monitor both risk and position status. ※ This strategy is provided for educational, research, and backtesting purposes only. It does not constitute investment advice and does not guarantee any profits. 2. Core Concepts 2-1. Drawdown from ATH (All-Time High) On the chart, the strategy always tracks the highest high as the ATH. Whenever a new high is made, ATH is updated, and based on that ATH the following are calculated: How many percent the current bar’s Low is below the ATH How many percent the current bar’s Close is below the ATH Using these, the strategy executes buys at two predefined drawdown zones: 1st entry zone: When price drops X% from ATH 2nd entry zone: When price drops Y% from ATH Each zone is allowed to trigger only once per ATH cycle. When a new ATH is created, the “1st / 2nd entry possible” flags are reset, and new opportunities open up for that ATH leg. 2-2. Special Rule for the First Position (100% / 300%) A key feature of this strategy is the special rule for the very first position. When the strategy currently holds no position and is about to open the first long position: Under normal conditions, it builds the position using 100% of account equity. However, if at that moment the price has dropped by at least a predefined threshold from ATH (e.g. around –72.5% or more), → the strategy will open the first position using 300% of account equity. This rule works as follows: Whether the first entry happens at the 1st drawdown zone or at the 2nd drawdown zone, If the current drawdown from ATH is at or below the threshold (e.g. –72.5% or worse), → the strategy interprets this as “a sufficiently deep crash” and opens the initial position with 300% of equity. If the drawdown is less severe than the threshold, → the first entry is capped at 100% of equity. So the strategy has two modes for the first entry: Normal market conditions: 100% of equity Deep drawdown conditions: 300% of equity This special rule is intended to be aggressive in extremely deep crashes while staying more conservative in normal corrections. 3. Strategy Logic & Execution 3-1. Entry Conditions The strategy tracks the ATH using the High price. For each bar, it calculates the drawdown from ATH. The user defines two drawdown zones, for example: 1st zone: ATH – 50% 2nd zone: ATH – 72.5% For each zone, the strategy checks: If no buy has been executed yet for that zone in the current ATH leg, and If the current bar’s Low touches or falls below that zone’s price level, → That bar is considered to have triggered a buy condition. Order simulation: The strategy simulates entering a long position at that zone’s price level (using a limit/market-like approximation for backtesting). 3-2. ATH Reset & Entry Opportunity Reset When a new High goes above the previous ATH: The ATH is updated to this new high. Internal flags that track whether the 1st and 2nd entries have been used are reset. This means: Each time the market makes a new ATH, The strategy once again has a fresh opportunity to execute 1st and 2nd drawdown entries for that new ATH leg. 4. Position Sizing & Leverage 4-1. Position Size Based on Account Equity The strategy defines current equity as: Current Equity = Initial Capital + Realized PnL + Unrealized PnL For each entry zone, the position value is calculated as follows: The user inputs: “What % of equity to use at this zone” The strategy: Multiplies current equity by that percentage Then multiplies by the strategy’s leverage factor Thus: Position Value = Current Equity × (Zone % / 100) × Leverage Finally, this position value is divided by the entry price to determine the actual position size in tokens. 4-2. Exception for the First Position (100% / 300%) For the very first position (when there is no open position), the strategy does not use the zone % parameters. Instead, it uses fixed ratios: Default: Enter the first position with 100% of equity. If the drawdown from ATH at that moment is greater than or equal to a predefined threshold (e.g. –72.5% or more) → Enter the first position with 300% of equity. The position value is computed as: Position Value = Current Equity × (100% or 300%) × Leverage Then it is divided by the entry price to obtain the token quantity. This rule: Applies regardless of whether the first entry occurs at the 1st zone or 2nd zone. Embeds the philosophy: “In very deep crashes, go much larger on the first entry; otherwise, stay more conservative.” 4-3. Tracking Real Leverage On each bar, the strategy tracks: The existing position size at the start of the bar The newly added size (if any) on that bar When a new entry occurs, it calculates the real leverage at that moment: Real Leverage = (Position Value / Current Equity) This is then displayed on the chart as a label, for example: Lev 2.53x This makes it easy to see the actual leverage level at each entry point. 5. Visualization & Monitoring 5-1. On-Chart Visual Elements The strategy plots the following directly on the chart: ATH Line The all-time high (based on High) is plotted as an orange line. Average Entry Price Line When a position is open, the average entry price of that position is plotted as a yellow line. Estimated Liquidation Price (Fixed) Line The strategy detects when the position size changes. At each size change, it uses the current average entry price and real leverage to compute an approximate liquidation price. This “fixed liquidation price” is then plotted as a red line on the chart. If there is no position, or if leverage is 1x or lower, the liquidation line is removed. Entry Markers & Labels When 1st/2nd entry conditions are met, the strategy: Marks the entry point on the chart. Displays labels such as "Buy XX% @ Price" and "Lev XXx", showing both entry percentage and real leverage at that time. The label placement is configurable: Below Bar Above Bar At Price 5-2. Information Table (Top-Right Panel) In the top-right corner of the chart, the strategy displays a summary table of the current account and position status. It typically includes: Pos Qty (Token) Absolute size of the current position (in tokens) Pos Value (USDT) Market value of the current position (qty × current price) Leverage (Now) Current real leverage (position value / current equity) DD from ATH (%) Current drawdown (%) from the latest ATH, based on current price Avg Entry Average entry price of the current position PnL (%) Unrealized profit/loss (%) of the current position Max DD (Equity %) The maximum equity drawdown (MDD) recorded over the entire backtest period Last Entry Price Average entry price immediately after the most recent add-on entry Last Entry Lev Real leverage at the time of the most recent entry Liq Price (Fixed) The fixed estimated liquidation price described above Return from Start (%) Total return (%) of equity compared to the initial capital Through this table, users can quickly grasp: Current account and position status Current risk level Cumulative performance 6. Time Filters & Label Options 6-1. Strategy Date Range Filter The strategy provides an option to restrict trading to a specific time range. When “Use Date Range” is enabled: You can specify start and end timestamps. The strategy will only execute trades within that range. When this option is disabled: The strategy operates over the entire chart history. 6-2. Entry Label Placement Users can customize where entry/leverage labels are drawn: Below Bar (Below Bar) Above Bar (Above Bar) At the actual price level (At Price) This allows you to adjust visualization according to personal preference and chart readability. 7. Use Cases & Applications This strategy is suitable for the following purposes: Long-term / swing-style re-buy strategies for spot or futures long positions Testing rule-based strategies that rely on “drawdown from ATH” as a main signal Monitoring account leverage, liquidation price, and MDD when using leverage Handling situations where, for a given asset: “Every time a new ATH is formed, you want to wait for deep corrections and enter only at specific drawdown zones” It is generally recommended to use this strategy not as a direct plug-and-play live system, but as a tool for: Strategy idea validation Risk profile analysis Parameter exploration to match your personal risk tolerance and style 8. Limitations & Warnings Backtest results do not guarantee future performance. They are based on historical data only. In live markets, additional factors exist: Liquidity Slippage Fee structures Exchange-specific liquidation rules Funding fees, etc. The liquidation price is only an approximate estimate, derived from a simplified formula. Actual liquidation rules, maintenance margin requirements, fees, and other details differ by exchange. The liquidation line should be treated as a reference indicator, not an exact guarantee. Depending on the configured leverage and entry percentages, losses can be very large. In particular, extremely aggressive settings such as “first position 300% of equity” can greatly increase the risk of large account drawdowns and liquidation during sharp market crashes. Use such settings with extreme caution. For live trading, additional risk management is essential: Your own stop-loss rules Maximum position size limits Portfolio-level exposure controls And other external safety mechanisms beyond this strategy 9. Conclusion The ATH Drawdown Re-Buy Long Only strategy goes beyond simple “buy the dip” logic. It: Systematically utilizes drawdowns from ATH as a structural signal Applies a special first-position rule (100% / 300%) Integrates visualization of leverage, liquidation price, MDD, and returns All of this supports rule-based long position building in drawdown phases and comprehensive risk monitoring. With this strategy, users can: Explore different: Drawdown zones Entry percentages Leverage levels Run various backtests and scenario analyses Better understand the risk/return profile that fits their own market view and risk tolerance Once again, this strategy is intended for research, learning, and backtesting only. All real trading decisions and their consequences are solely the responsibility of the user.
Pine Script® ストラテジー
White_light_の投稿
3
Dobrusky Pressure CoreWhat it does & who it’s for Dobrusky Pressure Core is a volume by time replacement for traders who care about which side actually controls each bar. Instead of just plotting total volume, it splits each bar into estimated buy vs sell pressure and overlays a custom, session-aware volume baseline. It’s built for discretionary traders who want more nuanced volume context for entries, breakouts, and pullbacks. Core ideas Buy/sell pressure split: Each bar’s volume is broken into estimated buying and selling pressure. Dominant side highlighting: The dominant side (buy or sell) is always displayed starting from the bottom of the bar, so you can quickly see who “owned” that bar. Median-based baseline: Uses the median of the last N bars (50 by default) to build a robust volume baseline that’s less sensitive to one-off spikes. Session-aware behavior: Baseline is calculated from Regular Trading Hours (RTH) by default, with an option to include Extended Hours (ETH) and a control to force Regular data on higher timeframes. Volume regimes: Three multipliers (1x, 1.5x, 2x by default) show normal, high, and extreme volume regions. Flexible display: Baseline can be shown as lines or as columns behind the volume, with full color customization. How the pressure logic works For each bar, the script: Adjusts the range for gaps relative to the prior close so the “true” traded range is more consistent. Computes buy pressure as a proportion of the adjusted range from low to close. Defines sell pressure as: total volume minus buy pressure. Marks the bar as buy-dominant if buy pressure ≥ sell pressure, otherwise sell-dominant, and colors the dominant side from the bottom to at least the midpoint using the selected buy/sell colors. In practice, this turns basic volume columns into bars where the internal split and dominant side are clearly visible, helping you judge whether aggressive buyers or sellers truly controlled the bar instead of just looking at the price action. Volume baseline & session logic The script builds a session-aware baseline from recent volume: Baseline length: A rolling window (default 50 bars) is used to compute a median volume value instead of a simple moving average. RTH-only by default: By default, the baseline is built from Regular Trading Hours bars only. During extended hours, the baseline effectively “freezes” at the last RTH-derived value unless you choose to include extended session data. Extended mode: If you select Extended mode, the script builds separate rolling baselines for RTH and ETH trading, using the appropriate one depending on the current session. Force Regular Above Timeframe: On timeframes equal to or higher than your chosen threshold, the baseline automatically uses Regular session data, even if Extended is selected. Multipliers: Three adjustable multipliers (1x, 1.5x, 2x by default) create normal, high, and extreme volume bands for quick identification. This lets you choose whether you want a pure RTH reference or a baseline that adapts to extended-session activity. Example ways to use it 1. Replace standard volume bars Add Dobrusky Pressure Core to your volume pane and hide the default volume if you prefer a clean look. Use the colors and split to see at a glance whether buyers or sellers were dominant on each bar. 2. Pressure confirmation for entries For longs (example concept; adapt to your own rules): Require that the entry bar’s buy pressure is greater than the previous bar’s sell pressure , or If the entry and prior bar are both buy-dominant, require that the entry bar has more buy pressure than the prior bar. This helps avoid taking a long when buying pressure is clearly fading relative to what sellers recently showed. A mirrored idea can be used for short setups with sell pressure. 3. Context from baseline multipliers Use ~1x baseline as “normal” volume. Watch for bars at or above 1.5x baseline when you want to see increased participation. Treat 2x baseline and above as “extreme” volume zones that may mark climactic or especially important bars. In practice, the baseline and multipliers are best used as context and filters, not as rigid rules. Settings overview Display - Show Volume Baseline: toggle the baseline and its levels on or off. - Baseline Display: choose between Line or Bars for the baseline visualization. Baseline Calculation - Length: lookback for the median baseline (default 50, configurable). - Baseline Session Data: choose Regular or Extended to control which session data feeds the baseline. Session Controls - Regular Session (Local to TZ): define your RTH window (e.g., 0930-1600). - Session Time Zone: choose the time zone used for that window. - Force Regular Above Timeframe: on higher timeframes, force the baseline to use Regular session data only. Baseline Levels - Show Level x Multiplier 1/2/3: toggle each volume regime level. - Multiplier 1/2/3: define what you consider normal, high, and extreme volume (defaults: 1.0, 1.5, 2.0). Colors - Buy Volume / Sell Volume: choose colors for buy and sell pressure. - Baseline Bars (Base / x2 / x3): colors when the baseline is drawn as columns. - Baseline Line (Base / x2 / x3): colors when the baseline is drawn as lines. Limitations & best practices This is a decision-support and visualization tool, not a buy/sell signal generator. Best suited to markets where volume data is meaningful (e.g., index futures, liquid equities, liquid crypto). The usefulness of any volume-based metric depends on the underlying data feed and instrument structure. Always combine pressure and baseline context with your own strategy, risk management, and testing. Originality Most volume tools either show total volume only or compare it to a simple moving average. Dobrusky Pressure Core combines: An intrabar buy/sell pressure split based on a gap-adjusted price range. A median-based, configurable baseline built from session-specific data. Session-aware behavior that keeps the baseline focused on Regular hours by default, with the option to incorporate Extended hours and force Regular data on higher timeframes. The goal is to give traders a richer, session-aware view of participation and pressure that standard volume bars and simple SMA overlays don’t provide, while keeping everything transparent and open-source so users can review and adapt the logic.
Pine Script® インジケーター
adobtradesの投稿
MA SMART Angle ### 📊 WHAT IS MA SMART ANGLE? **MA SMART Angle** is an advanced momentum and trend detection indicator that analyzes the angles (slopes) of multiple moving averages to generate clear, non-repainting BUY and SELL signals. **Original Concept Credit:** This indicator builds upon the "MA Angles" concept originally created by **JD** (also known as Duyck). The core angle calculation methodology and Jurik Moving Average (JMA) implementation by **Everget** are preserved from the original open-source work. The angle calculation formula was contributed by **KyJ**. This enhanced version is published with respect to the open-source nature of the original indicator. Original indicator reference: "ma angles - JD" by Duyck --- ## 🎯 ORIGINALITY & VALUE PROPOSITION ### **What Makes This Different from the Original:** While the original "MA Angles" by **JD** provided excellent angle visualization, it lacked actionable entry signals. **MA SMART Angle** addresses this by adding: **1. Clear Entry/Exit Signals** - Explicit BUY/SELL arrows based on angle crossovers, momentum confirmation, and MA alignment - No guessing when to enter trades - the indicator tells you exactly when conditions align **2. Non-Repainting Logic** - All signals use confirmed historical data (shifted by 2 bars minimum) - Critical for backtesting reliability and live trading confidence - Original indicator could repaint signals on current bar **3. Dual Signal System** - **Simple Mode:** More frequent signals based on angle crossovers + momentum (for active traders) - **Strict Mode:** Requires full multi-MA alignment + momentum confirmation (for conservative traders) - Adaptable to different trading styles and risk tolerances **4. Smart Signal Filtering** - **Anti-spam cooldown:** Prevents duplicate signals within configurable bar count - **No-trade zone detection:** Filters out low-conviction sideways markets automatically - **Multi-timeframe MA alignment:** Ensures all moving averages agree on direction before signaling **5. Enhanced Visualization** - Large, clear BUY/SELL arrows with descriptive labels - Color-coded backgrounds for market states (trending vs. ranging) - Momentum histogram showing acceleration/deceleration in real-time - Live status table displaying trend strength, angle value, momentum, and MA alignment **6. Professional Alert System** - Four distinct alert conditions: BUY Signal, SELL Signal, Strong BUY, Strong SELL - Enables automated trade notifications and strategy integration **7. Modified MA Periods** - Original used EMA(27), EMA(83), EMA(278) - Enhanced version uses faster EMA(3), EMA(8), EMA(13) for more responsive signals - Better suited for modern volatile markets and shorter timeframes --- ## 📐 HOW IT WORKS - TECHNICAL EXPLANATION ### **Core Methodology:** The indicator calculates angles (slopes) for five key moving averages: - **JMA (Jurik Moving Average)** - Smooth, lag-reduced trend line (original implementation by **Everget**) - **JMA Fast** - Responsive momentum indicator with higher power parameter - **MA27 (EMA 3)** - Primary fast-moving average for signal generation - **MA83 (EMA 8)** - Medium-term trend confirmation - **MA278 (EMA 13)** - Slower trend filter ### **Angle Calculation Formula (by KyJ):** ``` angle = arctan((MA - MA ) / ATR(14)) × (180 / π) ``` **Why ATR normalization?** - Makes angles comparable across different instruments (forex, stocks, crypto) - Makes angles comparable across different timeframes - Accounts for volatility - a 10-point move in different assets has different significance **Angle Interpretation:** - **> 15°** = Strong trend (momentum accelerating) - **0° to 15°** = Weak trend (momentum present but moderate) - **-2° to +2°** = No-trade zone (sideways/choppy market) - **< -15°** = Strong downtrend ### **Signal Generation Logic:** #### **BUY Signal Conditions:** 1. MA27 angle crosses above 0° (upward momentum initiates) 2. All three EMAs (3, 8, 13) pointing upward (trend alignment confirmed) 3. Momentum is positive for 2+ bars (acceleration, not deceleration) 4. Angle exceeds minimum threshold (not in no-trade zone) 5. Cooldown period passed (prevents signal spam) #### **SELL Signal Conditions:** 1. MA27 angle crosses below 0° (downward momentum initiates) 2. All three EMAs pointing downward (downtrend alignment) 3. Momentum is negative for 2+ bars 4. Angle below negative threshold (not in no-trade zone) 5. Cooldown period passed #### **Strong BUY+ / SELL+ Signals:** Additional entry opportunities when JMA Fast crosses JMA Slow while maintaining strong directional angle - indicates momentum acceleration within established trend. --- ## 🔧 HOW TO USE ### **Recommended Settings by Trading Style:** **Scalpers / Day Traders:** - Signal Type: **Simple** - Minimum Angle: **3-5°** - Cooldown Bars: **3-5 bars** - Timeframes: 1m, 5m, 15m **Swing Traders:** - Signal Type: **Strict** - Minimum Angle: **7-10°** - Cooldown Bars: **8-12 bars** - Timeframes: 1H, 4H, Daily **Position Traders:** - Signal Type: **Strict** - Minimum Angle: **10-15°** - Cooldown Bars: **15-20 bars** - Timeframes: Daily, Weekly ### **Parameter Descriptions:** **1. Source** (default: OHLC4) - Price data used for MA calculations - OHLC4 provides smoothest angles - Close is more responsive but noisier **2. Threshold for No-Trade Zones** (default: 2°) - Angles below this are considered sideways/ranging - Increase for stricter filtering of choppy markets - Decrease to allow signals in quieter trending periods **3. Signal Type** (Simple vs. Strict) - **Simple:** Angle crossover OR (trend + momentum) - **Strict:** Angle crossover AND all MAs aligned AND momentum confirmed - Start with Simple, switch to Strict if too many false signals **4. Minimum Angle for Signal** (default: 5°) - Only generate signals when angle exceeds this threshold - Higher values = stronger trends required - Lower values = more sensitive to momentum changes **5. Cooldown Bars** (default: 5) - Minimum bars between consecutive signals - Prevents spam during volatile chop - Scale with your timeframe (higher TF = more bars) **6. Color Bars** (default: true) - Colors chart bars based on signal state - Green = bullish conditions, Red = bearish conditions - Can disable if you prefer clean price bars **7. Background Colors** - **Yellow background** = No-trade zone (low angle, ranging market) - **Green flash** = BUY signal generated - **Red flash** = SELL signal generated - All customizable or can be disabled --- ## 📊 INTERPRETING THE INDICATOR ### **Visual Elements:** **Main Chart Window:** - **Thick Lime/Fuchsia Line** = MA27 angle (primary signal line) - **Medium Green/Red Line** = MA83 angle (trend confirmation) - **Thin Green/Red Line** = MA278 angle (slow trend filter) - **Aqua/Orange Line** = JMA Fast (momentum detector) - **Green/Red Area** = JMA slope (overall trend context) - **Blue/Purple Histogram** = Momentum (angle acceleration/deceleration) **Signal Arrows:** - **Large Green ▲ "BUY"** = Primary buy signal (all conditions met) - **Small Green ▲ "BUY+"** = Strong momentum buy (JMA fast cross) - **Large Red ▼ "SELL"** = Primary sell signal (all conditions met) - **Small Red ▼ "SELL+"** = Strong momentum sell (JMA fast cross) **Status Table (Top Right):** - **Angle:** Current MA27 angle in degrees - **Trend:** Classification (STRONG UP/DOWN, UP/DOWN, FLAT) - **Momentum:** Acceleration state (ACCEL UP/DN, Up/Down) - **MAs:** Alignment status (ALL UP/DOWN, Mixed) - **Zone:** Trading zone status (ACTIVE vs. NO TRADE) - **Last:** Bars since last signal ### **Trading Strategies:** **Strategy 1: Pure Signal Following** - Enter LONG on BUY signal - Exit on SELL signal - Use stop-loss at recent swing low/high - Works best on trending instruments **Strategy 2: Confirmation with Price Action** - Wait for BUY signal + bullish candlestick pattern - Wait for SELL signal + bearish candlestick pattern - Increases win rate by filtering premature signals - Recommended for beginners **Strategy 3: Momentum Acceleration** - Use BUY+/SELL+ signals for adding to positions - Only take these in direction of primary signal - Scalp quick moves during momentum spikes - For experienced traders **Strategy 4: Mean Reversion in No-Trade Zones** - When status shows "NO TRADE", fade extremes - Wait for angle to exit no-trade zone for reversal - Contrarian approach for range-bound markets - Requires tight stops --- ## ⚠️ LIMITATIONS & DISCLAIMERS **What This Indicator DOES:** ✅ Measures momentum direction and strength via angle analysis ✅ Generates signals when multiple conditions align ✅ Filters out low-conviction sideways markets ✅ Provides visual clarity on trend state **What This Indicator DOES NOT:** ❌ Predict future price movements with certainty ❌ Guarantee profitable trades (no indicator can) ❌ Work equally well on all instruments/timeframes ❌ Replace proper risk management and position sizing **Known Limitations:** - **Lagging Nature:** Like all moving averages, signals occur after momentum begins - **Whipsaw Risk:** Can generate false signals in volatile, directionless markets - **Optimization Required:** Parameters need adjustment for different assets - **Not a Complete System:** Should be combined with risk management, position sizing, and other analysis **Best Performance Conditions:** - Strong trending markets (crypto bull runs, stock breakouts) - Liquid instruments (major forex pairs, large-cap stocks) - Appropriate timeframe selection (match to trading style) - Used alongside support/resistance and volume analysis --- ## 🔔 ALERT SETUP The indicator includes four alert conditions: **1. BUY SIGNAL** - Message: "MA SMART Angle: BUY SIGNAL! Angle crossed up with momentum" - Use for: Primary long entries **2. SELL SIGNAL** - Message: "MA SMART Angle: SELL SIGNAL! Angle crossed down with momentum" - Use for: Primary short entries or long exits **3. Strong BUY** - Message: "MA SMART Angle: Strong BUY momentum - JMA fast crossed up" - Use for: Adding to longs or aggressive entries **4. Strong SELL** - Message: "MA SMART Angle: Strong SELL momentum - JMA fast crossed down" - Use for: Adding to shorts or aggressive exits **Setting Up Alerts:** 1. Right-click indicator → "Add Alert on MA SMART Angle" 2. Select desired condition from dropdown 3. Choose notification method (popup, email, webhook) 4. Set alert expiration (typically "Once Per Bar Close") --- ## 📚 EDUCATIONAL VALUE This indicator serves as an excellent learning tool for understanding: **1. Angle-Based Momentum Analysis** - Traditional indicators show MA crossovers - This shows the *rate of change* (velocity) of MAs - Teaches traders to think in terms of momentum acceleration **2. Multi-Timeframe Confirmation** - Shows how fast, medium, and slow MAs interact - Demonstrates importance of trend alignment - Helps develop patience for high-probability setups **3. Signal Quality vs. Quantity Tradeoff** - Simple mode = more signals, more noise - Strict mode = fewer signals, higher quality - Teaches discretionary filtering skills **4. Market State Recognition** - Visual distinction between trending and ranging markets - Helps traders avoid trading choppy conditions - Develops "market context" awareness --- ## 🔄 DIFFERENCES FROM OTHER MA INDICATORS **vs. Traditional MA Crossovers:** - Measures momentum (angle) rather than just price crossing MA - Provides earlier signals as angles change before price crosses - Filters better for sideways markets using no-trade zones **vs. MACD:** - Uses multiple MAs instead of just two - ATR normalization makes it universal across instruments - Visual angle representation more intuitive than histogram **vs. Supertrend:** - Not based on ATR bands but on MA slope analysis - Provides graduated strength indication (not just binary trend) - Less prone to whipsaw in low volatility **vs. Original "MA Angles" by JD:** - Adds explicit entry/exit signals (original had none) - Implements no-repaint logic for reliability - Includes signal filtering and quality controls - Provides dual signal systems (Simple/Strict) - Enhanced visualization and status monitoring - Uses faster MA periods (3/8/13 vs 27/83/278) for modern markets --- ## 📖 CODE STRUCTURE (for Pine Script learners) This indicator demonstrates: **Advanced Pine Script Techniques:** - Custom function implementation (JMA, angle calculation) - Var declarations for stateful tracking - Table creation for HUD display - Multi-condition signal logic - Alert system integration - Proper use of historical references for no-repaint **Code Organization:** - Modular function definitions (JMA, angle) - Clear separation of concerns (inputs, calculations, plotting, alerts) - Extensive commenting for maintainability - Best practices for Pine Script v5 **Learning Resources:** - Study the JMA function to understand adaptive smoothing - Examine angle calculation for ATR normalization technique - Review signal logic for multi-condition confirmation patterns - Analyze anti-spam filtering for state management The code is open-source - feel free to study, modify, and improve upon it! --- ## 🙏 CREDITS & ATTRIBUTION **Original Concepts:** - **"ma angles - JD" by JD (Duyck)** - Core angle calculation methodology and indicator concept Original open-source indicator on TradingView Community Scripts - **JMA (Jurik Moving Average) implementation by Everget** - Smooth, low-lag moving average function Acknowledged in original JD indicator code - **Angle Calculation formula by KyJ** - Mathematical formula for converting MA slope to degrees using ATR normalization Acknowledged in original JD indicator code comments **Enhancements in This Version:** - Signal generation logic - Original implementation for this indicator - No-repaint confirmation system - Original implementation - Dual signal modes (Simple/Strict) - Original implementation - Visual enhancements and status table - Original implementation - Alert system and signal filtering - Original implementation - Modified MA periods (3/8/13 instead of 27/83/278) - Optimization for modern markets **Open Source Philosophy:** This indicator follows the open-source spirit of TradingView and the Pine Script community. The original "ma angles - JD" by JD (Duyck) was published as open-source, enabling this enhanced version. Similarly, this code is published as open-source to allow further community improvements. --- ## ⚡ QUICK START GUIDE **For New Users:** 1. Add indicator to chart 2. Start with default settings (Simple mode) 3. Wait for BUY signal (green arrow) 4. Observe how price behaves after signal 5. Check status table to understand market state 6. Adjust parameters based on your instrument/timeframe **For Experienced Traders:** 1. Switch to Strict mode for higher quality signals 2. Increase cooldown bars to reduce frequency 3. Raise minimum angle threshold for stronger trends 4. Combine with your existing strategy for confirmation 5. Set up alerts for desired signal types 6. Backtest on your preferred instruments --- ## 🎓 RECOMMENDED COMBINATIONS **Works Well With:** - **Volume Analysis:** Confirm signals with volume spikes - **Support/Resistance:** Take signals near key levels - **RSI/Stochastic:** Avoid overbought/oversold extremes - **ATR:** Size positions based on volatility - **Price Action:** Wait for candlestick confirmation **Complementary Indicators:** - Order Flow / Footprint (for institutional confirmation) - Volume Profile (for identifying value areas) - VWAP (for intraday mean reversion reference) - Fibonacci Retracements (for target setting) --- ## 📈 PERFORMANCE EXPECTATIONS **Realistic Win Rates:** - Simple Mode: 45-55% (higher frequency, moderate accuracy) - Strict Mode: 55-65% (lower frequency, higher accuracy) - Combined with price action: 60-70% **Best Asset Classes:** 1. **Cryptocurrencies** (strong trends, clear signals) 2. **Forex Major Pairs** (smooth price action, good angles) 3. **Large-Cap Stocks** (trending behavior, liquid) 4. **Index Futures** (trending instruments) **Challenging Conditions:** - Low volatility consolidation periods - News-driven erratic movements - Thin/illiquid instruments - Counter-trending markets --- ## 🛡️ RISK DISCLAIMER **IMPORTANT LEGAL NOTICE:** This indicator is for **educational and informational purposes only**. It is **NOT financial advice** and does not constitute a recommendation to buy or sell any financial instrument. **Trading Risks:** - Trading carries substantial risk of loss - Past performance does not guarantee future results - No indicator can predict market movements with certainty - You can lose more than your initial investment (especially with leverage) **User Responsibilities:** - Conduct your own research and due diligence - Understand the instruments you trade - Never risk more than you can afford to lose - Use proper position sizing and risk management - Consider consulting a licensed financial advisor **Indicator Limitations:** - Signals are based on historical data only - No guarantee of accuracy or profitability - Parameters must be optimized for your specific use case - Results vary significantly by market conditions By using this indicator, you acknowledge and accept all trading risks. The author is not responsible for any financial losses incurred through use of this indicator. --- ## 📧 SUPPORT & FEEDBACK **Found a bug?** Please report it in the comments with: - Chart symbol and timeframe - Parameter settings used - Description of unexpected behavior - Screenshot if possible **Have suggestions?** Share your ideas for improvements! **Enjoying the indicator?** Leave a like and follow for updates!
Pine Script® インジケーター
Smart-Day-Traderの投稿
Smart VWAP FVG SystemSmart VWAP FVG System - Professional Multi-Filter Trading Indicator 📊 OVERVIEW The Smart VWAP FVG System is an advanced multi-layered trading indicator that combines institutional volume analysis, multi-timeframe VWAP trend confirmation, and Fair Value Gap detection to identify high-probability trade entries. This indicator uses a sophisticated filtering mechanism where signals appear only when multiple independent confirmation criteria align simultaneously. Recommended Timeframe: 5-minute (M5) or higher. The indicator works best on M5, M15, and M30 charts for intraday trading. 🎯 ORIGINALITY & PURPOSE This indicator is original because it combines three distinct analytical methods into a unified decision-making system: Market Profile Volume Analysis - Identifies institutional accumulation/distribution zones Dual VWAP Filtering - Confirms trend direction using two independent VWAP calculations Fair Value Gap Detection - Validates institutional interest through price inefficiency zones The key innovation is the directional filter system: the primary Market Profile generates BUY-ONLY or SELL-ONLY states based on higher timeframe value area reversals, which then controls which signals from the main system are displayed. This creates a multi-timeframe confluence that significantly reduces false signals. Unlike simple indicator mashups, each component serves a specific purpose: Market Profile → Direction bias (trend filter) Primary VWAP (Session) → Short-term trend confirmation Secondary VWAP (Week) → Medium-term trend confirmation FVG Detection → Institutional activity validation 🔧 HOW IT WORKS 1. Primary Market Profile Filter (Higher Timeframe) The indicator calculates Market Profile on a higher timeframe (default: 1 hour) to determine the overall market structure: Value Area High (VAH): Top 70% of volume distribution Value Area Low (VAL): Bottom 70% of volume distribution Point of Control (POC): Price level with highest volume When price reaches VAH and reverses down → SELL-ONLY mode activated When price reaches VAL and reverses up → BUY-ONLY mode activated This higher timeframe filter ensures you're trading in the direction of institutional flow. 2. Dual VWAP System Two independent VWAP calculations provide multi-timeframe trend confirmation: Primary VWAP (Session-based): Resets daily, tracks intraday momentum Secondary VWAP (Week-based): Resets weekly, confirms longer-term trend Filter Logic: BUY signals require: Price > Primary VWAP AND Price > Secondary VWAP SELL signals require: Price < Primary VWAP AND Price < Secondary VWAP This dual confirmation prevents counter-trend trades during ranging conditions. 3. Fair Value Gap (FVG) Detection FVG zones identify price inefficiencies where institutional orders were executed rapidly: Bullish FVG: Gap between candle .high and candle .low (upward imbalance) Bearish FVG: Gap between candle .high and candle .low (downward imbalance) The indicator monitors recent FVG formation (lookback: 50 bars) and requires: Bullish FVG present for BUY signals Bearish FVG present for SELL signals FVG zones are displayed as colored boxes and automatically marked as "mitigated" when price fills the gap. 4. Main Trading Signal Logic The secondary Market Profile (default: 1 hour) generates the actual trading signals: BUY Signal Conditions: Price reaches Value Area Low Reversal pattern confirmed (minimum 1 bar) Price > Primary VWAP Price > Secondary VWAP (if filter enabled) Recent Bullish FVG detected (if filter enabled) Primary MP Filter = BUY-ONLY or NEUTRAL SELL Signal Conditions: Price reaches Value Area High Reversal pattern confirmed (minimum 1 bar) Price < Primary VWAP Price < Secondary VWAP (if filter enabled) Recent Bearish FVG detected (if filter enabled) Primary MP Filter = SELL-ONLY or NEUTRAL All conditions must be TRUE simultaneously for a signal to appear. 📈 VISUAL ELEMENTS On Chart: 🟢 Green Triangle (▲) = BUY Signal 🔴 Red Triangle (▼) = SELL Signal 🟦 Blue horizontal lines = Value Area zones 🟡 Yellow line = Point of Control (POC) 🟩 Green boxes = Bullish FVG zones 🟥 Red boxes = Bearish FVG zones 🔵 Blue line = Primary VWAP (Session) ⚪ White line = Secondary VWAP (Week) Info Panel (Top Right): Real-time status display showing: Filter Direction (BUY ONLY / SELL ONLY / NEUTRAL) Active timeframes for both MP filters FVG filter status and count VWAP positions (ABOVE/BELOW) Signal enablement status Alert status ⚙️ KEY SETTINGS MP/TPO Filter Settings (Primary Indicator) MP Filter Time Frame: 60 minutes (controls directional bias) Filter Value Area %: 70% (standard Market Profile calculation) Filter Alert Distance: 1 bar Filter Min Bars for Reversal: 1 bar Filter Alert Zone Margin: 0.01 (1%) FVG Filter Settings Use FVG Filter: Enabled (toggle on/off) FVG Timeframe: 60 minutes (1 hour) FVG Filter Mode: Both (require bullish FVG for BUY, bearish for SELL) FVG Lookback Period: 50 bars (how far back to search) Show FVG Formation Signals: Optional visual markers Max FVG on Chart: 50 zones Show Mitigated FVG: Display filled gaps Market Profile Settings Higher Time Frame: 60 minutes (for main signals) Percent for Value Area: 70% Show POC Line: Enabled Keep Old MPs: Enabled (maintain historical profiles) Primary VWAP Filter Use Primary VWAP Filter: Enabled Primary VWAP Anchor Period: Session (resets daily) Primary VWAP Source: HLC3 (typical price) Secondary VWAP Filter Use Secondary VWAP Filter: Enabled Secondary VWAP Anchor Period: Week (resets weekly) Secondary VWAP Filter Mode: Both Secondary VWAP Line Color: White Trading Signals Show Trading Signals on Chart: Enabled Show SELL Signals: Enabled Show BUY Signals: Enabled Alert Distance: 1 bar Min Bars for Reversal: 1 bar Alert Zone Margin: 0.01 (1%) Retest Search Period: 20 bars Min Bars Between Retests: 5 bars Show Only Retests: Disabled Alert Settings Enable Trading Notifications: Enabled VAH Reversal Alert: Enabled (SELL signals) VAL Reversal Alert: Enabled (BUY signals) Time Filter Settings Filter Alerts By Time: Optional (exclude specific hours) ⚠️ IMPORTANT WARNINGS & LIMITATIONS 1. Repainting Behavior CRITICAL: This indicator uses lookahead=barmerge.lookahead_on to access higher timeframe data immediately for FVG detection. This is necessary to provide real-time FVG zone visualization but has the following implications: FVG zones may shift slightly until the higher timeframe candle closes FVG detection signals are preliminary until HTF bar confirmation The main trading signals (triangles) appear on confirmed bars and do not repaint Best Practice: Always wait for the current timeframe bar to close before acting on signals. The filter status and FVG zones are informational but may adjust as new data arrives. 2. Minimum Timeframe Do NOT use on timeframes below 5 minutes (M5) Recommended: M5, M15, M30 for intraday trading Higher timeframes (H1, H4) can also be used but will generate fewer signals 3. Multiple Filters Can Block Signals By design, this indicator is conservative. When all filters are enabled: Signals appear ONLY when all conditions align You may see extended periods with no signals This is intentional to reduce false positives If you see no signals: Check the Info Panel to see which filters are failing Consider adjusting FVG lookback period Temporarily disable FVG filter to test Verify VWAP filters match current market trend 4. Market Profile Limitations Market Profile requires sufficient volume data Low-volume instruments may produce unreliable profiles Value Areas update only on higher timeframe bar close Works best on liquid markets (major forex pairs, indices, crypto) 📖 HOW TO USE Step 1: Add to Chart Apply indicator to M5 or higher timeframe chart Ensure chart shows volume data Use standard candles (NOT Heikin Ashi, Renko, etc.) Step 2: Configure Settings Primary MP Filter TF: Set to 60 (1 hour) minimum, or 240 (4 hour) for swing trading Main MP TF: Set to 60 (1 hour) for intraday signals FVG Timeframe: Match or exceed main MP timeframe Leave other settings at default initially Step 3: Understand the Info Panel Monitor the top-right panel: FILTER STATUS: Shows current directional bias NEUTRAL = Both signals allowed BUY ONLY = Only green triangles will appear SELL ONLY = Only red triangles will appear FVG Filter: Shows if bullish/bearish gaps detected recently VWAP positions: Confirms trend alignment Step 4: Take Signals For BUY Signal (Green Triangle ▲): Wait for green triangle to appear Check Info Panel shows ✓ for BUY signals Confirm current bar has closed Enter long position Stop loss: Below recent VAL or swing low Target: Previous Value Area High or 1.5-2× risk For SELL Signal (Red Triangle ▼): Wait for red triangle to appear Check Info Panel shows ✓ for SELL signals Confirm current bar has closed Enter short position Stop loss: Above recent VAH or swing high Target: Previous Value Area Low or 1.5-2× risk Step 5: Risk Management Risk per trade: Maximum 1-2% of account equity Position sizing: Adjust based on stop loss distance Avoid trading: During major news events or time filter periods Multiple confirmations: Look for confluence with price action (support/resistance, trendlines) 🎓 UNDERLYING CONCEPTS Market Profile Theory Developed by J. Peter Steidlmayer in the 1980s, Market Profile organizes price and volume data to identify: Value Areas: Where 70% of trading activity occurred POC: Price level with highest acceptance (most volume) Imbalances: When price moves away from value quickly This indicator uses TPO (Time Price Opportunity) calculation method to build the volume profile distribution. VWAP (Volume Weighted Average Price) VWAP represents the average price weighted by volume, showing where institutional traders are positioned: Price above VWAP = Bullish (institutions accumulated lower) Price below VWAP = Bearish (institutions distributed higher) Using dual VWAP (Session + Week) creates multi-timeframe trend alignment. Fair Value Gaps (FVG) Also known as "imbalance" or "inefficiency," FVG occurs when: Price moves so rapidly that a gap forms in the candlestick structure Indicates institutional order flow (large market orders) Price often returns to "fill" these gaps (rebalance) The 3-candle FVG pattern (gap between candle and candle ) is widely used in ICT (Inner Circle Trader) methodology and Smart Money Concepts. 🔍 CREDITS & CODE ATTRIBUTION This indicator builds upon established technical analysis concepts and combines multiple methodologies: 1. Market Profile / TPO Calculation Concept Origin: J. Peter Steidlmayer (Chicago Board of Trade, 1980s) Code Inspiration: TradingView's public domain Market Profile examples Modifications: Custom filtering logic for directional bias, dual timeframe implementation 2. VWAP Calculation Concept Origin: Standard financial instrument (widely used since 1980s) Code Base: TradingView built-in ta.vwap() function (public domain) Modifications: Dual VWAP system with independent anchor periods, custom filtering modes 3. Fair Value Gap Detection Concept Origin: Inner Circle Trader (ICT) / Smart Money Concepts methodology Code Implementation: Original implementation based on 3-candle gap pattern Features: Multi-timeframe detection, automatic mitigation tracking, visual zone display 4. Pine Script Framework Language: Pine Script v6 (TradingView) Built-in Functions Used: ta.vwap() - Volume weighted average price request.security() - Higher timeframe data access ta.change() - Period detection ta.cum() - Cumulative volume time() - Timestamp functions Note: All code is original implementation. While concepts are based on established trading methodologies, the combination, filtering logic, and execution are unique to this indicator. 📊 RECOMMENDED INSTRUMENTS Best Performance: Major Forex Pairs (EURUSD, GBPUSD, USDJPY) Stock Indices (ES, NQ, SPX, DAX) Major Cryptocurrencies (BTCUSD, ETHUSD) Liquid Stocks (high daily volume) Avoid: Low-volume altcoins Illiquid stocks Exotic forex pairs with wide spreads ⚡ PERFORMANCE TIPS Start Conservative: Enable all filters initially Reduce Filters Gradually: If too few signals, disable Secondary VWAP filter first Match Timeframes: Keep MP Filter TF and FVG TF at same value Backtest First: Review historical performance on your preferred instrument/timeframe Combine with Price Action: Look for support/resistance confluence Use Time Filter: Avoid low-liquidity hours (optional setting) 🚫 WHAT THIS INDICATOR DOES NOT DO Does not guarantee profits - No trading system is 100% accurate Does not predict the future - Based on historical patterns Does not replace risk management - Always use stop losses Does not work on all instruments - Requires volume data and liquidity Does not provide exact entry/exit prices - Signals are zones, not precise levels Does not account for fundamentals - Purely technical analysis 📜 DISCLAIMER This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results. Trading Risk Warning: All trading involves risk of loss You can lose more than your initial investment (leverage products) Only trade with capital you can afford to lose Always use appropriate position sizing and risk management Consider seeking advice from a licensed financial advisor Technical Limitations: Indicator may repaint FVG zones until HTF bar closes Signals are based on historical patterns that may not repeat Market conditions change and no system works in all environments Volume data quality varies by exchange/broker By using this indicator, you acknowledge these risks and agree that the author bears no responsibility for trading losses. 📞 SUPPORT & UPDATES Questions? Comment on this publication Issues? Describe the problem with chart screenshot Feature Requests? Suggest improvements in comments Updates: Will be published as new versions using TradingView's update feature 📝 VERSION HISTORY Version 1.0 (Current) Initial public release Multi-filter system: MP + Dual VWAP + FVG Directional bias filter Real-time info panel Comprehensive alert system Time-based filtering Thank you for using Smart VWAP FVG System! Happy Trading! 📈
Pine Script® インジケーター
Smart-Day-Traderの投稿
Range Trading StrategyOVERVIEW The Range Trading Strategy is a systematic trading approach that identifies price ranges from higher timeframe candles or trading sessions, tracks pivot points, and generates trading signals when range extremes are mitigated and confirmed by pivot levels. CORE CONCEPT The strategy is based on the principle that when a candle (or session) closes within the range of the previous candle (or session), that previous candle becomes a "range" with identifiable high and low extremes. When price breaks through these extremes, it creates trading opportunities that are confirmed by pivot levels. RANGE DETECTION MODES 1. HTF (Higher Timeframe) Mode: Automatically selects a higher timeframe based on the current chart timeframe Uses request.security() to fetch HTF candle data Range is created when an HTF candle closes within the previous HTF candle's range The previous HTF candle's high and low become the range extremes 2. Sessions Mode: - Divides the trading day into 4 sessions (UTC): * Session 1: 00:00 - 06:00 (6 hours) * Session 2: 06:00 - 12:00 (6 hours) * Session 3: 12:00 - 20:00 (8 hours) * Session 4: 20:00 - 00:00 (4 hours, spans midnight) - Tracks high, low, and close for each session - Range is created when a session closes within the previous session's range - The previous session's high and low become the range extremes PIVOT DETECTION Pivots are detected based on candle color changes (bullish/bearish transitions): 1. Pivot Low: Created when a bullish candle appears after a bearish candle Pivot low = minimum of the current candle's low and previous candle's low The pivot bar is the actual bar where the low was formed (current or previous bar) 2. Pivot High: Created when a bearish candle appears after a bullish candle Pivot high = maximum of the current candle's high and previous candle's high The pivot bar is the actual bar where the high was formed (current or previous bar) IMPORTANT: There is always only ONE active pivot high and ONE active pivot low at any given time. When a new pivot is created, it replaces the previous one. RANGE CREATION A range is created when: (HTF Mode) An HTF candle closes within the previous HTF candle's range AND a new HTF candle has just started (Sessions Mode) A session closes within the previous session's range AND a new session has just started Or Range Can Be Created when the Extreme of Another Range Gets Mitigated and We Have a Pivot low Just Above the Range Low or Pivot High just Below the Range High Range Properties: rangeHigh: The high extreme of the range rangeLow: The low extreme of the range highStartTime: The timestamp when the range high was actually formed (found by looping backwards through bars) lowStartTime: The timestamp when the range low was actually formed (found by looping backwards through bars) highMitigated / lowMitigated: Flags tracking whether each extreme has been broken isSpecial: Flag indicating if this is a "special range" (see Special Ranges section) RANGE MITIGATION A range extreme is considered "mitigated" when price interacts with it: High is mitigated when: high >= rangeHigh (any interaction at or above the level) Low is mitigated when: low <= rangeLow (any interaction at or below the level) Mitigation can happen: At the moment of range creation (if price is already beyond the extreme) At any point after range creation when price touches the extreme SIGNAL GENERATION 1. Pending Signals: When a range extreme is mitigated, a pending signal is created: a) BEARISH Pending Signal: - Triggered when: rangeHigh is mitigated - Confirmation Level: Current pivotLow - Signal is confirmed when: close < pivotLow - Stop Loss: Current pivotHigh (at time of confirmation) - Entry: Short position Signal Confirmation b) BULLISH Pending Signal: - Triggered when: rangeLow is mitigated - Confirmation Level: Current pivotHigh - Signal is confirmed when: close > pivotHigh - Stop Loss: Current pivotLow (at time of confirmation) - Entry: Long position IMPORTANT: There is only ever ONE pending bearish signal and ONE pending bullish signal at any given time. When a new pending signal is created, it replaces the previous one of the same type. 2. Signal Confirmation: - Bearish: Confirmed when price closes below the pivot low (confirmation level) - Bullish: Confirmed when price closes above the pivot high (confirmation level) - Upon confirmation, a trade is entered immediately - The confirmation line is drawn from the pivot bar to the confirmation bar TRADE EXECUTION When a signal is confirmed: 1. Position Management: - Any existing position in the opposite direction is closed first - Then the new position is entered 2. Stop Loss: - Bearish (Short): Stop at pivotHigh - Bullish (Long): Stop at pivotLow 3. Take Profit: - Calculated using Risk:Reward Ratio (default 2:1) - Risk = Distance from entry to stop loss - Target = Entry ± (Risk × R:R Ratio) - Can be disabled with "Stop Loss Only" toggle 4. Trade Comments: - "Range Bear" for short trades - "Range Bull" for long trades SPECIAL RANGES Special ranges are created when: - A range high is mitigated AND the current pivotHigh is below the range high - A range low is mitigated AND the current pivotLow is above the range low In these cases: - The pivot value is stored in an array (storedPivotHighs or storedPivotLows) - A "special range" is created with only ONE extreme: * If pivotHigh < rangeHigh: Creates a range with rangeHigh = pivotLow, rangeLow = na * If pivotLow > rangeLow: Creates a range with rangeLow = pivotHigh, rangeHigh = na - Special ranges can generate signals just like normal ranges - If a special range is mitigated on the creation bar or the next bar, it is removed entirely without generating signals (prevents false signals) Special Ranges REVERSE ON STOP LOSS When enabled, if a stop loss is hit, the strategy automatically opens a trade in the opposite direction: 1. Long Stop Loss Hit: - Detects when: position_size > 0 AND position_size <= 0 AND low <= longStopLoss - Action: Opens a SHORT position - Stop Loss: Current pivotHigh - Trade Comment: "Reverse on Stop" 2. Short Stop Loss Hit: - Detects when: position_size < 0 AND position_size >= 0 AND high >= shortStopLoss - Action: Opens a LONG position - Stop Loss: Current pivotLow - Trade Comment: "Reverse on Stop" The reverse trade uses the same R:R ratio and respects the "Stop Loss Only" setting. VISUAL ELEMENTS 1. Range Lines: - Drawn from the time when the extreme was formed to the mitigation point (or current time if not mitigated) - High lines: Blue (or mitigated color if mitigated) - Low lines: Red (or mitigated color if mitigated) - Style: SOLID - Width: 1 2. Confirmation Lines: - Drawn when a signal is confirmed - Extends from the pivot bar to the confirmation bar - Bearish: Red, solid line - Bullish: Green, solid line - Width: 1 - Can be toggled on/off STRATEGY SETTINGS 1. Range Detection Mode: - HTF: Uses higher timeframe candles - Sessions: Uses trading session boundaries 2. Auto HTF: - Automatically selects HTF based on current chart timeframe - Can be disabled to use manual HTF selection 3. Risk:Reward Ratio: - Default: 2.0 (2:1) - Minimum: 0.5 - Step: 0.5 4. Stop Loss Only: - When enabled: Trades only have stop loss (no take profit) - Trades close on stop loss or when opposite signal confirms 5. Reverse on Stop Loss: - When enabled: Hitting a stop loss opens opposite trade with stop at opposing pivot 6. Max Ranges to Display: - Limits the number of ranges kept in memory - Oldest ranges are purged when limit is exceeded KEY FEATURES 1. Dynamic Pivot Tracking: - Pivots update on every candle color change - Always maintains one high and one low pivot 2. Range Lifecycle: - Ranges are created when price closes within previous range - Ranges are tracked until mitigated - Mitigation creates pending signals - Signals are confirmed by pivot levels 3. Signal Priority: - Only one pending signal of each type at a time - New signals replace old ones - Confirmation happens on close of bar 4. Position Management: - Closes opposite positions before entering new trades - Tracks stop loss levels for reverse functionality - Respects pyramiding = 1 (only one position per direction) 5. Time-Based Drawing: - Uses time coordinates instead of bar indices for line drawing - Prevents "too far from current bar" errors - Lines can extend to any historical point USAGE NOTES - Best suited for trending and ranging markets - Works on any timeframe, but HTF mode adapts automatically - Sessions mode is ideal for intraday trading - Pivot detection requires clear candle color changes - Range detection requires price to close within previous range - Signals are generated on bar close, not intra-bar The strategy combines range identification, pivot tracking, and signal confirmation to create a systematic approach to trading breakouts and reversals based on price structure, past performance does not in any way predict future performance
Pine Script® ストラテジー
mindyourbuisnessの投稿
2
Multi-Timeframe SFP (Swing Failure Pattern)How to Use 1. Set Pivot Timeframe: Choose the timeframe for identifying major swing points (e.g., 'D' for Daily pivots). 2. Set SFP Timeframe: Choose the timeframe to find the SFP candle (e.g., '240' for the 4-Hour chart). 3. Set Confirmation Bars: Set how many SFP Timeframe bars must pass without invalidating the level. A value of '0' confirms immediately on the SFP bar's close. A value of '1' waits for one more bar to close. 4. Adjust Filters (Optional): Enable the 'Wick % Filter' to add a quality check for strong rejections. 5. Watch & Wait: The indicator will draw lines and labels and fire alerts for fully confirmed signals. In-Depth Explanation 1. Overview The Dynamic Pivot SFP Engine is a multi-timeframe tool designed to identify and validate Swing Failure Patterns (SFPs) at significant price levels. An SFP is a common price action pattern where price briefly trades beyond a previous swing high or low (sweeping liquidity) but then fails to hold those new prices, closing back inside the previous range. This "failure" often signals a reversal. This indicator enhances SFP detection by separating the Pivot (Liquidity) from the SFP (Rejection), allowing you to monitor them on different timeframes. 2. The Core Multi-Timeframe Logic The indicator's power comes from two key inputs: • Pivot Timeframe (Pivot Timeframe) This is the "high timeframe" used to establish significant support and resistance levels. The script finds standard pivots (swing highs and lows) on this timeframe based on the Pivot Left Strength and Pivot Right Strength inputs. These pivots are the "liquidity" levels the SFP will target. The Pivot Lookback input controls how long (in Pivot Timeframe bars) a pivot remains active and monitored. • SFP Timeframe (SFP Timeframe) This is the "execution timeframe" where the script looks for the actual SFP. On every new bar of this timeframe, the script checks if price has swept and rejected any of the active pivots. Example Setup: You might set Pivot Timeframe to 'D' (Daily) to find major daily swing points. You then set SFP Timeframe to '240' (4-Hour) to find a 4-hour candle that sweeps a daily pivot and closes back below/above it. 3. The SFP Confirmation Process An SFP is not confirmed instantly. It must pass a rigorous, multi-step validation process. Step 1: The SFP Candle (The Sweep) A potential SFP is identified when an SFP Timeframe bar does the following: • Bearish SFP: The bar's high trades above an active pivot high, but the bar closes below that same pivot high. • Bullish SFP: The bar's low trades below an active pivot low, but the bar closes above that same pivot low. Step 2: The Wick Filter (Optional Quality Check) If Enable Wick % Filter is checked, the SFP candle from Step 1 is also measured. • For a bearish SFP, the upper wick (from the high to the open/close) must be at least Min. Wick % of the entire candle's range (high-to-low). • For a bullish SFP, the lower wick (from the low to the open/close) must meet the same percentage requirement. If the SFP candle fails this test, it is discarded, even if it met the sweep/close criteria. Step 3: The Validation Window (The Confirmation) This is the most critical feature, controlled by Confirmation Bars. • If Confirmation Bars = 0: The SFP is confirmed immediately on the SFP candle's close (assuming it passed the optional wick check). The label, line, and alert are triggered at this moment. • If Confirmation Bars > 0: The SFP enters a "pending" state. The script will wait for $N$ more SFP Timeframe bars to close. o Invalidation: If, during this waiting period, any bar closes back across the pivot (e.g., a close above the pivot for a bearish SFP), the SFP is considered failed and invalidated. All pending plots are deleted. o Confirmation: If the $N$ confirmation bars all complete without invalidating the level, the SFP is finally confirmed. The label, line, and alert are only triggered after this entire process is complete. This adds a significant layer of robustness, ensuring the rejection holds for a period of time. 4. Visuals & Alerts • Lines: A horizontal line is drawn from the original pivot to the SFP bar, showing which level was targeted. Note: These lines will only be drawn on chart timeframes equal to or lower than the 'SFP Timeframe'. • Labels: A label is placed at the SFP's extreme (the high/low of the SFP bar). The label text conveniently includes the Ticker, Pivot TF, SFP TF, and Confirmation bar settings (e.g., "Bearish SFP BTCUSD / Pivot: 1D / SFP: 4H | Conf: 1"). • MTF Boxes (Show SFP Box, Show Conf. Boxes): These boxes highlight the SFP and confirmation bars. Crucially, they are only visible when your chart timeframe is lower than the SFP Timeframe. For example, if your SFP Timeframe is '240' (4H), you will only see these boxes on the 1H, 15M, 5M, etc., charts. This allows you to see the higher-timeframe SFP unfolding on your lower-timeframe chart. • Alerts (Enable Alerts): An alert is fired only when an SFP is fully confirmed (i.e., after the Confirmation Bars have passed successfully). For efficient, real-time monitoring, it is highly recommended to run this indicator server-side by creating an alert on TradingView set to trigger on "Any alert() function call".
Pine Script® インジケーター
nickbonenkampの投稿
Relative Strength Index Remastered [CHE]Relative Strength Index Remastered — Enhanced RSI with robust divergence detection using price-based pivots and line-of-sight validation to reduce false signals compared to the standard RSI indicator. Summary RSI Remastered builds on the classic Relative Strength Index by adding a more reliable divergence detection system that relies on price pivots rather than RSI pivots alone, incorporating a line-of-sight check to ensure the RSI path between points remains clear. This approach filters out many false divergences that occur in the original RSI indicator due to its volatile pivot detection on the RSI line itself. Users benefit from clearer reversal and continuation signals, especially in noisy markets, with optional hidden divergence support for trend confirmation. The core RSI calculation and smoothing options remain familiar, but the divergence logic provides materially fewer alerts while maintaining sensitivity. Motivation: Why this design? The standard RSI indicator often generates misleading divergence signals because it detects pivots directly on the RSI values, which can fluctuate erratically in volatile conditions, leading to frequent false positives that confuse traders during ranging or choppy price action. RSI Remastered addresses this by shifting pivot detection to the underlying price highs and lows, which are more stable, and adding a validation step that confirms the RSI line does not cross the direct path between pivot points. This design targets the real problem of over-signaling in the original, promoting more actionable insights without altering the RSI's core momentum measurement. What’s different vs. standard approaches? - Reference baseline: The classical TradingView RSI indicator, which uses simple RSI-based pivot detection for divergences. - Architecture differences: - Pivot identification on price extremes (highs and lows) instead of RSI values, extracting RSI levels at those points for comparison. - Addition of a line-of-sight validation that checks the RSI path bar by bar between pivots to prevent signals where the line is interrupted. - Inclusion of hidden divergence types alongside regular ones, using the same robust framework. - Configurable drawing of connecting lines between validated pivot RSI points for visual clarity. - Practical effect: Charts show fewer but higher-quality divergence markers and lines, reducing clutter from the original's frequent RSI pivot triggers; this matters for avoiding whipsaws in intraday trading, where the standard version might flag dozens of invalid setups per session. Key Comparison Aspects Aspect: Title/Shorttitle Original RSI: "Relative Strength Index" / "RSI" Robust Variant: "Relative Strength Index Remastered " / "RSI RM" Aspect: Max. Lines/Labels Original RSI: No specification (Standard: 50/50) Robust Variant: max_lines_count=200, max_labels_count=200 (for more lines/markers in divergences) Aspect: RSI Calculation & Plots Original RSI: Identical: RSI with RMA, Plots (line, bands, gradient fills) Robust Variant: Identical: RSI with RMA, Plots (line, bands, gradient fills) Aspect: Smoothing (MA) Original RSI: Identical: Inputs for MA types (SMA, EMA etc.), Bollinger Bands optional Robust Variant: Identical: Inputs for MA types (SMA, EMA etc.), Bollinger Bands optional Aspect: Divergence Activation Original RSI: input.bool(false, "Calculate Divergence") (disabled by default) Robust Variant: input.bool(true, "Calculate Divergence") (enabled by default, with tooltip) Aspect: Pivot Calculation Original RSI: Pivots on RSI (ta.pivotlow/high on RSI values) Robust Variant: Pivots on price (ta.pivotlow/high on low/high), RSI values then extracted Aspect: Lookback Values Original RSI: Fixed: lookbackLeft=5, lookbackRight=5 Robust Variant: Input: L=5 (Pivot Left), R=5 (Pivot Right), adjustable (min=1, max=50) Aspect: Range Between Pivots Original RSI: Fixed: rangeUpper=60, rangeLower=5 (via _inRange function) Robust Variant: Input: rangeUpper=60 (Max Bars), rangeLower=5 (Min Bars), adjustable (min=1–6, max=100–300) Aspect: Divergence Types Original RSI: Only Regular Bullish/Bearish: - Bull: Price LL + RSI HL - Bear: Price HH + RSI LH Robust Variant: Regular + Hidden (optional via showHidden=true): - Regular Bull: Price LL + RSI HL - Regular Bear: Price HH + RSI LH - Hidden Bull: Price HL + RSI LL - Hidden Bear: Price LH + RSI HH Aspect: Validation Original RSI: No additional check (only pivot + range check) Robust Variant: Line-of-Sight Check: RSI line must not cross the connecting line between pivots (line_clear function with slope calculation and loop for each bar in between) Aspect: Signals (Plots/Shapes) Original RSI: - Plot of pivot points (if divergence) - Shapes: "Bull"/"Bear" at RSI value, offset=-5 Robust Variant: - No pivot plots, instead shapes at RSI , offset=-R (adjustable) - Shapes: "Bull"/"Bear" (Regular), "HBull"/"HBear" (Hidden) - Colors: Lime/Red (Regular), Teal/Orange (Hidden) Aspect: Line Drawing Original RSI: No lines Robust Variant: Optional (showLines=true): Lines between RSI pivots (thick for regular, dashed/thin for hidden), extend=none Aspect: Alerts Original RSI: Only Regular Bullish/Bearish (with pivot lookback reference) Robust Variant: Regular Bullish/Bearish + Hidden Bullish/Bearish (specific "at latest pivot low/high") Aspect: Robustness Original RSI: Simple, prone to false signals (RSI pivots can be volatile) Robust Variant: Higher: Price pivots are more stable, line-of-sight filters "broken" divergences, hidden support for trend continuations Aspect: Code Length/Structure Original RSI: ~100 lines, simple if-blocks for bull/bear Robust Variant: ~150 lines, extended helper functions (e.g., inRange, line_clear), var group for inputs How it works (technical) The indicator first computes the core RSI value based on recent price changes, separating upward and downward movements over the specified length and smoothing them to derive a momentum reading scaled between zero and one hundred. This value is then plotted in a separate pane with fixed upper and lower reference lines at seventy and thirty, along with optional gradient fills to highlight overbought and oversold zones. For smoothing, a moving average type is applied to the RSI if enabled, with an option to add bands around it based on the variability of recent RSI values scaled by a multiplier. Divergence detection activates on confirmed price pivots: lows for bullish checks and highs for bearish. At each new pivot, the system retrieves the bar index and values (price and RSI) for the current and prior pivot, ensuring they fall within a configurable bar range to avoid unrelated points. Comparisons then assess whether the price has made a lower low (or higher high) while the RSI at those points moves in the opposite direction—higher for bullish regular, lower for bearish regular. For hidden types, the directions reverse to capture trend strength. The line-of-sight check calculates the straight path between the two RSI points and verifies that the actual RSI values in between stay entirely above (for bullish) or below (for bearish) that path, breaking the signal if any bar violates it. Valid signals trigger shapes at the RSI level of the new pivot and optional lines connecting the points. Initialization uses built-in functions to track prior occurrences, with states persisting across bars for accurate historical comparisons. No higher timeframe data is used, so confirmation occurs after the right pivot bars close, minimizing live-bar repaints. Parameter Guide Length — Controls the period for measuring price momentum changes — Default: 14 — Trade-offs/Tips: Shorter values increase responsiveness but add noise and more false signals; longer smooths trends but delays entries in fast markets. Source — Selects the price input for RSI calculation — Default: Close — Trade-offs/Tips: Use high or low for volatility focus, but close works best for most assets; mismatches can skew overbought/oversold reads. Calculate Divergence — Enables the enhanced divergence logic — Default: True — Trade-offs/Tips: Disable for pure RSI view to save computation; essential for signal reliability over the standard method. Type (Smoothing) — Chooses the moving average applied to RSI — Default: SMA — Trade-offs/Tips: None for raw RSI; EMA for quicker adaptation, but SMA reduces whipsaws; Bollinger Bands option adds volatility context at cost of added lines. Length (Smoothing) — Period for the smoothing average — Default: 14 — Trade-offs/Tips: Match RSI length for consistency; shorter boosts signal speed but amplifies noise in the smoothed line. BB StdDev — Multiplier for band width around smoothed RSI — Default: 2.0 — Trade-offs/Tips: Lower narrows bands for tighter signals, risking more touches; higher widens for fewer but stronger breakouts. Pivot Left — Bars to the left for confirming price pivots — Default: 5 — Trade-offs/Tips: Increase for stricter pivots in noisy data, reducing signals; too high delays confirmation excessively. Pivot Right — Bars to the right for confirming price pivots — Default: 5 — Trade-offs/Tips: Balances with left for symmetry; longer right ensures maturity but shifts signals backward. Max Bars Between Pivots — Upper limit on distance for valid pivot pairs — Default: 60 — Trade-offs/Tips: Tighten for short-term trades to focus recent action; widen for swing setups but risks unrelated comparisons. Min Bars Between Pivots — Lower limit to avoid clustered pivots — Default: 5 — Trade-offs/Tips: Raise to filter micro-moves; too low invites overlapping signals like the original RSI. Detect Hidden — Includes trend-continuation hidden types — Default: True — Trade-offs/Tips: Enable for full trend analysis; disable simplifies to reversals only, akin to basic RSI. Draw Lines — Shows connecting lines between valid pivots — Default: True — Trade-offs/Tips: Turn off for cleaner charts; helps visually confirm line-of-sight in backtests. Reading & Interpretation The main RSI line oscillates between zero and one hundred, crossing above fifty suggesting building momentum and below indicating weakness; touches near seventy or thirty flag potential extremes. The optional smoothed line and bands provide a filtered view—price above the upper band on the RSI pane hints at overextension. Divergence shapes appear as upward labels for bullish (lime for regular, teal for hidden) and downward for bearish (red regular, orange hidden) at the pivot's RSI level, signaling a mismatch only after validation. Connecting lines, if drawn, slope between points without RSI interference, their color matching the shape type; a dashed style denotes hidden. Fewer shapes overall compared to the standard RSI mean higher conviction, but always confirm with price structure. Practical Workflows & Combinations - Trend following: Enter longs on regular bullish shapes near support with higher highs in price; filter hidden bullish for pullback buys in uptrends, pairing with a rising smoothed RSI above fifty. - Exits/Stops: Use bearish regular as reversal warnings to tighten stops; hidden bearish in downtrends confirms continuation—exit if lines show RSI crossing the path. - Multi-asset/Multi-TF: Defaults suit forex and stocks on one-hour charts; for crypto volatility, widen pivot ranges to ten; scale min/max bars proportionally on daily for swings, avoiding the original's intraday spam. Behavior, Constraints & Performance Signals confirm only after the right pivot bars close, so live bars may show tentative pivots that vanish on close, unlike the standard RSI's immediate RSI-pivot triggers—plan for this delay in automation. No higher timeframe calls, so no security-related repaints. Resources include up to two hundred lines and labels for dense charts, with a loop in validation scanning up to three hundred bars between pivots, which is efficient but could slow on very long histories. Known limits: Slight lag at pivot confirmation in trending markets; volatile RSI might rarely miss fine path violations; not ideal for gap-heavy assets where pivots skip. Sensible Defaults & Quick Tuning Start with defaults for balanced momentum and divergence on most timeframes. For too many signals (like the original), raise pivot left/right to eight and min bars to ten to filter noise. If sluggish in trends, shorten RSI length to nine and enable EMA smoothing for faster adaptation. In high-volatility assets, widen max bars to one hundred but disable hidden to focus essentials. For clean reversal hunts, set smoothing to none and lines on. What this indicator is—and isn’t RSI Remastered serves as a refined momentum and divergence visualization tool, enhancing the standard RSI for better signal quality in technical analysis setups. It is not a standalone trading system, nor does it predict price moves—pair it with volume, structure breaks, and risk rules for decisions. Use alongside position sizing and broader context, not in isolation. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Pine Script® インジケーター
chervolinoの投稿
Luxy Momentum, Trend, Bias and Breakout Indicators V7 TABLE OF CONTENTS This is Version 7 (V7) - the latest and most optimized release. If you are using any older versions (V6, V5, V4, V3, etc.), it is highly recommended to replace them with V7. Why This Indicator is Different Who Should Use This Core Components Overview The UT Bot Trading System Understanding the Market Bias Table Candlestick Pattern Recognition Visual Tools and Features How to Use the Indicator Performance and Optimization FAQ --- ### CREDITS & ATTRIBUTION This indicator implements proven trading concepts using entirely original code developed specifically for this project. ### CONCEPTUAL FOUNDATIONS • UT Bot ATR Trailing System - Original concept by @QuantNomad: (search "UT-Bot-Strategy" - Our version is a complete reimplementation with significant enhancements: - Volume-weighted momentum adjustment - Composite stop loss from multiple S/R layers - Multi-filter confirmation system (swing, %, 2-bar, ZLSMA) - Full integration with multi-timeframe bias table - Visual audit trail with freeze-on-touch - NOTE: No code was copied - this is a complete reimplementation with enhancements. • Standard Technical Indicators (Public Domain Formulas): - Supertrend: ATR-based trend calculation with custom gradient fills - MACD: Gerald Appel's formula with separation filters - RSI: J. Welles Wilder's formula with pullback zone logic - ADX/DMI: Custom trend strength formula inspired by Wilder's directional movement concept, reimplemented with volume weighting and efficiency metrics - ZLSMA: Zero-lag formula enhanced with Hull MA and momentum prediction ### Custom Implementations - Trend Strength: Inspired by Wilder's ADX concept but using volume-weighted pressure calculation and efficiency metrics (not traditional +DI/-DI smoothing) - All code implementations are original ### ORIGINAL FEATURES (70%+ of codebase) - Multi-Timeframe Bias Table with live updates - Risk Management System (R-multiple TPs, freeze-on-touch) - Opening Range Breakout tracker with session management - Composite Stop Loss calculator using 6+ S/R layers - Performance optimization system (caching, conditional calcs) - VIX Fear Index integration - Previous Day High/Low auto-detection - Candlestick pattern recognition with interactive tooltips - Smart label and visual management - All UI/UX design and table architecture ### DEVELOPMENT PROCESS **AI Assistance:** This indicator was developed over 2+ months with AI assistance (ChatGPT/Claude) used for: - Writing Pine Script code based on design specifications - Optimizing performance and fixing bugs - Ensuring Pine Script v6 compliance - Generating documentation **Author's Role:** All trading concepts, system design, feature selection, integration logic, and strategic decisions are original work by the author. The AI was a coding tool, not the system designer. **Transparency:** We believe in full disclosure - this project demonstrates how AI can be used as a powerful development tool while maintaining creative and strategic ownership. --- 1. WHY THIS INDICATOR IS DIFFERENT Most traders use multiple separate indicators on their charts, leading to cluttered screens, conflicting signals, and analysis paralysis. The Suite solves this by integrating proven technical tools into a single, cohesive system. Key Advantages: All-in-One Design: Instead of loading 5-10 separate indicators, you get everything in one optimized script. This reduces chart clutter and improves TradingView performance. Multi-Timeframe Bias Table: Unlike standard indicators that only show the current timeframe, the Bias Table aggregates trend signals across multiple timeframes simultaneously. See at a glance whether 1m, 5m, 15m, 1h are aligned bullish or bearish - no more switching between charts. Smart Confirmations: The indicator doesn't just give signals - it shows you WHY. Every entry has multiple layers of confirmation (MA cross, MACD momentum, ADX strength, RSI pullback, volume, etc.) that you can toggle on/off. Dynamic Stop Loss System: Instead of static ATR stops, the SL is calculated from multiple support/resistance layers: UT trailing line, Supertrend, VWAP, swing structure, and MA levels. This creates more intelligent, price-action-aware stops. R-Multiple Take Profits: Built-in TP system calculates targets based on your initial risk (1R, 1.5R, 2R, 3R). Lines freeze when touched with visual checkmarks, giving you a clean audit trail of partial exits. Educational Tooltips Everywhere: Every single input has detailed tooltips explaining what it does, typical values, and how it impacts trading. You're not guessing - you're learning as you configure. Performance Optimized: Smart caching, conditional calculations, and modular design mean the indicator runs fast despite having 15+ features. Turn off what you don't use for even better performance. No Repainting: All signals respect bar close. Alerts fire correctly. What you see in history is what you would have gotten in real-time. What Makes It Unique: Integrated UT Bot + Bias Table: No other indicator combines UT Bot's ATR trailing system with a live multi-timeframe dashboard. You get precision entries with macro trend context. Candlestick Pattern Recognition with Interactive Tooltips: Patterns aren't just marked - hover over any emoji for a full explanation of what the pattern means and how to trade it. Opening Range Breakout Tracker: Built-in ORB system for intraday traders with customizable session times and real-time status updates in the Bias Table. Previous Day High/Low Auto-Detection: Automatically plots PDH/PDL on intraday charts with theme-aware colors. Updates daily without manual input. Dynamic Row Labels in Bias Table: The table shows your actual settings (e.g., "EMA 10 > SMA 20") not generic labels. You know exactly what's being evaluated. Modular Filter System: Instead of forcing a fixed methodology, the indicator lets you build your own strategy. Start with just UT Bot, add filters one at a time, test what works for your style. --- 2. WHO WHOULD USE THIS Designed For: Intermediate to Advanced Traders: You understand basic technical analysis (MAs, RSI, MACD) and want to combine multiple confirmations efficiently. This isn't a "one-click profit" system - it's a professional toolkit. Multi-Timeframe Traders: If you trade one asset but check multiple timeframes for confirmation (e.g., enter on 5m after checking 15m and 1h alignment), the Bias Table will save you hours every week. Trend Followers: The indicator excels at identifying and following trends using UT Bot, Supertrend, and MA systems. If you trade breakouts and pullbacks in trending markets, this is built for you. Intraday and Swing Traders: Works equally well on 5m-1h charts (day trading) and 4h-D charts (swing trading). Scalpers can use it too with appropriate settings adjustments. Discretionary Traders: This isn't a black-box system. You see all the components, understand the logic, and make final decisions. Perfect for traders who want tools, not automation. Works Across All Markets: Stocks (US, international) Cryptocurrency (24/7 markets supported) Forex pairs Indices (SPY, QQQ, etc.) Commodities NOT Ideal For : Complete Beginners: If you don't know what a moving average or RSI is, start with basics first. This indicator assumes foundational knowledge. Algo Traders Seeking Black Box: This is discretionary. Signals require context and confirmation. Not suitable for blind automated execution. Mean-Reversion Only Traders: The indicator is trend-following at its core. While VWAP bands support mean-reversion, the primary methodology is trend continuation. --- 3. CORE COMPONENTS OVERVIEW The indicator combines these proven systems: Trend Analysis: Moving Averages: Four customizable MAs (Fast, Medium, Medium-Long, Long) with six types to choose from (EMA, SMA, WMA, VWMA, RMA, HMA). Mix and match for your style. Supertrend: ATR-based trend indicator with unique gradient fill showing trend strength. One-sided ribbon visualization makes it easier to see momentum building or fading. ZLSMA : Zero-lag linear-regression smoothed moving average. Reduces lag compared to traditional MAs while maintaining smooth curves. Momentum & Filters: MACD: Standard MACD with separation filter to avoid weak crossovers. RSI: Pullback zone detection - only enter longs when RSI is in your defined "buy zone" and shorts in "sell zone". ADX/DMI: Trend strength measurement with directional filter. Ensures you only trade when there's actual momentum. Volume Filter: Relative volume confirmation - require above-average volume for entries. Donchian Breakout: Optional channel breakout requirement. Signal Systems: UT Bot: The primary signal generator. ATR trailing stop that adapts to volatility and gives clear entry/exit points. Base Signals: MA cross system with all the above filters applied. More conservative than UT Bot alone. Market Bias Table: Multi-timeframe dashboard showing trend alignment across 7 timeframes plus macro bias (3-day, weekly, monthly, quarterly, VIX). Candlestick Patterns: Six major reversal patterns auto-detected with interactive tooltips. ORB Tracker: Opening range high/low with breakout status (intraday only). PDH/PDL: Previous day levels plotted automatically on intraday charts. VWAP + Bands : Session-anchored VWAP with up to three standard deviation band pairs. --- 4. THE UT BOT TRADING SYSTEM The UT Bot is the heart of the indicator's signal generation. It's an advanced ATR trailing stop that adapts to market volatility. Why UT Bot is Superior to Fixed Stops: Traditional ATR stops use a fixed multiplier (e.g., "stop = entry - 2×ATR"). UT Bot is smarter: It TRAILS the stop as price moves in your favor It WIDENS during high volatility to avoid premature stops It TIGHTENS during consolidation to lock in profits It FLIPS when price breaks the trailing line, signaling reversals Visual Elements You'll See: Orange Trailing Line: The actual UT stop level that adapts bar-by-bar Buy/Sell Labels: Aqua triangle (long) or orange triangle (short) when the line flips ENTRY Line: Horizontal line at your entry price (optional, can be turned off) Suggested Stop Loss: A composite SL calculated from multiple support/resistance layers: - UT trailing line - Supertrend level - VWAP - Swing structure (recent lows/highs) - Long-term MA (200) - ATR-based floor Take Profit Lines: TP1, TP1.5, TP2, TP3 based on R-multiples. When price touches a TP, it's marked with a checkmark and the line freezes for audit trail purposes. Status Messages: "SL Touched ❌" or "SL Frozen" when the trade leg completes. How UT Bot Differs from Other ATR Systems: Multiple Filters Available: You can require 2-bar confirmation, minimum % price change, swing structure alignment, or ZLSMA directional filter. Most UT implementations have none of these. Smart SL Calculation: Instead of just using the UT line as your stop, the indicator suggests a better SL based on actual support/resistance. This prevents getting stopped out by wicks while keeping risk controlled. Visual Audit Trail: All SL/TP lines freeze when touched with clear markers. You can review your trades weeks later and see exactly where entries, stops, and targets were. Performance Options: "Draw UT visuals only on bar close" lets you reduce rendering load without affecting logic or alerts - critical for slower machines or 1m charts. Trading Logic: UT Bot flips direction (Buy or Sell signal appears) Check Bias Table for multi-timeframe confirmation Optional: Wait for Base signal or candlestick pattern Enter at signal bar close or next bar open Place stop at "Suggested Stop Loss" line Scale out at TP levels (TP1, TP2, TP3) Exit remaining position on opposite UT signal or stop hit --- 5. UNDERSTANDING THE MARKET BIAS TABLE This is the indicator's unique multi-timeframe intelligence layer. Instead of looking at one chart at a time, the table aggregates signals across seven timeframes plus macro trend bias. Why Multi-Timeframe Analysis Matters: Professional traders check higher and lower timeframes for context: Is the 1h uptrend aligning with my 5m entry? Are all short-term timeframes bullish or just one? Is the daily trend supportive or fighting me? Doing this manually means opening multiple charts, checking each indicator, and making mental notes. The Bias Table does it automatically in one glance. Table Structure: Header Row: On intraday charts: 1m, 5m, 15m, 30m, 1h, 2h, 4h (toggle which ones you want) On daily+ charts: D, W, M (automatic) Green dot next to title = live updating Headline Rows - Macro Bias: These show broad market direction over longer periods: 3 Day Bias: Trend over last 3 trading sessions (uses 1h data) Weekly Bias: Trend over last 5 trading sessions (uses 4h data) Monthly Bias: Trend over last 30 daily bars Quarterly Bias: Trend over last 13 weekly bars VIX Fear Index: Market regime based on VIX level - bullish when low, bearish when high Opening Range Breakout: Status of price vs. session open range (intraday only) These rows show text: "BULLISH", "BEARISH", or "NEUTRAL" Indicator Rows - Technical Signals: These evaluate your configured indicators across all active timeframes: Fast MA > Medium MA (shows your actual MA settings, e.g., "EMA 10 > SMA 20") Price > Long MA (e.g., "Price > SMA 200") Price > VWAP MACD > Signal Supertrend (up/down/neutral) ZLSMA Rising RSI In Zone ADX ≥ Minimum These rows show emojis: GREEB (bullish), RED (bearish), GRAY/YELLOW (neutral/NA) AVG Column: Shows percentage of active timeframes that are bullish for that row. This is the KEY metric: AVG > 70% = strong multi-timeframe bullish alignment AVG 40-60% = mixed/choppy, no clear trend AVG < 30% = strong multi-timeframe bearish alignment How to Use the Table: For a long trade: Check AVG column - want to see > 60% ideally Check headline bias rows - want to see BULLISH, not BEARISH Check VIX row - bullish market regime preferred Check ORB row (intraday) - want ABOVE for longs Scan indicator rows - more green = better confirmation For a short trade: Check AVG column - want to see < 40% ideally Check headline bias rows - want to see BEARISH, not BULLISH Check VIX row - bearish market regime preferred Check ORB row (intraday) - want BELOW for shorts Scan indicator rows - more red = better confirmation When AVG is 40-60%: Market is choppy, mixed signals. Either stay out or reduce position size significantly. These are low-probability environments. Unique Features: Dynamic Labels: Row names show your actual settings (e.g., "EMA 10 > SMA 20" not generic "Fast > Slow"). You know exactly what's being evaluated. Customizable Rows: Turn off rows you don't care about. Only show what matters to your strategy. Customizable Timeframes: On intraday charts, disable 1m or 4h if you don't trade them. Reduces calculation load by 20-40%. Automatic HTF Handling: On Daily/Weekly/Monthly charts, the table automatically switches to D/W/M columns. No configuration needed. Performance Smart: "Hide BIAS table on 1D or above" option completely skips all table calculations on higher timeframes if you only trade intraday. --- 6. CANDLESTICK PATTERN RECOGNITION The indicator automatically detects six major reversal patterns and marks them with emojis at the relevant bars. Why These Six Patterns: These are the most statistically significant reversal patterns according to trading literature: High win rate when appearing at support/resistance Clear visual structure (not subjective) Work across all timeframes and assets Studied extensively by institutions The Patterns: Bullish Patterns (appear at bottoms): Bullish Engulfing: Green candle completely engulfs prior red candle's body. Strong reversal signal. Hammer: Small body with long lower wick (at least 2× body size). Shows rejection of lower prices by buyers. Morning Star: Three-candle pattern (large red → small indecision → large green). Very strong bottom reversal. Bearish Patterns (appear at tops): Bearish Engulfing: Red candle completely engulfs prior green candle's body. Strong reversal signal. Shooting Star: Small body with long upper wick (at least 2× body size). Shows rejection of higher prices by sellers. Evening Star: Three-candle pattern (large green → small indecision → large red). Very strong top reversal. Interactive Tooltips: Unlike most pattern indicators that just draw shapes, this one is educational: Hover your mouse over any pattern emoji A tooltip appears explaining: what the pattern is, what it means, when it's most reliable, and how to trade it No need to memorize - learn as you trade Noise Filter: "Min candle body % to filter noise" setting prevents false signals: Patterns require minimum body size relative to price Filters out tiny candles that don't represent real buying/selling pressure Adjust based on asset volatility (higher % for crypto, lower for low-volatility stocks) How to Trade Patterns: Patterns are NOT standalone entry signals. Use them as: Confirmation: UT Bot gives signal + pattern appears = stronger entry Reversal Warning: In a trade, opposite pattern appears = consider tightening stop or taking profit Support/Resistance Validation: Pattern at key level (PDH, VWAP, MA 200) = level is being respected Best combined with: UT Bot or Base signal in same direction Bias Table alignment (AVG > 60% or < 40%) Appearance at obvious support/resistance --- 7. VISUAL TOOLS AND FEATURES VWAP (Volume Weighted Average Price): Session-anchored VWAP with standard deviation bands. Shows institutional "fair value" for the trading session. Anchor Options: Session, Day, Week, Month, Quarter, Year. Choose based on your trading timeframe. Bands: Up to three pairs (X1, X2, X3) showing statistical deviation. Price at outer bands often reverses. Auto-Hide on HTF: VWAP hides on Daily/Weekly/Monthly charts automatically unless you enable anchored mode. Use VWAP as: Directional bias (above = bullish, below = bearish) Mean reversion levels (outer bands) Support/resistance (the VWAP line itself) Previous Day High/Low: Automatically plots yesterday's high and low on intraday charts: Updates at start of each new trading day Theme-aware colors (dark text for light charts, light text for dark charts) Hidden automatically on Daily/Weekly/Monthly charts These levels are critical for intraday traders - institutions watch them closely as support/resistance. Opening Range Breakout (ORB): Tracks the high/low of the first 5, 15, 30, or 60 minutes of the trading session: Customizable session times (preset for NYSE, LSE, TSE, or custom) Shows current breakout status in Bias Table row (ABOVE, BELOW, INSIDE, BUILDING) Intraday only - auto-disabled on Daily+ charts ORB is a classic day trading strategy - breakout above opening range often leads to continuation. Extra Labels: Change from Open %: Shows how far price has moved from session open (intraday) or daily open (HTF). Green if positive, red if negative. ADX Badge: Small label at bottom of last bar showing current ADX value. Green when above your minimum threshold, red when below. RSI Badge: Small label at top of last bar showing current RSI value with zone status (buy zone, sell zone, or neutral). These labels provide quick at-a-glance confirmation without needing separate indicator windows. --- 8. HOW TO USE THE INDICATOR Step 1: Add to Chart Load the indicator on your chosen asset and timeframe First time: Everything is enabled by default - the chart will look busy Don't panic - you'll turn off what you don't need Step 2: Start Simple Turn OFF everything except: UT Bot labels (keep these ON) Bias Table (keep this ON) Moving Averages (Fast and Medium only) Suggested Stop Loss and Take Profits Hide everything else initially. Get comfortable with the basic UT Bot + Bias Table workflow first. Step 3: Learn the Core Workflow UT Bot gives a Buy or Sell signal Check Bias Table AVG column - do you have multi-timeframe alignment? If yes, enter the trade Place stop at Suggested Stop Loss line Scale out at TP levels Exit on opposite UT signal Trade this simple system for a week. Get a feel for signal frequency and win rate with your settings. Step 4: Add Filters Gradually If you're getting too many losing signals (whipsaws in choppy markets), add filters one at a time: Try: "Require 2-Bar Trend Confirmation" - wait for 2 bars to confirm direction Try: ADX filter with minimum threshold - only trade when trend strength is sufficient Try: RSI pullback filter - only enter on pullbacks, not chasing Try: Volume filter - require above-average volume Add one filter, test for a week, evaluate. Repeat. Step 5: Enable Advanced Features (Optional) Once you're profitable with the core system, add: Supertrend for additional trend confirmation Candlestick patterns for reversal warnings VWAP for institutional anchor reference ORB for intraday breakout context ZLSMA for low-lag trend following Step 6: Optimize Settings Every setting has a detailed tooltip explaining what it does and typical values. Hover over any input to read: What the parameter controls How it impacts trading Suggested ranges for scalping, day trading, and swing trading Start with defaults, then adjust based on your results and style. Step 7: Set Up Alerts Right-click chart → Add Alert → Condition: "Luxy Momentum v6" → Choose: "UT Bot — Buy" for long entries "UT Bot — Sell" for short entries "Base Long/Short" for filtered MA cross signals Optionally enable "Send real-time alert() on UT flip" in settings for immediate notifications. Common Workflow Variations: Conservative Trader: UT signal + Base signal + Candlestick pattern + Bias AVG > 70% Enter only at major support/resistance Wider UT sensitivity, multiple filters Aggressive Trader: UT signal + Bias AVG > 60% Enter immediately, no waiting Tighter UT sensitivity, minimal filters Swing Trader: Focus on Daily/Weekly Bias alignment Ignore intraday noise Use ORB and PDH/PDL less (or not at all) Wider stops, patient approach --- 9. PERFORMANCE AND OPTIMIZATION The indicator is optimized for speed, but with 15+ features running simultaneously, chart load time can add up. Here's how to keep it fast: Biggest Performance Gains: Disable Unused Timeframes: In "Time Frames" settings, turn OFF any timeframe you don't actively trade. Each disabled TF saves 10-15% calculation time. If you only day trade 5m, 15m, 1h, disable 1m, 2h, 4h. Hide Bias Table on Daily+: If you only trade intraday, enable "Hide BIAS table on 1D or above". This skips ALL table calculations on higher timeframes. Draw UT Visuals Only on Bar Close: Reduces intrabar rendering of SL/TP/Entry lines. Has ZERO impact on logic or alerts - purely visual optimization. Additional Optimizations: Turn off VWAP bands if you don't use them Disable candlestick patterns if you don't trade them Turn off Supertrend fill if you find it distracting (keep the line) Reduce "Limit to 10 bars" for SL/TP lines to minimize line objects Performance Features Built-In: Smart Caching: Higher timeframe data (3-day bias, weekly bias, etc.) updates once per day, not every bar Conditional Calculations: Volume filter only calculates when enabled. Swing filter only runs when enabled. Nothing computes if turned off. Modular Design: Every component is independent. Turn off what you don't need without breaking other features. Typical Load Times: 5m chart, all features ON, 7 timeframes: ~2-3 seconds 5m chart, core features only, 3 timeframes: ~1 second 1m chart, all features: ~4-5 seconds (many bars to calculate) If loading takes longer, you likely have too many indicators on the chart total (not just this one). --- 10. FAQ Q: How is this different from standard UT Bot indicators? A: Standard UT Bot (originally by @QuantNomad) is just the ATR trailing line and flip signals. This implementation adds: - Volume weighting and momentum adjustment to the trailing calculation - Multiple confirmation filters (swing, %, 2-bar, ZLSMA) - Smart composite stop loss system from multiple S/R layers - R-multiple take profit system with freeze-on-touch - Integration with multi-timeframe Bias Table - Visual audit trail with checkmarks Q: Can I use this for automated trading? A: The indicator is designed for discretionary trading. While it has clear signals and alerts, it's not a mechanical system. Context and judgment are required. Q: Does it repaint? A: No. All signals respect bar close. UT Bot logic runs intrabar but signals only trigger on confirmed bars. Alerts fire correctly with no lookahead. Q: Do I need to use all the features? A: Absolutely not. The indicator is modular. Many profitable traders use just UT Bot + Bias Table + Moving Averages. Start simple, add complexity only if needed. Q: How do I know which settings to use? A: Every single input has a detailed tooltip. Hover over any setting to see: What it does How it affects trading Typical values for scalping, day trading, swing trading Start with defaults, adjust gradually based on results. Q: Can I use this on crypto 24/7 markets? A: Yes. ORB will not work (no defined session), but everything else functions normally. Use "Day" anchor for VWAP instead of "Session". Q: The Bias Table is blank or not showing. A: Check: "Show Table" is ON Table position isn't overlapping another indicator's table (change position) At least one row is enabled "Hide BIAS table on 1D or above" is OFF (if on Daily+ chart) Q: Why are candlestick patterns not appearing? A: Patterns are relatively rare by design - they only appear at genuine reversal points. Check: Pattern toggles are ON "Min candle body %" isn't too high (try 0.05-0.10) You're looking at a chart with actual reversals (not strong trending market) Q: UT Bot is too sensitive/not sensitive enough. A: Adjust "Sensitivity (Key×ATR)". Lower number = tighter stop, more signals. Higher number = wider stop, fewer signals. Read the tooltip for guidance. Q: Can I get alerts for the Bias Table? A: The Bias Table is a dashboard for visual analysis, not a signal generator. Set alerts on UT Bot or Base signals, then manually check Bias Table for confirmation. Q: Does this work on stocks with low volume? A: Yes, but turn OFF the volume filter. Low volume stocks will never meet relative volume requirements. Q: How often should I check the Bias Table? A: Before every entry. It takes 2 seconds to glance at the AVG column and headline rows. This one check can save you from fighting the trend. Q: What if UT signal and Base signal disagree? A: UT Bot is more aggressive (ATR trailing). Base signals are more conservative (MA cross + filters). If they disagree, either: Wait for both to align (safest) Take the UT signal but with smaller size (aggressive) Skip the trade (conservative) There's no "right" answer - depends on your risk tolerance. --- FINAL NOTES The indicator gives you an edge. How you use that edge determines results. For questions, feedback, or support, comment on the indicator page or message the author. Happy Trading!
Pine Script® インジケーター
orenluxyの投稿
39
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model. Original Script Link This indicator is built on top of my volume sampling engine. See the base implementation here: Why Volume Sampling Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals. Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally: filters dead time by skipping low volume chop; standardizes the information content per bar, improving comparability across regimes; stabilizes volatility estimates used inside banded indicators; gives trend and breakout logic cleaner state transitions with fewer micro flips. What this tool does It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock. Core Features Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user. Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles. Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars. Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme. Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats. Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series. How it works Sampling Pick Sampling Method = Volume or Dollar Bars. Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant. The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation. Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic. Supertrend on the sampled stream Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle. Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR . Apply classic trailing band and direction rules to produce Supertrend and trend state. Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints. Reading the display Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls. Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1. Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles. Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop. Settings you will use most Data Settings Sampling Method - Volume or Dollar Bars. Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother. Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes. Max Stored Samples - Ring buffer limit for performance. Indicator Settings SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout. Supertrend Source - Price field from the synthetic candle. ATR Period and Factor - Standard Supertrend controls applied on the synthetic series. Visuals and UI Show Synthetic Bars - Turn synthetic candles on or off. Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive. Mark new samples - Puts a dot when a bucket closes. Show Time Bars - Overlay regular candles for comparison. Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction. Line Width , Colors , and Stats Table toggles. Some workflow notes: Trend Following Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples. Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars. Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries. Breakout and Continuation Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend. The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts. Mean Reversion In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens. Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting. Stats table (top right) Method and Total Samples - Sampling regime and current synthetic history length. Current Vol or Dollar and Threshold - Live bucket fill versus the trigger. Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress. Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes. Why this reduces noise Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs. Notes and tips Use Dollar Bars on assets where nominal price varies widely over time or across symbols. Median filter can resist single burst outliers when setting dynamic thresholds. If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests. Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching. Link again for reference Original Volume Based Sampling engine: Bottom line When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
Pine Script® インジケーター
BackQuantの投稿
Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex) # Short Description Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX. --- # What it does (Quick) * **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle. * **Real-time** — accumulates intrabar volume live by tick-direction. * **History Mode** — splits Up/Down on closed bars via simple or range-aware logic. * **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend). * **Contextual opacity** — stronger signals appear bolder. * **Label density** — draw every N-th bar and limit to last X bars for performance. * **Alerts** — thresholds for |Δ|, Δ%, and UpShare%. --- # How it works (Real-Time vs History) * **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available. * **History (closed bars):** * **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history. * **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars. * **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low. * **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**. --- # Rows & Meaning * **Volume** — total bar volume (no split). * **UpVol / DownVol** — directional intrabar volume. * **Delta (Δ)** — UpVol − DownVol. * **Absolute**: raw units * **Relative (Δ%)**: Δ / (Up+Down) × 100 * **Both**: shows both formats * **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish. * Helpful icons: ▲ (>65%), ▼ (<35%). --- # MTF Dashboard (🔧 Enable Dashboard) A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons. --- # Inputs (Grouped) ## Display * Toggle rows: **Volume / Up / Down / Delta / UpShare** * **Delta Display**: Absolute / Relative / Both ## Realtime & History * **History Mode**: Auto / None / Approx / Price Action Based * **Compact Numbers**: 1.2k, 1.25M, 3.4B… ## Theme & UI * **Theme Mode**: Auto / Light / Dark * **Row Spacing**: vertical spacing between rows * **Top Row Y**: moves the whole grid vertically * **Draw Guide Lines**: faint dotted guides * **Text Size**: Tiny / Small / Normal / Large ## 🔧 Dashboard Settings * **Enable Dashboard** * **📏 Table Text Size**: Tiny…Huge * **🦓 Zebra Rows** * **🔲 Table Border** ## ⏰ Timeframes (for Dashboard) * **M1…D1** toggles ## Contextual Coloring * **Enable Contextual Coloring**: opacity by signal strength * **Δ% cap / Share offset cap**: saturation caps * **Min/Max transparency**: solid vs faint extremes ## Label Density & Size * **Show every N-th bar**: draw labels only every Nth bar * **Limit to last X bars**: keep labels only in the most recent X bars ## Colors * Up / Down / Text / Guide ## Alerts * **Delta Threshold (abs)** — |Δ| in volume units * **UpShare > / <** — bullish/bearish thresholds * **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels --- # How to use (Quick Start) 1. Add the indicator to your chart (overlay=false → separate pane). 2. **History Mode**: * Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history. * Stocks/Index → prefer **None** or **Price Action Based** for safer splits. 3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**. 4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves. 5. **Dashboard**: enable and pick only the TFs you actually use. 6. **Alerts**: set thresholds (ideas below). --- # Alerts (in TradingView) Add alert → pick this indicator → choose any of: * **Delta exceeds threshold** (|Δ| > X) * **UpShare above threshold** (UpShare% > X) * **UpShare below threshold** (UpShare% < X) * **Relative Delta above +X%** * **Relative Delta below −X%** **Starter thresholds (tune per symbol & TF):** * **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish) * **FX (tick volume)**: UpShare > 60–65% or < 40–35% * **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k) --- # Notes by Market Type * **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx. * **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday. * **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx. --- # “All Timeframes” accuracy * Works on **any TF** (M1 → D1/W1). * **Real-time accuracy** is strong for the open bar (live accumulation). * **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced). * The MTF dashboard uses `request.security` and therefore follows the same logic per TF. --- # Trade Ideas (Use-Cases) * **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries. * **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend. * **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias. --- # Advantages * **True-feeling live flow** on the open bar. * **Adaptable history** (three modes) to match data quality. * **Clean visual layout** with guides, compact numbers, contextual opacity. * **MTF snapshot** for quick bias read. * **Performance controls** (last X bars, every N-th bar). --- # Limitations & Care * **FX uses tick volume** — interpret Δ/Share accordingly. * **History Mode is an approximation** — confirm with trend/structure/liquidity context. * **Illiquid symbols** can produce noisy or contradictory signals. * **Too many labels** can slow charts → raise N, lower X, or disable guides. --- # Best Practices (Checklist) * Crypto/Futures: prefer **Price Action Based** for history. * Stocks: **None** or **Price Action Based**; be cautious with **Approx**. * FX: pair Δ% & UpShare% with session context (London/NY) and volatility. * If labels overlap: tweak **Row Spacing** and **Text Size**. * In the dashboard, keep only the TFs you actually act on. * Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset. --- # FAQ **1) Why do some closed bars show 0%/100% UpShare?** You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits. **2) Δ% looks strong but price doesn’t move — why?** Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations. **3) Performance slowdown — what to do?** Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**. **4) Dashboard values don’t “match” the grid exactly?** Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal. --- # Short “Store” Marketing Blurb Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
Pine Script® インジケーター
a_jabbaroffの投稿
CVD Polarity Indicator (With Rolling Smoothed)📊 CVD Polarity Indicator (with Rolling Smoothing) Purpose The CVD Polarity Indicator combines Cumulative Volume Delta (CVD) with price bar direction to measure whether buying or selling pressure is in agreement with price action. It then smooths that signal over time, making it easier to see underlying volume-driven market trends. This indicator is essentially a volume–price agreement oscillator: - It compares price direction with volume delta (CVD). - Translates that into per-bar polarity. - Smooths it into a rolling sum for clarity. - Adds a short EMA to highlight turning points. The end result: a tool that helps you see when price action is backed by real volume flows versus when it’s running on weak participation. __________________________________________________________________________________ 1. Cumulative Volume Delta (CVD) What it is: CVD is the cumulative sum of buying vs. selling pressure measured by volume. - If a bar closes higher than it opens → that bar’s volume is treated as buying pressure (+volume). - If a bar closes lower than it opens → that bar’s volume is treated as selling pressure (–volume). Rolling version: Instead of accumulating indefinitely (which just creates a line that trends forever), this indicator uses a rolling sum over a user-defined number of bars (cumulation_length, default 14). - This shows the net delta in recent bars, making the CVD more responsive and localized. 2. Bar Direction vs. CVD Change Each bar has two pieces of directional information: 1. Bar direction: Whether the candle closed above or below its open (close - open). 2. CVD change: Whether cumulative delta increased or decreased from the prior bar (cvd - cvd ). By comparing these two: - Agreement (both up or both down): → Polarity = +volume (if bullish) or –volume (if bearish). - Disagreement (bar up but CVD down, or bar down but CVD up): → Polarity flips sign, signaling divergence between price and volume. Thus, raw polarity = a per-bar measure of whether price action and volume delta are in sync. 3. Polarity Smoothing (Rolling Polarity) - Problem with raw polarity: It flips bar-to-bar and looks very jagged — not great for seeing trends. - Solution: The indicator applies a rolling sum over the past polarity_length bars (default 14). - This creates a smoother curve, representing the net polarity over time. - Positive values = net bullish alignment (buyers stronger). - Negative values = net bearish alignment (sellers stronger). Think of it like an oscillator showing whether buyers or sellers have had control recently. 4. EMA Smoothing Finally, a 10-period EMA is applied on top of the rolling polarity line: - This further reduces noise. - It helps highlight shifts in the underlying polarity trend. - Crossovers of the polarity line and its EMA can serve as trade signals (bullish/bearish inflection points). ________________________________________________________________________________ How to Read It 1. Polarity above zero → Recent bars show more bullish agreement between price and volume. 2. Polarity below zero → Recent bars show more bearish agreement. 3. Polarity diverging from price → If price goes up but polarity trends down, it signals weakening buying pressure (potential reversal). 4. EMA crossovers → - Polarity crossing above its EMA = bullish momentum shift. - Polarity crossing below its EMA = bearish momentum shift. Practical Use Cases - Trend Confirmation Use polarity to confirm whether a price move is supported by volume. If price rallies but polarity stays negative, the move is weak. - Divergence Signals Watch for divergences between price trend and polarity trend (e.g., higher highs in price but lower highs in polarity). - Momentum Shifts Use EMA crossovers as signals that the underlying balance of buying/selling has flipped.
Pine Script® インジケーター
Cruiserの投稿
ADR/ATR Session No Probability Table by LKHere you go—clear, English docs you can drop into your script’s description or share with teammates. ADR/ATR Session by LK — Overview This indicator summarizes Average Daily Range (ADR) and Average True Range (ATR) for two horizons: • Session H4 (e.g., 06:00–13:00 on a 4‑hour chart) • Daily (D) It shows: • Current ADR/ATR values (using your chosen smoothing method) • How much of ADR/ATR today/this bar has already been consumed (% of ADR/ATR) • ADR/ATR as a percent of price • Optional probability blocks: likelihood that %ADR will exceed user‑defined thresholds over a lookback window • Optional on‑chart lines for the current H4 and Daily candles: Open, ADR High, ADR Low ⸻ What the metrics mean • ADR (H4 / D): Moving average of the bar range (high - low). • ATR (H4 / D): Moving average of True Range (max(hi-lo, |hi-close |, |lo-close |)). • % of ADR (curr H4): (H4 range of the current H4 bar) / ADR(H4) × 100. Updates live even if the current time is outside the session. • % of ADR (Daily): (today’s intra‑day range) / ADR(D) × 100. • % of ATR (curr H4 / Daily): TR / ATR × 100 for that horizon. • ADR % of Price / ATR % of Price: ADR or ATR divided by current price × 100 (a quick “volatility vs. price” gauge). Session logic (H4): ADR/ATR(H4) only update on bars that fall inside the configured session window; outside the window the values hold steady (no recalculation “bleed”). Daily range tracking: The indicator tracks today’s high/low in real‑time and resets at the day change. ⸻ Inputs (quick reference) Core • Length (ADR/ATR): smoothing length for ADR/ATR (default 21). • Wait for Higher TF Bar Close: if true, updates ADR/ATR only after the higher‑TF bar closes when using request.security. Timeframes • Session Timeframe (H4): default 240. • Daily Timeframe: default D. Session time • Session Timezone: “Chart” (default) or a fixed timezone. • Session Start Hour, End Hour (minutes are fixed to 0 in this version). Smoothing methods • H4 ADR Method / H4 ATR Method: SMA/EMA/RMA/WMA. • Daily ADR Method / Daily ATR Method: SMA/EMA/RMA/WMA. Table appearance • Table BG, Table Text, Table Font Size. Lines (optional) • Show current H4 segments, Show current Daily segments • Line colors for Open / ADR High / ADR Low • Line width Probability • H4 Probability Lookback (bars): number of H4 bars to examine (e.g., 300). • Daily Probability Lookback (days): number of D bars (e.g., 180). • ADR thresholds (%): CSV list of thresholds (e.g., 25,50,55,60,65,70,75,80,85,90,95,100,125,150). The table will show the % of lookback bars where %ADR ≥ threshold. Tip: If you want probabilities only for session H4 bars (not every H4 bar), ask and I can add a toggle to filter by inSess. ⸻ How to read the table H4 block • ADR (method) / ATR (method): the session‑aware averages. • % of ADR (curr H4): live progress of this H4 bar toward the session ADR. • ADR % of Price: ADR(H4) relative to price. • % of ATR (curr H4) and ATR % of Price: same idea for ATR. H4 Probability (lookback N bars) • Rows like “≥ 80% ADR” show the fraction (in %) of the last N H4 bars that reached at least 80% of ADR(H4). Daily block • Mirrors the H4 block, but for Daily. Daily Probability (lookback M days) • Rows like “≥ 100% ADR” show the fraction of the last M daily bars whose daily range reached at least 100% of ADR(D). ⸻ Practical usage • Use % of ADR (curr H4 / Daily) to judge exhaustion or room left in the day/session. E.g., if Daily %ADR is already 95%, be cautious with momentum continuation trades. • The probability tables give a quick historical context: If “≥ 125% ADR” is ~18%, the market rarely stretches that far; your trade sizing/targets can reflect that. • ADR/ATR % of Price helps normalize volatility between instruments. ⸻ Troubleshooting • If probability rows are blank: ensure lookback windows are large enough (and that the chart has enough history). • If ADR/ATR show … (NA): usually you don’t have enough bars for the chosen length/TF yet. • If line segments are missing: verify you’re on a chart with visible current H4/D bars and the toggles are enabled. ⸻ Notes & customization ideas • Add a toggle to count only session bars in H4 probability. • Add separate thresholds for H4 vs Daily. • Let users pick minutes for session start/end if needed. • Add alerts when %ADR crosses specified thresholds. If you want me to bundle any of the “ideas” above into the code, say the word and I’ll ship a clean patch.
Pine Script® インジケーター
kimngan894923の投稿
Helper Lib by tristanlee85Library "helpers" This library offers various functions and types based on the algorithmic concepts as authored by ICT. kv(key, value)   Returns a string of the key/value set, suitable for debug logging   Parameters:      key (string)      value (string)   Returns: A string formatted as "{key}: {value}" kv(key, value)   Parameters:      key (string)      value (int) kv(key, value)   Parameters:      key (string)      value (float) kv(key, value)   Parameters:      key (string)      value (bool) method enable(this, enable)   Enable/Disable debug logging   Namespace types: Debugger   Parameters:      this (Debugger)      enable (bool) : Set to `true` by default. method group(this, label)   Creates a group label for nested debug() invocations   Namespace types: Debugger   Parameters:      this (Debugger)      label (string) method groupEnd(this, label)   Ends the specified debug group   Namespace types: Debugger   Parameters:      this (Debugger)      label (string) method log(this, s, arg1, arg2, arg3, arg4, arg5)   Logs the param values if debug mode is enabled   Namespace types: Debugger   Parameters:      this (Debugger)      s (string) : Title of the log message      arg1 (string)      arg2 (string)      arg3 (string)      arg4 (string)      arg5 (string) method logIf(this, expr, s, arg1, arg2, arg3, arg4, arg5)   Same behavior as debug() except will only log if the passed expression is true   Namespace types: Debugger   Parameters:      this (Debugger)      expr (bool) : Boolean expression to determine if debug logs should be logged      s (string) : Title of the log message      arg1 (string)      arg2 (string)      arg3 (string)      arg4 (string)      arg5 (string) style_getLineStyleFromType(opt)   Returns the corresponding line style constant for the given LineStyleType   Parameters:      opt (series LineStyleType) : The selected line style type   Returns: The Pine Script line style constant style_getTextSizeFromType(opt)   Returns the corresponding text size constant for the given TextSizeType   Parameters:      opt (series TextSizeType) : The selected text size type   Returns: The Pine Script text size constant style_getTextHAlignFromType(t)   Returns the corresponding horizontal text align constant for the given HAlignType   Parameters:      t (series HAlignType) : The selected text align type   Returns: The Pine Script text align constant style_getTextVAlignFromType(t)   Returns the corresponding vertical text align constant for the given VAlignType   Parameters:      t (series VAlignType) : The selected text align type   Returns: The Pine Script text align constant format_sentimentType(sentiment, pd)   Used to produce a string with the sentiment and PD array type (e.g., "+FVG")   Parameters:      sentiment (series SentimentType) : The sentiment value (e.g., SentimentType.BULLISH)      pd (series PDArrayType) : The price data array (e.g., PDArrayType.FVG)   Returns: A formatted string with the sentiment and PD array (e.g., "+FVG") format_timeToString(timestamp)   Formats a UNIX timestamp into a date and time string based on predefined formats   Parameters:      timestamp (int) : The UNIX timestamp to format   Returns: A formatted string as "MM-dd (E) - HH:mm" method init(this)   Initializes the session and validates the configuration. This MUST be called immediately after creating a new instance.   Namespace types: Session   Parameters:      this (Session) : The Session object reference   Returns: The Session object (chainable) or throws a runtime error if invalid method isActive(this, _time)   Determines if the session is active based on the current bar time   Namespace types: Session   Parameters:      this (Session) : The Session object reference      _time (int)   Returns: `true` if the session is currently active; `false` otherwise method draw(this)   Draws the line and optional label   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference   Returns: The LineLabel object (chainable) method extend(this, x)   Extends the line and label right to the specified bar index   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference      x (int) : The bar index to extend to   Returns: The LineLabel object (chainable) method destroy(this)   Removes the line and label from the chart   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference isFVG(includeVI, barIdx)   Checks if the previous bars form a Fair Value Gap (FVG)   Parameters:      includeVI (bool) : If true, includes Volume Imbalance in the FVG calculation      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if a FVG is detected; otherwise, `na` isVolumeImbalance(barIdx)   Checks if the previous bars form a Volume Imbalance (VI)   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if a VI is detected; otherwise, `na` isLiquidityVoid(barIdx)   Checks if the previous bars form a Liquidity Void (LV)   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if an LV is detected; otherwise, `na` isSwingPoint(barIdx)   Checks if the previous bars form a swing point   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A SwingPoint object if a swing point is detected; otherwise, `na` Debugger   A debug logging utility with group support   Fields:      enabled (series bool)      _debugGroupStack (array) Session   Defines a trading session with a name and time range. When creating a new instance of this type, you MUST call init() immediately.   Fields:      name (series string) : A display-friendly name (e.g., "NY AM")      session (series string) : A string defining the session time range (e.g., "1300-1400")      enabled (series bool) : Optional flag for custom logic; defaults to false      start (series int) : UNIX time representing the session start (set via isActive())      end (series int) : UNIX time representing the session end (set via isActive())      _t (series int)      _start_HH (series float)      _start_mm (series float)      _end_HH (series float)      _end_mm (series float) Gap   Represents a price inefficiency (gap) with details on sentiment and price levels   Fields:      type (series SentimentType) : The sentiment of the gap (e.g., SentimentType.BULLISH)      name (series string) : A display-friendly name (e.g., "+FVG")      startTime (series int) : UNIX time value for the gap's start      endTime (series int) : UNIX time value for the gap's end      startIndex (series int) : Bar index where the gap starts      endIndex (series int) : Bar index where the gap ends      gapLow (series float) : The lowest price level of the gap      gapHigh (series float) : The highest price level of the gap      ce (series float) : The consequent encroachment level of the gap SwingPoint   Represents a swing point with details on type and price level   Fields:      type (series SwingPointType) : The type of swing point (e.g., SwingPointType.HIGH)      time (series int) : UNIX time value for the swing point      barIdx (series int) : Bar index where the swing point occurs      price (series float) : The price level of the swing point which is either the high or low of the middle bar LineLabel   Combines a line and box type to produce a line with a label that is properly aligned   Fields:      x (series int) : The X-axis starting point as a bar index      y (series float) : The Y-axis starting point as the price level      color (series color) : Both the line and text color      width (series int) : Thickness of the line      label (series string) : Text to display      showLabel (series bool) : Boolean to conditionally show/hide the label (default is false)      lineStyle (series LineStyleType) : The style of the line      textSize (series TextSizeType)      _b (series box)      _l (series line)
Pine Script® ライブラリ
tristanlee85の投稿
real_time_candlesIntroduction The Real-Time Candles Library provides comprehensive tools for creating, manipulating, and visualizing custom timeframe candles in Pine Script. Unlike standard indicators that only update at bar close, this library enables real-time visualization of price action and indicators within the current bar, offering traders unprecedented insight into market dynamics as they unfold. This library addresses a fundamental limitation in traditional technical analysis: the inability to see how indicators evolve between bar closes. By implementing sophisticated real-time data processing techniques, traders can now observe indicator movements, divergences, and trend changes as they develop, potentially identifying trading opportunities much earlier than with conventional approaches. Key Features The library supports two primary candle generation approaches: Chart-Time Candles: Generate real-time OHLC data for any variable (like RSI, MACD, etc.) while maintaining synchronization with chart bars. Custom Timeframe (CTF) Candles: Create candles with custom time intervals or tick counts completely independent of the chart's native timeframe. Both approaches support traditional candlestick and Heikin-Ashi visualization styles, with options for moving average overlays to smooth the data. Configuration Requirements For optimal performance with this library: Set max_bars_back = 5000 in your script settings When using CTF drawing functions, set max_lines_count = 500, max_boxes_count = 500, and max_labels_count = 500 These settings ensure that you will be able to draw correctly and will avoid any runtime errors. Usage Examples Basic Chart-Time Candle Visualization // Create real-time candles for RSI float rsi = ta.rsi(close, 14) Candle rsi_candle = candle_series(rsi, CandleType.candlestick) // Plot the candles using Pine's built-in function plotcandle(rsi_candle.Open, rsi_candle.High, rsi_candle.Low, rsi_candle.Close, "RSI Candles", rsi_candle.candle_color, rsi_candle.candle_color) Multiple Access Patterns The library provides three ways to access candle data, accommodating different programming styles: // 1. Array-based access for collection operations Candle candles = candle_array(source) // 2. Object-oriented access for single entity manipulation Candle candle = candle_series(source) float value = candle.source(Source.HLC3) // 3. Tuple-based access for functional programming styles = candle_tuple(source) Custom Timeframe Examples // Create 20-second candles with EMA overlay plot_ctf_candles( source = close, candle_type = CandleType.candlestick, sample_type = SampleType.Time, number_of_seconds = 20, timezone = -5, tied_open = true, ema_period = 9, enable_ema = true ) // Create tick-based candles (new candle every 15 ticks) plot_ctf_tick_candles( source = close, candle_type = CandleType.heikin_ashi, number_of_ticks = 15, timezone = -5, tied_open = true ) Advanced Usage with Custom Visualization // Get custom timeframe candles without automatic plotting CandleCTF my_candles = ctf_candles_array( source = close, candle_type = CandleType.candlestick, sample_type = SampleType.Time, number_of_seconds = 30 ) // Apply custom logic to the candles float ema_values = my_candles.ctf_ema(14) // Draw candles and EMA using time-based coordinates my_candles.draw_ctf_candles_time() ema_values.draw_ctf_line_time(line_color = #FF6D00) Library Components Data Types Candle: Structure representing chart-time candles with OHLC, polarity, and visualization properties CandleCTF: Extended candle structure with additional time metadata for custom timeframes TickData: Structure for individual price updates with time deltas Enumerations CandleType: Specifies visualization style (candlestick or Heikin-Ashi) Source: Defines price components for calculations (Open, High, Low, Close, HL2, etc.) SampleType: Sets sampling method (Time-based or Tick-based) Core Functions get_tick(): Captures current price as a tick data point candle_array(): Creates an array of candles from price updates candle_series(): Provides a single candle based on latest data candle_tuple(): Returns OHLC values as a tuple ctf_candles_array(): Creates custom timeframe candles without rendering Visualization Functions source(): Extracts specific price components from candles candle_ctf_to_float(): Converts candle data to float arrays ctf_ema(): Calculates exponential moving averages for candle arrays draw_ctf_candles_time(): Renders candles using time coordinates draw_ctf_candles_index(): Renders candles using bar index coordinates draw_ctf_line_time(): Renders lines using time coordinates draw_ctf_line_index(): Renders lines using bar index coordinates Technical Implementation Notes This library leverages Pine Script's varip variables for state management, creating a sophisticated real-time data processing system. The implementation includes: Efficient tick capturing: Samples price at every execution, maintaining temporal tracking with time deltas Smart state management: Uses a hybrid approach with mutable updates at index 0 and historical preservation at index 1+ Temporal synchronization: Manages two time domains (chart time and custom timeframe) The tooltip implementation provides crucial temporal context for custom timeframe visualizations, allowing users to understand exactly when each candle formed regardless of chart timeframe. Limitations Custom timeframe candles cannot be backtested due to Pine Script's limitations with historical tick data Real-time visualization is only available during live chart updates Maximum history is constrained by Pine Script's array size limits Applications Indicator visualization: See how RSI, MACD, or other indicators evolve in real-time Volume analysis: Create custom volume profiles independent of chart timeframe Scalping strategies: Identify short-term patterns with precisely defined time windows Volatility measurement: Track price movement characteristics within bars Custom signal generation: Create entry/exit signals based on custom timeframe patterns Conclusion The Real-Time Candles Library bridges the gap between traditional technical analysis (based on discrete OHLC bars) and the continuous nature of market movement. By making indicators more responsive to real-time price action, it gives traders a significant edge in timing and decision-making, particularly in fast-moving markets where waiting for bar close could mean missing important opportunities. Whether you're building custom indicators, researching price patterns, or developing trading strategies, this library provides the foundation for sophisticated real-time analysis in Pine Script. Implementation Details & Advanced Guide Core Implementation Concepts The Real-Time Candles Library implements a sophisticated event-driven architecture within Pine Script's constraints. At its heart, the library creates what's essentially a reactive programming framework handling continuous data streams. Tick Processing System The foundation of the library is the get_tick() function, which captures price updates as they occur: export get_tick(series float source = close, series float na_replace = na)=> varip float price = na varip int series_index = -1 varip int old_time = 0 varip int new_time = na varip float time_delta = 0 // ... This function: Samples the current price Calculates time elapsed since last update Maintains a sequential index to track updates The resulting TickData structure serves as the fundamental building block for all candle generation. State Management Architecture The library employs a sophisticated state management system using varip variables, which persist across executions within the same bar. This creates a hybrid programming paradigm that's different from standard Pine Script's bar-by-bar model. For chart-time candles, the core state transition logic is: // Real-time update of current candle candle_data := Candle.new(Open, High, Low, Close, polarity, series_index, candle_color) candles.set(0, candle_data) // When a new bar starts, preserve the previous candle if clear_state candles.insert(1, candle_data) price.clear() // Reset state for new candle Open := Close price.push(Open) series_index += 1 This pattern of updating index 0 in real-time while inserting completed candles at index 1 creates an elegant solution for maintaining both current state and historical data. Custom Timeframe Implementation The custom timeframe system manages its own time boundaries independent of chart bars: bool clear_state = switch settings.sample_type SampleType.Ticks => cumulative_series_idx >= settings.number_of_ticks SampleType.Time => cumulative_time_delta >= settings.number_of_seconds This dual-clock system synchronizes two time domains: Pine's execution clock (bar-by-bar processing) The custom timeframe clock (tick or time-based) The library carefully handles temporal discontinuities, ensuring candle formation remains accurate despite irregular tick arrival or market gaps. Advanced Usage Techniques 1. Creating Custom Indicators with Real-Time Candles To develop indicators that process real-time data within the current bar: // Get real-time candles for your data Candle rsi_candles = candle_array(ta.rsi(close, 14)) // Calculate indicator values based on candle properties float signal = ta.ema(rsi_candles.first().source(Source.Close), 9) // Detect patterns that occur within the bar bool divergence = close > close and rsi_candles.first().Close < rsi_candles.get(1).Close 2. Working with Custom Timeframes and Plotting For maximum flexibility when visualizing custom timeframe data: // Create custom timeframe candles CandleCTF volume_candles = ctf_candles_array( source = volume, candle_type = CandleType.candlestick, sample_type = SampleType.Time, number_of_seconds = 60 ) // Convert specific candle properties to float arrays float volume_closes = volume_candles.candle_ctf_to_float(Source.Close) // Calculate derived values float volume_ema = volume_candles.ctf_ema(14) // Create custom visualization volume_candles.draw_ctf_candles_time() volume_ema.draw_ctf_line_time(line_color = color.orange) 3. Creating Hybrid Timeframe Analysis One powerful application is comparing indicators across multiple timeframes: // Standard chart timeframe RSI float chart_rsi = ta.rsi(close, 14) // Custom 5-second timeframe RSI CandleCTF ctf_candles = ctf_candles_array( source = close, candle_type = CandleType.candlestick, sample_type = SampleType.Time, number_of_seconds = 5 ) float fast_rsi_array = ctf_candles.candle_ctf_to_float(Source.Close) float fast_rsi = fast_rsi_array.first() // Generate signals based on divergence between timeframes bool entry_signal = chart_rsi < 30 and fast_rsi > fast_rsi_array.get(1) Final Notes This library represents an advanced implementation of real-time data processing within Pine Script's constraints. By creating a reactive programming framework for handling continuous data streams, it enables sophisticated analysis typically only available in dedicated trading platforms. The design principles employed—including state management, temporal processing, and object-oriented architecture—can serve as patterns for other advanced Pine Script development beyond this specific application. ------------------------ Library "real_time_candles" A comprehensive library for creating real-time candles with customizable timeframes and sampling methods. Supports both chart-time and custom-time candles with options for candlestick and Heikin-Ashi visualization. Allows for tick-based or time-based sampling with moving average overlay capabilities. get_tick(source, na_replace)   Captures the current price as a tick data point   Parameters:      source (float) : Optional - Price source to sample (defaults to close)      na_replace (float) : Optional - Value to use when source is na   Returns: TickData structure containing price, time since last update, and sequential index candle_array(source, candle_type, sync_start, bullish_color, bearish_color)   Creates an array of candles based on price updates   Parameters:      source (float) : Optional - Price source to sample (defaults to close)      candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)      sync_start (simple bool) : Optional - Whether to synchronize with the start of a new bar      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles   Returns: Array of Candle objects ordered with most recent at index 0 candle_series(source, candle_type, wait_for_sync, bullish_color, bearish_color)   Provides a single candle based on the latest price data   Parameters:      source (float) : Optional - Price source to sample (defaults to close)      candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)      wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles   Returns: A single Candle object representing the current state candle_tuple(source, candle_type, wait_for_sync, bullish_color, bearish_color)   Provides candle data as a tuple of OHLC values   Parameters:      source (float) : Optional - Price source to sample (defaults to close)      candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)      wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles   Returns: Tuple representing current candle values method source(self, source, na_replace)   Extracts a specific price component from a Candle   Namespace types: Candle   Parameters:      self (Candle)      source (series Source) : Type of price data to extract (Open, High, Low, Close, or composite values)      na_replace (float) : Optional - Value to use when source value is na   Returns: The requested price value from the candle method source(self, source)   Extracts a specific price component from a CandleCTF   Namespace types: CandleCTF   Parameters:      self (CandleCTF)      source (simple Source) : Type of price data to extract (Open, High, Low, Close, or composite values)   Returns: The requested price value from the candle as a varip method candle_ctf_to_float(self, source)   Converts a specific price component from each CandleCTF to a float array   Namespace types: array   Parameters:      self (array)      source (simple Source) : Optional - Type of price data to extract (defaults to Close)   Returns: Array of float values extracted from the candles, ordered with most recent at index 0 method ctf_ema(self, ema_period)   Calculates an Exponential Moving Average for a CandleCTF array   Namespace types: array   Parameters:      self (array)      ema_period (simple float) : Period for the EMA calculation   Returns: Array of float values representing the EMA of the candle data, ordered with most recent at index 0 method draw_ctf_candles_time(self, sample_type, number_of_ticks, number_of_seconds, timezone)   Renders custom timeframe candles using bar time coordinates   Namespace types: array   Parameters:      self (array)      sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips      number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips      number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips      timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips   Returns: void - Renders candles on the chart using time-based x-coordinates method draw_ctf_candles_index(self, sample_type, number_of_ticks, number_of_seconds, timezone)   Renders custom timeframe candles using bar index coordinates   Namespace types: array   Parameters:      self (array)      sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips      number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips      number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips      timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips   Returns: void - Renders candles on the chart using index-based x-coordinates method draw_ctf_line_time(self, source, line_size, line_color)   Renders a line representing a price component from the candles using time coordinates   Namespace types: array   Parameters:      self (array)      source (simple Source) : Optional - Type of price data to extract (defaults to Close)      line_size (simple int) : Optional - Width of the line      line_color (simple color) : Optional - Color of the line   Returns: void - Renders a connected line on the chart using time-based x-coordinates method draw_ctf_line_time(self, line_size, line_color)   Renders a line from a varip float array using time coordinates   Namespace types: array   Parameters:      self (array)      line_size (simple int) : Optional - Width of the line, defaults to 2      line_color (simple color) : Optional - Color of the line   Returns: void - Renders a connected line on the chart using time-based x-coordinates method draw_ctf_line_index(self, source, line_size, line_color)   Renders a line representing a price component from the candles using index coordinates   Namespace types: array   Parameters:      self (array)      source (simple Source) : Optional - Type of price data to extract (defaults to Close)      line_size (simple int) : Optional - Width of the line      line_color (simple color) : Optional - Color of the line   Returns: void - Renders a connected line on the chart using index-based x-coordinates method draw_ctf_line_index(self, line_size, line_color)   Renders a line from a varip float array using index coordinates   Namespace types: array   Parameters:      self (array)      line_size (simple int) : Optional - Width of the line, defaults to 2      line_color (simple color) : Optional - Color of the line   Returns: void - Renders a connected line on the chart using index-based x-coordinates plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)   Plots tick-based candles with moving average   Parameters:      source (float) : Input price source to sample      candle_type (simple CandleType) : Type of candle chart to display      number_of_ticks (simple int) : Number of ticks per candle      timezone (simple int) : Timezone offset from UTC (-12 to +12)      tied_open (simple bool) : Whether to tie open price to close of previous candle      ema_period (simple float) : Period for the exponential moving average      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles      line_width (simple int) : Optional - Width of the moving average line, defaults to 2      ema_color (color) : Optional - Color of the moving average line      use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index   Returns: void - Creates visual candle chart with EMA overlay plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)   Plots tick-based candles without moving average   Parameters:      source (float) : Input price source to sample      candle_type (simple CandleType) : Type of candle chart to display      number_of_ticks (simple int) : Number of ticks per candle      timezone (simple int) : Timezone offset from UTC (-12 to +12)      tied_open (simple bool) : Whether to tie open price to close of previous candle      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles      use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index   Returns: void - Creates visual candle chart without moving average plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)   Plots time-based candles with moving average   Parameters:      source (float) : Input price source to sample      candle_type (simple CandleType) : Type of candle chart to display      number_of_seconds (simple float) : Time duration per candle in seconds      timezone (simple int) : Timezone offset from UTC (-12 to +12)      tied_open (simple bool) : Whether to tie open price to close of previous candle      ema_period (simple float) : Period for the exponential moving average      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles      line_width (simple int) : Optional - Width of the moving average line, defaults to 2      ema_color (color) : Optional - Color of the moving average line      use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index   Returns: void - Creates visual candle chart with EMA overlay plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)   Plots time-based candles without moving average   Parameters:      source (float) : Input price source to sample      candle_type (simple CandleType) : Type of candle chart to display      number_of_seconds (simple float) : Time duration per candle in seconds      timezone (simple int) : Timezone offset from UTC (-12 to +12)      tied_open (simple bool) : Whether to tie open price to close of previous candle      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles      use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index   Returns: void - Creates visual candle chart without moving average plot_ctf_candles(source, candle_type, sample_type, number_of_ticks, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, enable_ema, line_width, ema_color, use_time_indexing)   Unified function for plotting candles with comprehensive options   Parameters:      source (float) : Input price source to sample      candle_type (simple CandleType) : Optional - Type of candle chart to display      sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks)      number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)      number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)      timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12)      tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle      ema_period (simple float) : Optional - Period for the exponential moving average      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles      enable_ema (bool) : Optional - Whether to display the EMA overlay      line_width (simple int) : Optional - Width of the moving average line, defaults to 2      ema_color (color) : Optional - Color of the moving average line      use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index   Returns: void - Creates visual candle chart with optional EMA overlay ctf_candles_array(source, candle_type, sample_type, number_of_ticks, number_of_seconds, tied_open, bullish_color, bearish_color)   Creates an array of custom timeframe candles without rendering them   Parameters:      source (float) : Input price source to sample      candle_type (simple CandleType) : Type of candle chart to create (candlestick or Heikin-Ashi)      sample_type (simple SampleType) : Method for sampling data (Time or Ticks)      number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)      number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)      tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle      bullish_color (color) : Optional - Color for bullish candles      bearish_color (color) : Optional - Color for bearish candles   Returns: Array of CandleCTF objects ordered with most recent at index 0 Candle   Structure representing a complete candle with price data and display properties   Fields:      Open (series float) : Opening price of the candle      High (series float) : Highest price of the candle      Low (series float) : Lowest price of the candle      Close (series float) : Closing price of the candle      polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)      series_index (series int) : Sequential index identifying the candle in the series      candle_color (series color) : Color to use when rendering the candle      ready (series bool) : Boolean indicating if candle data is valid and ready for use TickData   Structure for storing individual price updates   Fields:      price (series float) : The price value at this tick      time_delta (series float) : Time elapsed since the previous tick in milliseconds      series_index (series int) : Sequential index identifying this tick CandleCTF   Structure representing a custom timeframe candle with additional time metadata   Fields:      Open (series float) : Opening price of the candle      High (series float) : Highest price of the candle      Low (series float) : Lowest price of the candle      Close (series float) : Closing price of the candle      polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)      series_index (series int) : Sequential index identifying the candle in the series      open_time (series int) : Timestamp marking when the candle was opened (in Unix time)      time_delta (series float) : Duration of the candle in milliseconds      candle_color (series color) : Color to use when rendering the candle
Pine Script® ライブラリ
The_Peaceful_Lizardの投稿
30
TrinityBar**TrinityBar Strategy Description** The TrinityBar strategy is a price‐action based trading model that leverages Bill Williams’ bar thirds concept to generate entry signals and execute market orders automatically. Here’s how it works: 1. **Bar Thirds Calculation:** The strategy calculates the range of both the current fully formed bar and the previous fully formed bar. It then divides each bar’s range into three equal parts (thirds). - For the current bar, the lower third and upper third levels are computed. - The same is done for the previous bar. 2. **Bar Type Classification:** Each bar is classified into one of several types based on where its open and close fall relative to its thirds: - **Bullish Patterns:** - *1‑3 Bar:* Opens in the lower third and closes in the upper third. - *2‑3 Bar:* Opens in the middle third and closes in the upper third. - *3‑3 Bar:* Both open and close are in the upper third. - **Bearish Patterns:** - *3‑1 Bar:* Opens in the upper third and closes in the lower third. - *2‑1 Bar:* Opens in the middle third and closes in the lower third. - *1‑1 Bar:* Both open and close are in the lower third. 3. **Signal Generation:** - **Bullish Signal:** A valid buy is generated when the previous bar exhibits any bullish pattern (1‑3, 2‑3, or 3‑3) and the current bar is either a 1‑3 or a 3‑3 bar. - **Bearish Signal:** A valid sell is generated when the previous bar shows any bearish pattern (1‑1, 2‑1, or 3‑1) and the current bar is either a 1‑1 or a 3‑1 bar. 4. **Visual Alerts:** When a valid signal is identified, the strategy plots a small triangle below the bar for a buy signal (labeled “B” in green) and a triangle above the bar for a sell signal (labeled “S” in red). 5. **Trade Execution:** Once a signal is confirmed: - If a bullish signal is generated, any short positions are closed, and if there is no existing long position, a market long order is entered. - Conversely, if a bearish signal occurs, any long positions are closed, and a market short order is entered if not already in a short position. This strategy is designed to capture significant price expansions by relying solely on price action and bar structure, without relying on lagging indicators. It provides a mechanical, systematic approach that removes emotional bias from trading decisions.
Pine Script® ストラテジー
Forex-Therapyの投稿