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NSR - Dynamic Linear Regression ChannelOverview The NSR - Dynamic Linear Regression Channel is a powerful overlay indicator that plots a dynamic regression-based channel around price action. Unlike static channels, this tool continuously recalculates the linear regression trendline from a user-defined starting point and builds upper and lower boundaries using a combination of standard deviation and maximum price deviations (highs/lows). It visually separates "Premium" (overvalued) and "Discount" (undervalued) zones relative to the regression trend — ideal for mean-reversion, breakout, or trend-following strategies. Key Features Dynamic Regression Line Calculates slope, intercept, and average using full lookback from a reset point. Adaptive Channel Width Combines standard deviation of residuals with max high/low deviations for robust boundaries. Auto-Reset on Breakout Channel resets when price closes beyond upper/lower band twice in direction of trend . Visual Zones Blue shaded = Premium (resistance zone) Red shaded = Discount (support zone) Real-Time Updates Live channel extends with each bar; historical channels preserved on reset. How It Works Regression Calculation Uses all bars since last reset to compute the best-fit line: y = intercept + slope × bar_position Deviation Bands Statistical : Standard deviation of price from regression line Structural : Maximum distance from highs to line (upper) and lows to line (lower) Final band = Regression Line ± (Deviation Input × StdDev) Channel Reset Logic Resets when: Price closes above upper band twice in an uptrend (slope > 0) OR closes below lower band twice in a downtrend (slope < 0) Prevents overextension and adapts to new trends. Visual Output Active channel updates in real-time Completed channels saved as historical reference (up to 500 lines/boxes) Input Parameters Deviation (2.0) - Multiplier for standard deviation to set channel width Premium Color - blue color for upper (resistance) zone Discount Color - red color for lower (support) zone Best Use Cases Mean Reversion - Buy near lower band in uptrend, sell near upper band Breakout Trading - Enter on confirmed close beyond band + volume Trend Confirmation - Use slope direction + price position in channel Stop Loss / Take Profit - Place stops beyond opposite band Pro Tips Use on higher timeframes (4H, Daily) for cleaner regression fits Combine with volume or momentum to filter false breakouts Lower Deviation (e.g., 1.5) for tighter, more responsive channels Watch channel resets — they often mark significant trend shifts Why Use DLRC? "Most channels are static. This one evolves with the market." The NSR-DLRC gives you a mathematically sound, visually intuitive way to see: Where price should be (regression) Where it has been (deviation extremes) When the trend is breaking structure Perfect for traders who want regression-based precision without rigid assumptions. Add to chart → Watch price dance within the evolving trend corridor.
אינדיקטור Pine Script®
מאת ‎nsrgroup‎
MIG and MC 发布简介（中文） MIG and MC 指标帮助日内交易者快速识别微型缺口（Micro Gap）与微型通道（Micro Channel）。脚本支持过滤开盘跳空、合并连续缺口，并自动绘制 FPL（Fair Price Line）延伸线，既可追踪缺口是否被填补，也能直观标注潜在的趋势结构。为了确保跨周期一致性，最新版本对开盘前后和跨日场景做了专门处理 主要特性 - 自动检测并显示看涨/看跌微型缺口，支持按需合并连续缺口。 - 自定义是否忽略开盘缺口、缺口显示范围与 FPL 样式。 - FPL 触及后即停止延伸，辅助研判缺口是否真正回补。 - 内置强收盘与缺口过滤的微型通道识别，可选多种严格程度。 - 适用于 1/5/9 分钟等日内周期，也适用于更长周期。 Recommended English Description The MIG and MC indicator highlights Micro Gaps and Micro Channels so you can track true intraday imbalances without noise. It merges consecutive gaps, projects Fair Price Lines (FPL) that stop once touched, and offers a full intraday-ready opening-gap filter so your early bars stay clean. The latest update refines cross-session handling, giving reliable gap plots on 1-, 5-, and 9-minute charts as well as higher time frames. Key Features - Detects bullish and bearish micro gaps with optional gap merging. - Toggle opening-gap filters and configure look back, visibility, and FPL style. - FPL lines stop as soon as price revisits the gap, making gap closure obvious. - Micro Channel mode uses strong-close and gap filters to mark high-quality trend legs. - Consistent behavior across intraday and higher time frames.
אינדיקטור Pine Script®
מאת ‎WendellZhang‎
Machine Learning Moving Average [BackQuant]Machine Learning Moving Average A powerful tool combining clustering, pseudo-machine learning, and adaptive prediction, enabling traders to understand and react to price behavior across multiple market regimes (Bullish, Neutral, Bearish). This script uses a dynamic clustering approach based on percentile thresholds and calculates an adaptive moving average, ideal for forecasting price movements with enhanced confidence levels. What is Percentile Clustering? Percentile clustering is a method that sorts and categorizes data into distinct groups based on its statistical distribution. In this script, the clustering process relies on the percentile values of a composite feature (based on technical indicators like RSI, CCI, ATR, etc.). By identifying key thresholds (lower and upper percentiles), the script assigns each data point (price movement) to a cluster (Bullish, Neutral, or Bearish), based on its proximity to these thresholds. This approach mimics aspects of machine learning, where we “train” the model on past price behavior to predict future movements. The key difference is that this is not true machine learning; rather, it uses data-driven statistical techniques to "cluster" the market into patterns. Why Percentile Clustering is Useful Clustering price data into meaningful patterns (Bullish, Neutral, Bearish) helps traders visualize how price behavior can be grouped over time. By leveraging past price behavior and technical indicators, percentile clustering adapts dynamically to evolving market conditions. It helps you understand whether price behavior today aligns with past bullish or bearish trends, improving market context. Clusters can be used to predict upcoming market conditions by identifying regimes with high confidence, improving entry/exit timing. What This Script Does Clustering Based on Percentiles : The script uses historical price data and various technical features to compute a "composite feature" for each bar. This feature is then sorted and clustered based on predefined percentile thresholds (e.g., 10th percentile for lower, 90th percentile for upper). Cluster-Based Prediction : Once clustered, the script uses a weighted average, cluster momentum, or regime transition model to predict future price behavior over a specified number of bars. Dynamic Moving Average : The script calculates a machine-learning-inspired moving average (MLMA) based on the current cluster, adjusting its behavior according to the cluster regime (Bullish, Neutral, Bearish). Adaptive Confidence Levels : Confidence in the predicted return is calculated based on the distance between the current value and the other clusters. The further it is from the next closest cluster, the higher the confidence. Visual Cluster Mapping : The script visually highlights different clusters on the chart with distinct colors for Bullish, Neutral, and Bearish regimes, and plots the MLMA line. Prediction Output : It projects the predicted price based on the selected method and shows both predicted price and confidence percentage for each prediction horizon. Trend Identification : Using the clustering output, the script colors the bars based on the current cluster to reflect whether the market is trending Bullish (green), Bearish (red), or is Neutral (gray). How Traders Use It Predicting Price Movements : The script provides traders with an idea of where prices might go based on past market behavior. Traders can use this forecast for short-term and long-term predictions, guiding their trades. Clustering for Regime Analysis : Traders can identify whether the market is in a Bullish, Neutral, or Bearish regime, using that information to adjust trading strategies. Adaptive Moving Average for Trend Following : The adaptive moving average can be used as a trend-following indicator, helping traders stay in the market when it’s aligned with the current trend (Bullish or Bearish). Entry/Exit Strategy : By understanding the current cluster and its associated trend, traders can time entries and exits with higher precision, taking advantage of favorable conditions when the confidence in the predicted price is high. Confidence for Risk Management : The confidence level associated with the predicted returns allows traders to manage risk better. Higher confidence levels indicate stronger market conditions, which can lead to higher position sizes. Pseudo Machine Learning Aspect While the script does not use conventional machine learning models (e.g., neural networks or decision trees), it mimics certain aspects of machine learning in its approach. By using clustering and the dynamic adjustment of a moving average, the model learns from historical data to adjust predictions for future price behavior. The "learning" comes from how the script uses past price data (and technical indicators) to create patterns (clusters) and predict future market movements based on those patterns. Why This Is Important for Traders Understanding market regimes helps to adjust trading strategies in a way that adapts to current market conditions. Forecasting price behavior provides an additional edge, enabling traders to time entries and exits based on predicted price movements. By leveraging the clustering technique, traders can separate noise from signal, improving the reliability of trading signals. The combination of clustering and predictive modeling in one tool reduces the complexity for traders, allowing them to focus on actionable insights rather than manual analysis. How to Interpret the Output Bullish (Green) Zone : When the price behavior clusters into the Bullish zone, expect upward price movement. The MLMA line will help confirm if the trend remains upward. Bearish (Red) Zone : When the price behavior clusters into the Bearish zone, expect downward price movement. The MLMA line will assist in tracking any downward trends. Neutral (Gray) Zone : A neutral market condition signals indecision or range-bound behavior. The MLMA line can help track any potential breakouts or trend reversals. Predicted Price : The projected price is shown on the chart, based on the cluster's predicted behavior. This provides a useful reference for where the price might move in the near future. Prediction Confidence : The confidence percentage helps you gauge the reliability of the predicted price. A higher percentage indicates stronger market confidence in the forecasted move. Tips for Use Combining with Other Indicators : Use the output of this indicator in combination with your existing strategy (e.g., RSI, MACD, or moving averages) to enhance signal accuracy. Position Sizing with Confidence : Increase position size when the prediction confidence is high, and decrease size when it’s low, based on the confidence interval. Regime-Based Strategy : Consider developing a multi-strategy approach where you use this tool for Bullish or Bearish regimes and a separate strategy for Neutral markets. Optimization : Adjust the lookback period and percentile settings to optimize the clustering algorithm based on your asset’s characteristics. Conclusion The Machine Learning Moving Average offers a novel approach to price prediction by leveraging percentile clustering and a dynamically adapting moving average. While not a traditional machine learning model, this tool mimics the adaptive behavior of machine learning by adjusting to evolving market conditions, helping traders predict price movements and identify trends with improved confidence and accuracy.
אינדיקטור Pine Script®
מאת ‎BackQuant‎
8
RSI Overbought/Oversold + Divergence Indicator (new)//@version=5 indicator('CryptoSignalScanner - RSI Overbought/Oversold + Divergence Indicator (new)', //--------------------------------------------------------------------------------------------------------------------------------- //--- Define Colors --------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------- vWhite = #FFFFFF vViolet = #C77DF3 vIndigo = #8A2BE2 vBlue = #009CDF vGreen = #5EBD3E vYellow = #FFB900 vRed = #E23838 longColor = color.green shortColor = color.red textColor = color.white bullishColor = color.rgb(38,166,154,0) //Used in the display table bearishColor = color.rgb(239,83,79,0) //Used in the display table nomatchColor = color.silver //Used in the display table //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Functions-------------------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- TF2txt(TF) => switch TF "S" => "RSI 1s:" "5S" => "RSI 5s:" "10S" => "RSI 10s:" "15S" => "RSI 15s:" "30S" => "RSI 30s" "1" => "RSI 1m:" "3" => "RSI 3m:" "5" => "RSI 5m:" "15" => "RSI 15m:" "30" => "RSI 30m" "45" => "RSI 45m" "60" => "RSI 1h:" "120" => "RSI 2h:" "180" => "RSI 3h:" "240" => "RSI 4h:" "480" => "RSI 8h:" "D" => "RSI 1D:" "1D" => "RSI 1D:" "2D" => "RSI 2D:" "3D" => "RSI 2D:" "3D" => "RSI 3W:" "W" => "RSI 1W:" "1W" => "RSI 1W:" "M" => "RSI 1M:" "1M" => "RSI 1M:" "3M" => "RSI 3M:" "6M" => "RSI 6M:" "12M" => "RSI 12M:" //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Show/Hide Settings ---------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- rsiShowInput = input(true, title='Show RSI', group='Show/Hide Settings') maShowInput = input(false, title='Show MA', group='Show/Hide Settings') showRSIMAInput = input(true, title='Show RSIMA Cloud', group='Show/Hide Settings') rsiBandShowInput = input(true, title='Show Oversold/Overbought Lines', group='Show/Hide Settings') rsiBandExtShowInput = input(true, title='Show Oversold/Overbought Extended Lines', group='Show/Hide Settings') rsiHighlightShowInput = input(true, title='Show Oversold/Overbought Highlight Lines', group='Show/Hide Settings') DivergenceShowInput = input(true, title='Show RSI Divergence Labels', group='Show/Hide Settings') //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Table Settings -------------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- rsiShowTable = input(true, title='Show RSI Table Information box', group="RSI Table Settings") rsiTablePosition = input.string(title='Location', defval='middle_right', options= , group="RSI Table Settings", inline='1') rsiTextSize = input.string(title=' Size', defval='small', options= , group="RSI Table Settings", inline='1') rsiShowTF1 = input(true, title='Show TimeFrame1', group="RSI Table Settings", inline='tf1') rsiTF1 = input.timeframe("15", title=" Time", group="RSI Table Settings", inline='tf1') rsiShowTF2 = input(true, title='Show TimeFrame2', group="RSI Table Settings", inline='tf2') rsiTF2 = input.timeframe("60", title=" Time", group="RSI Table Settings", inline='tf2') rsiShowTF3 = input(true, title='Show TimeFrame3', group="RSI Table Settings", inline='tf3') rsiTF3 = input.timeframe("240", title=" Time", group="RSI Table Settings", inline='tf3') rsiShowTF4 = input(true, title='Show TimeFrame4', group="RSI Table Settings", inline='tf4') rsiTF4 = input.timeframe("D", title=" Time", group="RSI Table Settings", inline='tf4') rsiShowHist = input(true, title='Show RSI Historical Columns', group="RSI Table Settings", tooltip='Show the information of the 2 previous closed candles') //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- RSI Input Settings ---------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- rsiSourceInput = input.source(close, 'Source', group='RSI Settings') rsiLengthInput = input.int(14, minval=1, title='RSI Length', group='RSI Settings', tooltip='Here we set the RSI lenght') rsiColorInput = input.color(#26a69a, title="RSI Color", group='RSI Settings') rsimaColorInput = input.color(#ef534f, title="RSIMA Color", group='RSI Settings') rsiBandColorInput = input.color(#787B86, title="RSI Band Color", group='RSI Settings') rsiUpperBandExtInput = input.int(title='RSI Overbought Extended Line', defval=80, minval=50, maxval=100, group='RSI Settings') rsiUpperBandInput = input.int(title='RSI Overbought Line', defval=70, minval=50, maxval=100, group='RSI Settings') rsiLowerBandInput = input.int(title='RSI Oversold Line', defval=30, minval=0, maxval=50, group='RSI Settings') rsiLowerBandExtInput = input.int(title='RSI Oversold Extended Line', defval=20, minval=0, maxval=50, group='RSI Settings') //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- MA Input Settings ----------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- maTypeInput = input.string("EMA", title="MA Type", options= , group="MA Settings") maLengthInput = input.int(14, title="MA Length", group="MA Settings") maColorInput = input.color(color.yellow, title="MA Color", group='MA Settings') //#7E57C2 //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Divergence Input Settings --------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- lbrInput = input(title="Pivot Lookback Right", defval=2, group='RSI Divergence Settings') lblInput = input(title="Pivot Lookback Left", defval=2, group='RSI Divergence Settings') lbRangeMaxInput = input(title="Max of Lookback Range", defval=10, group='RSI Divergence Settings') lbRangeMinInput = input(title="Min of Lookback Range", defval=2, group='RSI Divergence Settings') plotBullInput = input(title="Plot Bullish", defval=true, group='RSI Divergence Settings') plotHiddenBullInput = input(title="Plot Hidden Bullish", defval=true, group='RSI Divergence Settings') plotBearInput = input(title="Plot Bearish", defval=true, group='RSI Divergence Settings') plotHiddenBearInput = input(title="Plot Hidden Bearish", defval=true, group='RSI Divergence Settings') //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- RSI Calculation ------------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- rsi = ta.rsi(rsiSourceInput, rsiLengthInput) rsiprevious = rsi = request.security(syminfo.tickerid, rsiTF1, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on) = request.security(syminfo.tickerid, rsiTF2, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on) = request.security(syminfo.tickerid, rsiTF3, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on) = request.security(syminfo.tickerid, rsiTF4, [rsi, rsi , rsi ], lookahead=barmerge.lookahead_on) //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- MA Calculation ------------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- ma(source, length, type) => switch type "SMA" => ta.sma(source, length) "Bollinger Bands" => ta.sma(source, length) "EMA" => ta.ema(source, length) "SMMA (RMA)" => ta.rma(source, length) "WMA" => ta.wma(source, length) "VWMA" => ta.vwma(source, length) rsiMA = ma(rsi, maLengthInput, maTypeInput) rsiMAPrevious = rsiMA //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Stoch RSI Settings + Calculation -------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- showStochRSI = input(false, title="Show Stochastic RSI", group='Stochastic RSI Settings') smoothK = input.int(title="Stochastic K", defval=3, minval=1, maxval=10, group='Stochastic RSI Settings') smoothD = input.int(title="Stochastic D", defval=4, minval=1, maxval=10, group='Stochastic RSI Settings') lengthRSI = input.int(title="Stochastic RSI Lenght", defval=14, minval=1, group='Stochastic RSI Settings') lengthStoch = input.int(title="Stochastic Lenght", defval=14, minval=1, group='Stochastic RSI Settings') colorK = input.color(color.rgb(41,98,255,0), title="K Color", group='Stochastic RSI Settings', inline="1") colorD = input.color(color.rgb(205,109,0,0), title="D Color", group='Stochastic RSI Settings', inline="1") StochRSI = ta.rsi(rsiSourceInput, lengthRSI) k = ta.sma(ta.stoch(StochRSI, StochRSI, StochRSI, lengthStoch), smoothK) //Blue Line d = ta.sma(k, smoothD) //Red Line //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Divergence Settings ------------------------------------------------------------------------------------------------------------------------------------------ //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- bearColor = color.red bullColor = color.green hiddenBullColor = color.new(color.green, 50) hiddenBearColor = color.new(color.red, 50) //textColor = color.white noneColor = color.new(color.white, 100) osc = rsi plFound = na(ta.pivotlow(osc, lblInput, lbrInput)) ? false : true phFound = na(ta.pivothigh(osc, lblInput, lbrInput)) ? false : true _inRange(cond) => bars = ta.barssince(cond == true) lbRangeMinInput <= bars and bars <= lbRangeMaxInput //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Define Plot & Line Colors --------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- rsiColor = rsi >= rsiMA ? rsiColorInput : rsimaColorInput //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Plot Lines ------------------------------------------------------------------------------------------------------------------------------------------------------ //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- // Create a horizontal line at a specific price level myLine = line.new(bar_index , 75, bar_index, 75, color = color.rgb(187, 14, 14), width = 2) bottom = line.new(bar_index , 50, bar_index, 50, color = color.rgb(223, 226, 28), width = 2) mymainLine = line.new(bar_index , 60, bar_index, 60, color = color.rgb(13, 154, 10), width = 3) hline(50, title='RSI Baseline', color=color.new(rsiBandColorInput, 50), linestyle=hline.style_solid, editable=false) hline(rsiBandExtShowInput ? rsiUpperBandExtInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false) hline(rsiBandShowInput ? rsiUpperBandInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false) hline(rsiBandShowInput ? rsiLowerBandInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false) hline(rsiBandExtShowInput ? rsiLowerBandExtInput : na, title='RSI Upper Band', color=color.new(rsiBandColorInput, 10), linestyle=hline.style_dashed, editable=false) bgcolor(rsiHighlightShowInput ? rsi >= rsiUpperBandExtInput ? color.new(rsiColorInput, 70) : na : na, title="Show Extended Oversold Highlight", editable=false) bgcolor(rsiHighlightShowInput ? rsi >= rsiUpperBandInput ? rsi < rsiUpperBandExtInput ? color.new(#64ffda, 90) : na : na: na, title="Show Overbought Highlight", editable=false) bgcolor(rsiHighlightShowInput ? rsi <= rsiLowerBandInput ? rsi > rsiLowerBandExtInput ? color.new(#F43E32, 90) : na : na : na, title="Show Extended Oversold Highlight", editable=false) bgcolor(rsiHighlightShowInput ? rsi <= rsiLowerBandInput ? color.new(rsimaColorInput, 70) : na : na, title="Show Oversold Highlight", editable=false) maPlot = plot(maShowInput ? rsiMA : na, title='MA', color=color.new(maColorInput,0), linewidth=1) rsiMAPlot = plot(showRSIMAInput ? rsiMA : na, title="RSI EMA", color=color.new(rsimaColorInput,0), editable=false, display=display.none) rsiPlot = plot(rsiShowInput ? rsi : na, title='RSI', color=color.new(rsiColor,0), linewidth=1) fill(rsiPlot, rsiMAPlot, color=color.new(rsiColor, 60), title="RSIMA Cloud") plot(showStochRSI ? k : na, title='Stochastic K', color=colorK, linewidth=1) plot(showStochRSI ? d : na, title='Stochastic D', color=colorD, linewidth=1) //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Plot Divergence ------------------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- // Regular Bullish // Osc: Higher Low oscHL = osc > ta.valuewhen(plFound, osc , 1) and _inRange(plFound ) // Price: Lower Low priceLL = low < ta.valuewhen(plFound, low , 1) bullCond = plotBullInput and priceLL and oscHL and plFound plot( plFound ? osc : na, offset=-lbrInput, title="Regular Bullish", linewidth=2, color=(bullCond ? bullColor : noneColor) ) plotshape( DivergenceShowInput ? bullCond ? osc : na : na, offset=-lbrInput, title="Regular Bullish Label", text=" Bull ", style=shape.labelup, location=location.absolute, color=bullColor, textcolor=textColor ) //------------------------------------------------------------------------------ // Hidden Bullish // Osc: Lower Low oscLL = osc < ta.valuewhen(plFound, osc , 1) and _inRange(plFound ) // Price: Higher Low priceHL = low > ta.valuewhen(plFound, low , 1) hiddenBullCond = plotHiddenBullInput and priceHL and oscLL and plFound plot( plFound ? osc : na, offset=-lbrInput, title="Hidden Bullish", linewidth=2, color=(hiddenBullCond ? hiddenBullColor : noneColor) ) plotshape( DivergenceShowInput ? hiddenBullCond ? osc : na : na, offset=-lbrInput, title="Hidden Bullish Label", text=" H Bull ", style=shape.labelup, location=location.absolute, color=bullColor, textcolor=textColor ) //------------------------------------------------------------------------------ // Regular Bearish // Osc: Lower High oscLH = osc < ta.valuewhen(phFound, osc , 1) and _inRange(phFound ) // Price: Higher High priceHH = high > ta.valuewhen(phFound, high , 1) bearCond = plotBearInput and priceHH and oscLH and phFound plot( phFound ? osc : na, offset=-lbrInput, title="Regular Bearish", linewidth=2, color=(bearCond ? bearColor : noneColor) ) plotshape( DivergenceShowInput ? bearCond ? osc : na : na, offset=-lbrInput, title="Regular Bearish Label", text=" Bear ", style=shape.labeldown, location=location.absolute, color=bearColor, textcolor=textColor ) //------------------------------------------------------------------------------ // Hidden Bearish // Osc: Higher High oscHH = osc > ta.valuewhen(phFound, osc , 1) and _inRange(phFound ) // Price: Lower High priceLH = high < ta.valuewhen(phFound, high , 1) hiddenBearCond = plotHiddenBearInput and priceLH and oscHH and phFound plot( phFound ? osc : na, offset=-lbrInput, title="Hidden Bearish", linewidth=2, color=(hiddenBearCond ? hiddenBearColor : noneColor) ) plotshape( DivergenceShowInput ? hiddenBearCond ? osc : na : na, offset=-lbrInput, title="Hidden Bearish Label", text=" H Bear ", style=shape.labeldown, location=location.absolute, color=bearColor, textcolor=textColor ) //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Check RSI Lineup ------------------------------------------------------------------------------------------------------------------------------------------------ //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- bullTF = rsi > rsi and rsi > rsi bearTF = rsi < rsi and rsi < rsi bullTF1 = rsi1 > rsi1_1 and rsi1_1 > rsi1_2 bearTF1 = rsi1 < rsi1_1 and rsi1_1 < rsi1_2 bullTF2 = rsi2 > rsi2_1 and rsi2_1 > rsi2_2 bearTF2 = rsi2 < rsi2_1 and rsi2_1 < rsi2_2 bullTF3 = rsi3 > rsi3_1 and rsi3_1 > rsi3_2 bearTF3 = rsi3 < rsi3_1 and rsi3_1 < rsi3_2 bullTF4 = rsi4 > rsi4_1 and rsi4_1 > rsi4_2 bearTF4 = rsi4 < rsi4_1 and rsi4_1 < rsi4_2 bbTxt(bull,bear) => bull ? "BULLISH" : bear ? "BEARISCH" : 'NO LINEUP' bbColor(bull,bear) => bull ? bullishColor : bear ? bearishColor : nomatchColor newTC(tBox, col, row, txt, width, txtColor, bgColor, txtHA, txtSize) => table.cell(table_id=tBox,column=col, row=row, text=txt, width=width,text_color=txtColor,bgcolor=bgColor, text_halign=txtHA, text_size=txtSize) //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- //--- Define RSI Table Setting ---------------------------------------------------------------------------------------------------------------------------------------- //--------------------------------------------------------------------------------------------------------------------------------------------------------------------- width_c0 = 0 width_c1 = 0 if rsiShowTable var tBox = table.new(position=rsiTablePosition, columns=5, rows=6, bgcolor=color.rgb(18,22,33,50), frame_color=color.black, frame_width=1, border_color=color.black, border_width=1) newTC(tBox, 0,1,"RSI Current",width_c0,color.orange,color.rgb(0,0,0,100),'right',rsiTextSize) newTC(tBox, 1,1,str.format(" {0,number,#.##} ", rsi),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 4,1,bbTxt(bullTF, bearTF),width_c0,vWhite,bbColor(bullTF, bearTF),'center',rsiTextSize) if rsiShowHist newTC(tBox, 2,1,str.format(" {0,number,#.##} ", rsi ),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 3,1,str.format(" {0,number,#.##} ", rsi ),width_c0,vWhite,rsi < 50 ? bearishColor:bullishColor,'left',rsiTextSize) if rsiShowTF1 newTC(tBox, 0,2,TF2txt(rsiTF1),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize) newTC(tBox, 1,2,str.format(" {0,number,#.##} ", rsi1),width_c0,vWhite,rsi1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 4,2,bbTxt(bullTF1, bearTF1),width_c0,vWhite,bbColor(bullTF1,bearTF1),'center',rsiTextSize) if rsiShowHist newTC(tBox, 2,2,str.format(" {0,number,#.##} ", rsi1_1),width_c0,vWhite,rsi1_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 3,2,str.format(" {0,number,#.##} ", rsi1_2),width_c0,vWhite,rsi1_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) if rsiShowTF2 newTC(tBox, 0,3,TF2txt(rsiTF2),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize) newTC(tBox, 1,3,str.format(" {0,number,#.##} ", rsi2),width_c0,vWhite,rsi2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 4,3,bbTxt(bullTF2, bearTF2),width_c0,vWhite,bbColor(bullTF2,bearTF2),'center',rsiTextSize) if rsiShowHist newTC(tBox, 2,3,str.format(" {0,number,#.##} ", rsi2_1),width_c0,vWhite,rsi2_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 3,3,str.format(" {0,number,#.##} ", rsi2_2),width_c0,vWhite,rsi2_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) if rsiShowTF3 newTC(tBox, 0,4,TF2txt(rsiTF3),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize) newTC(tBox, 1,4,str.format(" {0,number,#.##} ", rsi3),width_c0,vWhite,rsi3 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 4,4,bbTxt(bullTF3, bearTF3),width_c0,vWhite,bbColor(bullTF3,bearTF3),'center',rsiTextSize) if rsiShowHist newTC(tBox, 2,4,str.format(" {0,number,#.##} ", rsi3_1),width_c0,vWhite,rsi3_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 3,4,str.format(" {0,number,#.##} ", rsi3_2),width_c0,vWhite,rsi3_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) if rsiShowTF4 newTC(tBox, 0,5,TF2txt(rsiTF4),width_c0,vWhite,color.rgb(0,0,0,100),'right',rsiTextSize) newTC(tBox, 1,5,str.format(" {0,number,#.##} ", rsi4),width_c0,vWhite,rsi4 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 4,5,bbTxt(bullTF4, bearTF4),width_c0,vWhite,bbColor(bullTF4,bearTF4),'center',rsiTextSize) if rsiShowHist newTC(tBox, 2,5,str.format(" {0,number,#.##} ", rsi4_1),width_c0,vWhite,rsi4_1 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) newTC(tBox, 3,5,str.format(" {0,number,#.##} ", rsi4_2),width_c0,vWhite,rsi4_2 < 50 ? bearishColor:bullishColor,'left',rsiTextSize) //------------------------------------------------------ //--- Alerts ------------------------------------------- //------------------------------------------------------
אינדיקטור Pine Script®
מאת ‎RandyDahlin‎
Intraday Perpetual Premium & Z-ScoreThis indicator measures the real-time premium of a perpetual futures contract relative to its spot market and interprets it through a statistical lens. It helps traders detect when funding pressure is building, when leverage is being unwound, and when crowding in the futures market may precede volatility. How it works • Premium (%) = (Perp – Spot) ÷ Spot × 100 The script fetches both spot and perpetual prices and calculates their percentage difference each minute. • Rolling Mean & Z-Score Over a 4-hour look-back, it computes the average premium and standard deviation to derive a Z-Score, showing how stretched current sentiment is. • Dynamic ±2σ Bands highlight statistically extreme premiums or discounts. • Rate of Change (ROC) over one hour gauges the short-term directional acceleration of funding flows. Colour & Label Interpretation Visual cue Meaning Trading Implication 🟢 Green bars + “BULL Pressure” Premium rising faster than mean Leverage inflows → momentum strengthening 🔴 Red bars + “BEAR Pressure” Premium shrinking Leverage unwind → pull-back or consolidation ⚠️ Orange “EXTREME Premium/Discount” Crowded trade → heightened reversal risk ⚪ Grey bars Neutral Balanced conditions Alerts • Bull Pressure Alert → funding & premium rising (momentum building) • Bear Pressure Alert → premium falling (deleveraging) • Extreme Premium Alert → crowded longs; potential top • Extreme Discount Alert → capitulation; possible bottom Use case Combine this indicator with your Heikin-Ashi, RSI, and MACD confluence rules: • Enter only when your oscillators are low → curling up and Bull Pressure triggers. • Trim or exit when Bear Pressure or Extreme Premium appears. • Watch for Extreme Discount during flushes as an early bottoming clue.
אינדיקטור Pine Script®
מאת ‎TokenTrendTracker‎
Simulated Fear & Greed (CNN-calibrated v2)🧭 Fear & Greed Index — TradingView Version (Simulated CNN Model) 🔍 Purpose The Fear & Greed Index is a sentiment indicator that quantifies market emotion on a scale from 0 to 100, where: 0 represents Extreme Fear (capitulation, oversold conditions), and 100 represents Extreme Greed (euphoria, overbought conditions). It helps traders assess whether the market is driven by fear (risk aversion) or greed (risk appetite) — giving a high-level view of potential turning points in market sentiment. ⚙️ How It Works in TradingView Because TradingView cannot directly access CNN’s or alternative external sentiment feeds, this indicator simulates the Fear & Greed Index by analyzing in-chart technical data that reflect investor psychology. It uses a multi-factor model, converting price and volume signals into a composite sentiment score. 🧩 Components Used (Simulated Metrics) Category Metric Emotional Interpretation Volatility ATR (Average True Range) High ATR = Fear, Low ATR = Greed Momentum RSI + MACD Histogram Rising momentum = Greed, Falling = Fear Volume Activity Volume Z-Score High positive deviation = Greed, Low = Fear Trend Context SMA Regime Bias (50/200) Downtrend adds Fear penalty, Uptrend supports Greed These elements are normalized into a 0–100 scale using percentile ranks (like statistical scoring) and then combined using user-adjustable weights. ⚖️ CNN-Style Calibration The script follows CNN’s five sentiment bands for clarity: Range Zone Colour Description 0–25 Extreme Fear 🔴 Red Panic, forced selling, capitulation risk 25–45 Fear 🟠 Orange Uncertainty, hesitation, early accumulation phase 45–55 Neutral ⚪ Gray Balanced sentiment, indecision 55–75 Greed 🟢 Light Green Optimism, trend continuation 75–100 Extreme Greed 💚 Bright Green Euphoria, risk of reversal This structure aligns visually with CNN’s public gauge, making it easy to interpret.
אינדיקטור Pine Script®
מאת ‎thriftyLion65492‎
Vandan V2Vandan V2 is an automated trading strategy for NQ1! (E-mini Nasdaq-100) based on short-term mean reversion with dynamic risk control. It combines volatility filters and overbought/oversold signals to capture local market imbalances. Backtested from 2015 to 2025, it achieved a +730% total return, Profit Factor of 1.40, max drawdown of only 1.61%, and over 106,000 trades. Designed for systematic scalping or intraday arbitrage with a limit of 3 simultaneous contracts.
אסטרטגיית Pine Script®
מאת ‎gerasymenko_nazarr‎
4
Accurate ATR Stop Loss Distance — Risk Management ToolAccurate ATR Stop Loss Distance — Risk Management Tool This indicator calculates an accurate Stop Loss distance in pips using the Average True Range (ATR) multiplied by a user-defined multiplier. It automatically detects the correct pip size based on the instrument type (Forex, Crypto, Stocks, Indices, Futures), adjusting for 2-, 3-, 4-, or 5-digit quotes — ensuring professional-grade precision that matches institutional ATR-based risk systems. 📊 Features: Uses ATR × Multiplier to determine precise SL distance in pips. Automatically adjusts pip value depending on the asset type (handles 5-digit Forex brokers). Clean and minimal design — displays only one info box in the top-right corner. Fully customizable text and background colors. Includes alert condition for automated SL updates. ⚙️ How to use: Set your preferred ATR period and multiplier. The indicator instantly displays your Stop Loss distance in pips at the top-right of the chart. Combine with your entry strategy to calculate lot size or risk per trade. 💡 Ideal for traders who want consistent, objective SL distances derived from volatility rather than arbitrary points or emotions. Note: Educational and informational tool only. Does not execute trades or give financial advice.
אינדיקטור Pine Script®
מאת ‎AleNewTrade‎
Liquidity & Momentum Master (LMM)💎 Liquidity & Momentum Master (LMM) A professional dual-system indicator that combines: 📦 High-Volume Support/Resistance Zones and 📊 RSI + Bollinger Band Combo Signals — to visualize both smart money footprints and momentum reversals in one clean tool. 🧱 1. High-Volume Liquidity Zones (Support/Resistance Boxes) Conditions Visible only on 1H and higher timeframes (1H, 4H, 1D, etc.) Detects candles with abnormally high volume and strong ATR-based range Separates bullish (support) and bearish (resistance) zones Visualization All boxes are white, with adjustable transparency (alphaW, alphaBorder) Each box extends to the right automatically Only the most important (Top-N) zones are kept — weaker ones are removed automatically Interpretation White boxes = price areas with heavy liquidity and volume concentration Price approaching these zones often leads to bounces or rejections Narrow spacing = consolidation, wide spacing = potential large move 💎 2. RSI Exit + BB-RSI Combo Signals RSI Exit (Overbought/Oversold Recovery) RSI drops from overbought (>70) → plots red “RSI” above the candle RSI rises from oversold (<30) → plots green “RSI” below the candle Works on 15m, 30m, 1H, 4H, 1D → Indicates short-term exhaustion recovery BB-RSI Combo (Momentum Reversal Confirmation) Active on 1H and higher only Requires both: ✅ RSI divergence (bullish or bearish) ✅ Bollinger Band re-entry (after temporary breakout) Combo Buy (Green Diamond) Bullish RSI divergence Candle closes back above lower Bollinger Band Combo Sell (Red Diamond) Bearish RSI divergence Candle closes back below upper Bollinger Band → Confirms stronger reversal momentum compared to standard RSI signals
אינדיקטור Pine Script®
מאת ‎HSeungpyo‎
Dynamic Liquidity HeatMap Profile [BigBeluga]🔵 OVERVIEW The Dynamic Liquidity HeatMap Profile is a smart-flow liquidity tracker that maps where stop-loss clusters and resting limit orders are likely positioned. Instead of traditional volume profiles based only on executed transactions, this tool projects probable liquidity pools — areas where traders are trapped or positioned and where smart money may hunt stops or fill orders. It dynamically scans recent price swings, builds liquidity zones above and below price, and visualizes them as a heat map + histogram — highlighting areas with the greatest liquidity attraction. Orange highlights the highest-concentration liquidity (POC), making potential sweep targets obvious. 🔵 CONCEPTS Liquidity pools form above swing highs (buy stops) and below swing lows (sell stops). Market makers & large players often push price into these zones to trigger stops and capture liquidity. The indicator uses recent volatility + volume expansion to estimate where these pools exist. Horizontal heat bars show depth and intensity of probable liquidity. Profile side histogram displays buy-side vs sell-side liquidity distribution. 🔵 FEATURES Dynamic Liquidity Detection — finds potential stop-loss clusters from recent swing behavior. Dual-Side Heatmap — split liquidity view above (short stops) and below (long stops) current price. Volume-Weighted Levels — higher volatility & volume = deeper liquidity expectation. Real-Time Heat Coloring • Lime = liquidity below price (potential buy-side fuel) • Blue = liquidity above price (potential sell-side fuel) • Orange = peak liquidity (POC) Liquidity Profile Histogram — plotted at right side, layered by strength. Auto-Cleaning Engine — removes invalidated liquidity after breaks. Adjustable lookback window and bin resolution . 🔵 HOW TO USE Look for price moving toward dense liquidity zones — high probability of wick raids or sweeps. Orange POC often acts as magnet — strong target zone for smart money. Combine with SFP / BOS logic to time reversals after liquidity hunts. In trend, price repeatedly sweeps opposite-side liquidity before continuation. Use liquidity walls as bias filters — heavy liquidity above often precedes downward move, and vice-versa. Great for scalping sessions, indices, FX, BTC, ETH. 🔵 CONCLUSION The Dynamic Liquidity HeatMap Profile gives traders a tactical edge by revealing where the market’s hidden liquidity resides. It highlights where shorts and longs are positioned, identifies likely sweep zones, and marks the most attractive liquidity magnet (POC). Use it to anticipate stop hunts, avoid getting trapped, and align with smart-money flow instead of fighting it.
אינדיקטור Pine Script®
מאת ‎BigBeluga‎
28
Volumatic VIDYA – Pro+1. Professional & Clear (recommended for TradingView) Volumatic VIDYA Pro+ combines a dynamic VIDYA trend filter, Delta Volume pressure, and automatic pattern recognition (Double/Triple Tops & Bottoms, Head & Shoulders). A complete technical tool for detecting momentum shifts, trend reversals, and trade entries across multiple timeframes. 2. Short & Catchy Adaptive VIDYA trendline + Delta Volume + Pattern detection in one tool. Instantly visualize market bias, structure, and momentum strength. 3. Educational / Analytical Analyze market dynamics with VIDYA-based trend filtering, volume delta analysis, and automated pattern recognition. Ideal for traders who combine price action with quantitative confirmation.
אינדיקטור Pine Script®
מאת ‎jr36187‎
2
Volume Momentum Div - [TCMaster]📘 Description Volume + Momentum (Instant Alert) is a dynamic indicator designed to detect potential market tops and bottoms in real time by combining momentum shifts with volume spikes. Unlike traditional oscillators that confirm signals only after candle close, this tool reacts instantly, providing early alerts during live market movements. ⚙️ How It Works Momentum Calculation: Measures the short-term price acceleration using the difference between the current price and the price n periods ago. Rising momentum indicates bullish strength, while falling momentum shows bearish pressure. Volume Spike Detection: Compares current volume to its moving average. When the current volume exceeds the average by a defined multiplier, it signals strong market participation — often appearing near market reversals. Signal Logic: Top Alert (🔻): Momentum turns negative while a volume spike occurs → potential short opportunity. Bottom Alert (🔺): Momentum turns positive while a volume spike occurs → potential long opportunity. 🎯 Features Real-time alerts (calc_on_every_tick=true) — signals trigger instantly during live candles. Multiple plot styles available: Line, Histogram, or Columns. Simple yet powerful logic suitable for scalping, intraday, and swing trading. Works across all markets (forex, crypto, stocks, commodities). 💡 How to Use Look for Volume Spikes — sudden increases in volume often mark exhaustion or breakout points. Check Momentum Direction — combine with volume to confirm reversals. Entry/Exit: Buy when a green triangle (🔺) appears below the bar. Sell when a red triangle (🔻) appears above the bar. Optional Filters: For improved accuracy, combine with RSI, Stochastic, or trend filters (e.g., EMA200).
אינדיקטור Pine Script®
מאת ‎TCMaster‎
1
Inyerneck UT Bot with 9 EMA Filter With Signals (Tight) v: 4.20this script is a customized version of the UT bot, enhanced with 9ema trend filter for cleaner entries.designed for short term traders to reduce noise and avoid false signals during choppy price action. youll only see signals when price action confirms momentum aligned with trend as defined by EMA. try adjusting sensitivity and ATR period to your liking. my current setting is ATR 6,Sensitivity 3.8,EMA 9 to 11...
אינדיקטור Pine Script®
מאת ‎oogabooger‎
VIX/VVIX Spike RiskVIX/VVIX Spike Risk Analyzer The VIX/VVIX Spike Risk Analyzer analyzes historical VIX behavior under similar market conditions to forecast future VIX spike risk. By combining current VIX and VVIX levels as dual filters, it identifies historical precedents and calculates the probability and magnitude of VIX spikes over the next 1, 5, and 10 trading days. IMPORTANT: This indicator must be applied to the VIX chart (CBOE:VIX) to function correctly. Methodology 1. Dual-Filter Pattern Matching The indicator uses both VIX and VVIX as simultaneous filters to identify historically analogous market conditions: By requiring BOTH metrics to match historical levels, the indicator creates more precise market condition filters than using VIX alone. This dual-filter approach significantly improves predictive accuracy because: VIX alone might be at 15, but VVIX can tell us if that 15 is stable (low VVIX) or explosive (high VVIX) High VVIX + Low VIX often precedes major spikes Low VVIX + Low VIX suggests sustained calm 2. Tolerance Settings VIX Matching (Default: ±10% Relative) Uses relative percentage matching for consistency across different VIX regimes Example: VIX at 15 matches 13.5-16.5 (±10%) Can switch to absolute tolerance (±5 points) if preferred VVIX Matching (Default: ±10 Points Absolute) Uses absolute point matching as VVIX scales differently Example: VVIX at 100 matches 90-110 Can switch to relative percentage if preferred 3. Historical Analysis Window The indicator scans up to 500 bars backward (limited by VVIX data availability) to find all historical periods where both VIX and VVIX were at similar levels. Each match becomes a "sample" for statistical analysis. 4. Forward-Looking Spike Analysis For each historical match, the indicator measures VIX behavior over the next 1, 5, and 10 days Display Metrics Explained Average Highest Spike Shows the average of the maximum VIX spikes observed. Highest Single Spike Shows the single largest spike ever recorded Probability No 10% Spike Shows what percentage of historical cases stayed BELOW a 10% spike: Probability No 20% Spike Shows what percentage of historical cases stayed BELOW a 20% spike: Note : You'll see many more shaded bars than the sample count because each match creates up to 5 consecutive shaded bars (bars 1-5 after the match all "look back" and see it). Short Volatility Strategies: Enter when there's a LOW probability of big vol spikes based on today's metrics Long Volatility Strategies Enter when there's a HIGH probability of big vol spikes based on today's metrics
אינדיקטור Pine Script®
מאת ‎CIVolatility‎
Tristan's Tri-band StrategyTristan's Tri-band Strategy - Confluence Trading System Strategy Overview: This strategy combines three powerful technical indicators - RSI, Williams %R, and Bollinger Bands - into a single visual trading system. Instead of cluttering your chart with separate indicator panels, all signals are displayed directly on the price chart using color-coded gradient overlays, making it easy to spot high-probability trade setups at a glance. How It Works: The strategy identifies trading opportunities when multiple indicators align (confluence), suggesting strong momentum shifts: 📈 Long Entry Signals: RSI drops to 30 or below (oversold) Williams %R reaches -80 to -100 range (oversold) Price touches or breaks below the lower Bollinger Band All three conditions must align during your selected trading session 📉 Short Entry Signals: RSI rises to 70 or above (overbought) Williams %R reaches 0 to -20 range (overbought) Price touches or breaks above the upper Bollinger Band All three conditions must align during your selected trading session Visual Indicators: (faint) Green gradients below candles = Bullish oversold conditions (buying opportunity) (faint) Red/Orange gradients above candles = Bearish overbought conditions (selling opportunity) Stacked/brighter gradients = Multiple indicators confirming the same signal (higher probability) will stack and show brighter / less faint Blue Bollinger Bands = Volatility boundaries and mean reversion zones Exit Strategy: Long trades exit when price reaches the upper Bollinger Band OR RSI becomes overbought (≥70) Short trades exit when price reaches the lower Bollinger Band OR RSI becomes oversold (≤30) Key Features: ✅ Session Filters - Trade only during NY (9:30 AM-4 PM), London (3 AM-11:30 AM), or Asia (7 PM-1 AM EST) sessions ✅ No Repainting - Signals are confirmed on candle close for realistic backtesting and live trading ✅ Customizable Parameters - Adjust RSI levels, BB standard deviations, Williams %R periods, and gradient visibility ✅ Visual Clarity - See all three indicators at once without switching between panels ✅ Built-in Alerts - Get notified when entry and exit conditions are met How to Use Effectively: Choose Your Trading Session - For day trading US stocks, enable only the NY session. For forex or 24-hour markets, select the sessions that match your schedule. Look for Gradient Stacking - The brightest, most visible gradients occur when both RSI and Williams %R signal together. These are your highest-probability setups. Confirm with Price Action - Wait for the candle to close before entering. The strategy enters on the next bar's open to prevent repainting. Respect the Bollinger Bands - Entries occur at the outer bands (price extremes), and exits occur at the opposite band or when momentum reverses. Backtest First - Test the strategy on your preferred instruments and timeframes. Works best on liquid assets with clear trends and mean reversion patterns (stocks, major forex pairs, indices). Adjust Gradient Visibility - Use the "Gradient Strength" slider (lower = more visible) to make signals stand out on your chart style. Best Timeframes: 5-minute to 1-hour charts for intraday trading; 4-hour to daily for swing trading (I have also found the 3 hour timeframe to work really well for some stocks / ETFs.) Best Markets: Liquid instruments with volatility - SPY, QQQ, major stocks, EUR/USD, GBP/USD, major indices Risk Management: This is a mean reversion strategy that works best in ranging or choppy markets. In strong trends, signals may appear less frequently. Always use proper position sizing and stop losses based on your risk tolerance. ---------------------------------------------- Note: Past performance does not guarantee future results. This strategy is provided for educational purposes. Always backtest thoroughly and practice proper risk management before live trading.RetryClaude can make mistakes. Please double-check responses. Sonnet 4.5
אסטרטגיית Pine Script®
מאת ‎OhRayOhRay‎
India Vix based Strangle StrikesA clean Nifty–VIX dashboard that converts India VIX into expected daily moves, price ranges, and suggested strangle strikes. Includes VIX %, expanded 1.2× range, and smart rounded strike levels for options trading. This script provides a professional on-chart dashboard that converts India VIX into actionable trading levels for Nifty. It calculates the VIX-based expected daily move, projected price ranges, expanded 1.2× ranges, and suggested strangle strike prices. Includes clean formatting, color-coded sections, and real-time updates. Ideal for traders using straddles, strangles, intraday volatility models, range-bound setups, and options-based risk management. 1.2x expanded range is better success probability, may keep 20% of strangle value as stop loss. The vix based system is intended to give approx. 70%+ success rate.
אינדיקטור Pine Script®
מאת ‎ipuneet‎
VIX Regime AnalyzerVIX Regime Analyzer The VIX Regime Analyzer is an analytical tool that examines historical VIX patterns to provide insights into how your asset typically performs under similar volatility conditions. Key Features: Historical Pattern Matching: Automatically scans up to 1,000 bars of history to find all periods when VIX was at levels similar to today, using customizable tolerance ranges (absolute or percentage-based). Forward-Looking Statistics: For each VIX regime match, calculates what actually happened to your asset over the next 1, 5, 10, and 20 trading days, providing both average returns and probability of positive outcomes. Regime Classification System: Intelligently categorizes the current market environment as bullish or bearish: Visual Historical Context: Background shading throughout your chart highlights every historical period when VIX matched current levels, color-coded by subsequent performance (green for gains, red for losses). User Inputs: VIX Level Tolerance (+/-): How closely VIX must match (default: ±5 points) Use Relative Tolerance (%): Switch to percentage-based matching for consistency across different VIX levels Lookback Period: How many bars to analyze Highlight Historical VIX Matches: Toggle background highlighting of past matching periods The Data Table The statistics box appears in the right handside of your chart and contains three main sections: Section 1: VIX REGIME Current VIX: The live VIX closing price Range: The tolerance band being searched (e.g., if VIX is 18 with ±5 tolerance, range is 13-23) Historical Samples: Number of matching periods found in the lookback window (minimum 10 required for statistical validity) Section 2: FORWARD RETURN Shows the average percentage change in your asset over different timeframes following similar VIX levels: Avg Next Day: What typically happened by the next trading session Avg Next 5 Days: Average 5-day forward performance Avg Next 10 Days: Average 10-day forward performance Avg Next 20 Days: Average 20-day forward performance (approximately 1 month) Section 3: PROBABILITY UP Shows the win rate - the percentage of times your asset closed higher after VIX matched current levels: Next Day: Probability of being up the next session Next 5 Days: Probability of being up after 5 days Next 10 Days: Probability of being up after 10 days Next 20 Days: Probability of being up after 20 days Colors: 🟢 Green: Bullish regimes (various strengths) 🔴 Red: Bearish regimes (various strengths) 🟡 Yellow: Choppy/uncertain regime When "Highlight Historical VIX Matches" is enabled: Scroll back through your chart and you'll see colored backgrounds highlighting every period when VIX matched today's level. The color tells you whether that match led to gains (green) or losses (red). This provides instant visual pattern recognition - you can quickly see if similar VIX levels historically led to bullish or bearish outcomes. Practical Example: If you see that most historical periods with similar VIX levels are highlighted in green, it suggests the current VIX level has historically been a bullish signal for your asset. How The Indicator Makes Decisions The regime classification uses both magnitude AND probability to avoid false signals: Example of Strong Classification: Average 5-day return: +1.5% Win rate: 65% Result: STRONG BULLISH (both high return and high probability) Example of Weak Signal: Average 5-day return: +2.0% Win rate: 35% Result: CHOPPY (high average but low consistency = unreliable) This dual-factor approach ensures the indicator doesn't mislead you with regimes that had a few huge winners but mostly losers, or vice versa. Best Practices Combine with your existing strategy: Use this as a regime filter rather than standalone signals Check sample size: More historical matches = more reliable statistics Consider multiple timeframes: If 5-day and 20-day metrics disagree, proceed with caution Asset-specific tuning: Different assets may require different tolerance settings VIX spikes: The indicator is particularly useful during VIX spikes to understand if panic is justified What Makes This Different Unlike simple VIX indicators that just plot the fear index, this tool: Quantifies the actual impact of VIX levels on YOUR specific asset Provides probability-based forecasts rather than subjective interpretation Shows historical context visually so you can see patterns at a glance Uses rigorous statistical criteria to avoid false regime classifications
אינדיקטור Pine Script®
מאת ‎CIVolatility‎