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RSI Prediction by Range Segmentation [LuxAlgo]The RSI Prediction by Range Segmentation indicator projects a future path for the Relative Strength Index (RSI) by analyzing and averaging historical patterns that originated from similar RSI levels. This tool provides a probabilistic forecast based on how the RSI has historically behaved after reaching specific value segments. 🔶 USAGE The indicator segments the RSI range (0-100) into multiple horizontal zones. When the current RSI value falls into a specific zone, the script identifies all historical instances where the RSI was in that same zone and calculates the average path it took over a subsequent period. Users can observe the dynamic polyline forecast extending from the current RSI value to anticipate potential overbought or oversold conditions before they occur. The RSI line itself changes color based on its position relative to the 50 level, providing an immediate visual cue for bullish or bearish momentum. 🔹 Range Segmentation The RSI scale is divided into "Range Segments" (e.g., 10 segments of 10 points each). This allows the indicator to categorize market momentum into specific states. By increasing the number of segments, you make the historical matching more precise but may have fewer historical samples to average. A step-line is plotted to visualize the base of the current segment being analyzed. 🔹 The Forecast The forecast is generated only on the most recent bar using a polyline. It looks at the current RSI segment, retrieves the "Historical Limit" of stored patterns for that specific segment, and plots the mathematical average of those paths. The forecast color is dynamic: it appears bullish if the predicted endpoint is higher than the current RSI, and bearish if it is lower. 🔹 Overbought/Oversold Fills To highlight extreme momentum, the script includes conditional vertical gradient fills. When the RSI rises above the user-defined Overbought Level, a green gradient fills the space between the RSI and the level. Conversely, when it drops below the Oversold Level, a red gradient appears. 🔶 DETAILS The script utilizes User-Defined Types (UDTs) to store sequences of RSI values (Segments) within specific RangeData objects. This architecture allows the script to efficiently manage memory while maintaining a deep history of price momentum patterns. Every time a new bar is processed, the script "looks back" at a pattern of a specific length and stores it in the bucket corresponding to where that pattern started (the anchor point). This creates a library of outcomes categorized by their starting momentum state, which is then accessed on the real-time bar to generate the forecast. 🔶 SETTINGS 🔹 General Settings Historical Limit : Determines the maximum number of historical segments stored for each RSI range. A higher limit provides a more "smoothed" average by including more historical data. Forecast Length : The number of bars into the future the prediction will extend. This also defines the length of the historical patterns being recorded. Range Segments : The number of divisions for the 0-100 RSI scale. For example, setting this to 10 creates segments of 10 units (0-10, 10-20, etc.). RSI Length : The lookback period for the standard RSI calculation. 🔹 Levels Overbought Level : The threshold above which the RSI is considered overbought and the bullish gradient fill is triggered. Oversold Level : The threshold below which the RSI is considered oversold and the bearish gradient fill is triggered. 🔹 Colors Bullish Color : The color used for the RSI line (when > 50), the overbought gradient, and bullish forecasts. Bearish Color : The color used for the RSI line (when < 50), the oversold gradient, and bearish forecasts. Level Color : The color of the Overbought, Oversold, and Center (50) horizontal levels.
Pine Script®指標
由LuxAlgo提供
Reaction Entry Engine | tradewsametReaction Entry Engine is a supply and demand based signal indicator designed to detect first-touch reactions, project structured trade levels, and visualize post-entry outcomes directly on the chart. The script is built around a simple core idea: not every return into a zone should be treated equally. Instead of reacting to every retest, the indicator focuses on first meaningful interactions with validated supply and demand areas and combines that logic with quality filtering, projected risk mapping, and on-chart performance tracking. What the script does This indicator identifies supply and demand zones from confirmed pivot structure on both the chart timeframe and an optional higher timeframe. When price returns to a valid zone and produces a first-touch condition, the script generates a BUY or SELL signal and plots the related trade framework on the chart. The trade framework includes: - entry level - stop loss level - take profit level - TP / SL boxes - historical trade visualization - performance panel - daily PnL panel The result is a signal engine that not only highlights possible setups, but also helps users review how those setups evolve after entry. How it works 1. Supply and demand zone construction The script builds zones from pivot highs and pivot lows. These pivots can be detected from the current chart timeframe and from a selected higher timeframe. A configurable zone thickness is applied around each pivot so that the script works with areas rather than single-price levels. 2. Zone merging When nearby zones of the same type are formed within a defined distance threshold, they can be merged into a broader structural area. This helps reduce overlap and keeps the model cleaner on crowded charts. 3. First-touch logic The main signal engine is based on the first meaningful return into a valid zone. The purpose of this logic is to prioritize earlier reactions rather than repeated tests of the same area. This creates a more selective signal framework compared with simple touch-based scripts that treat every revisit the same way. 4. Impulse filter An optional impulse filter evaluates the move surrounding the pivot that formed the zone. This filter can check: - candle range relative to ATR, - candle body strength, - close position within the candle, - optional volume participation. The goal is to reduce weak zones that were not formed by sufficiently directional movement. 5. Quality engine Each zone can be scored using a quality model. This model uses several factors such as: - displacement after formation, - reaction quality after touch, - penetration depth into the zone, - repeated-touch penalties. The score is then classified into grades such as A, B, or TRASH. Users can decide whether to allow all signals or restrict the engine to higher-grade setups only. 6. Trade projection When a valid first-touch setup appears, the script projects a complete trade map: - BUY or SELL label, - stop loss, - take profit, - TP / SL boxes, - guide lines. Historical TP / SL boxes remain on the chart, which makes it easier to study how previous signals behaved instead of only viewing the active setup. 7. Performance tracking The script includes a performance panel that tracks: - total trades, - wins and losses, - win rate, - profit factor, - average result per trade, - net result in R, - max drawdown, - streak statistics. A separate daily PnL panel tracks daily performance using GMT+3 timing. Why this script is useful This script is intended for traders who want a more structured way to observe first-touch zone reactions without manually drawing every level and calculating every trade projection by hand. Possible use cases include: - identifying early reactions from supply and demand zones, - visually mapping predefined stop and target levels, - reviewing historical signal behavior on the chart, - filtering setups using quality grading, - monitoring day-by-day forward behavior through the built-in performance panels. It is designed as a signal and chart-analysis tool, not as a guarantee of outcome. Usage notes - Use the script on standard candlestick charts. - If you want a cleaner chart, keep zone visibility disabled and use only the signal labels and TP / SL boxes. - If you want stricter setups, increase the quality threshold and keep the impulse filter enabled. - If you want broader signal coverage, allow both chart timeframe and higher timeframe zones. - Different brokers and different symbols may require different pip settings. Important pip setting note If signals do not appear correctly on some forex pairs, the Pip Value input may need to be reduced. For some small-decimal forex instruments, a Pip Value setting of: 0.000001 may be required so that distance, zone thickness, stop loss, and take profit calculations behave correctly. Recommended starting symbols As practical starting references, the current configuration can be tested first on: - EURNZD - EURAUD - GBPAUD - USDCNH These symbols are shared as setup references, not as performance claims. Input values may still need adjustment depending on broker feed, spread structure, and timeframe. Important notes - This script is a structured signal visualization tool. - It does not guarantee future results. - Broker feed differences, spread, volatility, and timeframe selection can affect how zones and signals appear. - The built-in simulator and panels are intended to help users review and organize signal behavior more consistently. Not financial advice.
Pine Script®指標
由trade_w_samet提供
Statistical FVG | ProjectSyndicateStatistical FVG automatically identifies Fair Value Gaps, filters them by session Asian, London, NY, and presents a live statistical dashboard quantifying the historical performance of every FVG type. It transforms the subjective FVG pattern into a purely objective, data-driven trading tool. 🧠 Live Statistical Dashboard — The core of the indicator. This is not a static score. The dashboard displays the live, data-driven statistics for both Bullish and Bearish FVGs, including the Win Rate, Probability of Touch, Average Win/Loss Bars, R:R Ratio, Sample Size, and the critical Expected Value (EV). This gives you an instant, quantifiable edge. 🎯 Session-Specific Edge — The engine's most powerful feature. It doesn't just find FVGs; it categorizes them by the session in which they formed Asian, London, or New York. The dashboard allows you to see if, for example, Bearish FVGs from the New York session have a historically higher win rate and EV than those from the Asian session, allowing you to focus only on the highest-probability setups. 🎨 Normalized & Extended Zones — Eliminates visual noise from inconsistent FVG sizes. This feature forces every FVG zone to a uniform, clean height. It also extends the zones far into the future until they are mitigated, ensuring you never miss a reaction to a key level. 📊 Historical Zone Plotting — Mitigated doesn't mean forgotten. A toggleable option allows you to see all past, mitigated FVGs as faded, non-intrusive zones on your chart. This provides a complete historical footprint of where the market has reacted, allowing for deeper analysis of legacy price structures. ✅ Full-History Accumulator — The statistical engine's credibility comes from its depth. On every bar, it simulates the outcome of every valid FVG across the chart's full history, constantly feeding the win/loss accumulator. The stats you see are robust and based on a large sample size — not just the last few signals. 🔧 Fully Customizable — Control every aspect of the engine, including the TP/SL ATR ratios used for the statistical calculations and the colors/visibility of Bullish, Bearish, and Historical FVG zones. 🔬 Why this algo is unique: Standard FVG indicators are subjective — they just draw boxes on a 3-candle imbalance with no statistical proof of edge. The Manus FVG Stats Engine transforms this common pattern into an objective, quantitative trading instrument. It doesn't just show you an FVG; it shows you the historical performance and statistical probability of that FVG type working out, broken down by session, based on thousands of back-tested examples on the exact chart you are viewing. 🌐 Apply to Gold (XAUUSD), Indices (US30, NAS100), Forex Majors, and Crypto on M5, M15, or H1 timeframes. The engine is designed for intraday assets and timeframes that exhibit clear FVG structures and respect liquidity dynamics. 🗂️ How to use this? The most critical metric is the Expected Value (EV) on the dashboard. A positive EV for a specific FVG type e.g., Bullish NY/London indicates a statistical edge over the long term. Consider only taking trades from FVG types with a positive EV and a Win Rate that aligns with your risk tolerance. For higher-probability setups, align your trades with the prevailing higher-timeframe trend. ⚙️ IMPORTANT NOTICE: This indicator is a professional-grade tool designed to identify a statistical edge. It should NOT be used as a standalone signal for entering trades. Always use it in conjunction with your own trading strategy, price action analysis, and other technical indicators to confirm trade setups and manage risk.
Pine Script®指標
由ProjectSyndicate提供
Volume Delta with Fibonacci Projection [UAlgo]Volume Delta Profile with Fibonacci Projection is a structure driven profiling tool that combines swing discovery, lower timeframe volume allocation, delta analysis, Fibonacci mapping, and forward target projection inside a single chart overlay. Its purpose is not only to show where price has moved, but also to show how participation was distributed inside that move and where the next projected objective levels may sit. The script begins by identifying a dominant recent swing inside a user defined lookback window. Once that swing is found, it becomes the structural anchor for everything else in the indicator. The swing defines the full high to low range, the Fibonacci ladder, the profile segmentation, the delta bands, and the forward projection path. This creates a unified framework where all visual components are tied to the same market structure instead of being calculated independently. A key part of the script is its lower timeframe profiling engine. It requests intrabar data from a lower timeframe and uses that data to distribute volume into price rows and Fibonacci bands inside the active swing. This allows the indicator to estimate where buying activity and selling activity were concentrated with far more detail than a simple bar based approximation. If lower timeframe data is unavailable for a given bar, the script falls back to the chart bar itself so the profile can still be built. The profile section shows how total activity was distributed across the swing range, while the delta section shows which Fibonacci bands leaned more bullish or bearish in terms of estimated participation. A Point of Control line can also be drawn to highlight the most active profile row. In addition, the script projects a continuation path from a chosen Fibonacci level toward target extensions such as 100 percent, 127.2 percent, and 161.8 percent of the swing. The result is a tool that can be used for structure analysis, premium and discount mapping, participation study, and projection planning. It is especially useful for traders who want to combine profile logic and Fibonacci logic inside the same structural framework rather than treating them as separate tools. 🔹 Features 🔸 Structure Based Swing Detection The script automatically finds a recent dominant swing inside the selected lookback period and requires a minimum separation between the major high and low. This gives the indicator a clean structural base before any profile or projection is drawn. 🔸 Auto Lower Timeframe Intrabar Analysis The indicator can automatically choose a lower timeframe for intrabar volume analysis based on the current chart timeframe. A custom intrabar timeframe can also be used if desired. 🔸 Volume Profile Across the Swing Range The full swing range is divided into profile rows, and lower timeframe volume is distributed into those rows according to price overlap. This builds a true participation map across the swing rather than a simple one point volume assignment. 🔸 Delta by Fibonacci Band In addition to row based profiling, the script also groups volume into six Fibonacci bands between the swing extremes. Each band receives estimated buy and sell volume, and the script calculates directional delta for each band. 🔸 Fib POC Highlighting A Point of Control line can be displayed at the profile row with the highest total accumulated volume, giving the user a quick view of the strongest participation level inside the swing. 🔸 Flexible Row Sizing Profile row size can be determined automatically from ATR and tick size, or it can be defined manually through ticks per row. This makes the profile adaptable to very different instruments. 🔸 Forward Projection Path The script draws a projection path starting from a selected retracement level and extends it toward major target levels such as 100 percent, 127.2 percent, and 161.8 percent of the swing range. 🔸 Optional Target Boxes Target zones can be shown as compact boxes around the projected objective levels, helping the user visualize likely reaction areas rather than only exact lines. 🔸 Bull and Bear Participation Coloring The profile and delta display use directional coloring to separate estimated buying volume from estimated selling volume. This makes the participation structure much easier to read visually. 🔸 Complete Structural Integration The swing line, Fibonacci levels, volume profile, delta profile, Point of Control, and projection targets all come from the same underlying swing. This keeps the whole tool internally consistent. 🔹 Calculations 1) Defining the Swing Object type Swing int startIndex int endIndex float startPrice float endPrice float lowPrice float highPrice float swingRange bool bullish int recentOffset int olderOffset This object stores the full structural context of the move being analyzed. It contains: where the swing starts, where it ends, the starting price, the ending price, the full low and high of the move, the total range, the direction, and the bar offsets used for the profiling loop. This is important because the script does not calculate the profile on an arbitrary fixed range. It first defines a real market swing and then builds all later logic from that anchor. 2) Choosing the Lower Timeframe Automatically autoLowerTf() => if timeframe.isseconds "1S" else if timeframe.isminutes and timeframe.multiplier == 1 "1S" else if timeframe.isintraday "1" else if timeframe.isdaily "5" else "60" This function selects a lower timeframe automatically according to the current chart timeframe. Very fast charts use one second data. Intraday charts use one minute data. Daily charts use five minute data. Higher charts default to sixty minute data. The goal is to obtain more granular intrabar structure without forcing the user to choose a lower timeframe manually every time. 3) Computing Automatic Row Size autoTicksPerRow(int atrLen) => int t = int(math.round((0.2 * ta.atr(atrLen)) / syminfo.mintick)) math.max(1, t) When row size mode is set to Auto, the script derives the profile row size from ATR and tick size. It takes twenty percent of ATR, converts that value into ticks, then enforces a minimum of one tick. This creates a profile row height that adapts to the instrument’s current volatility instead of staying fixed across very different market conditions. 4) Finding the Major Swing makeSwing(int lookback, int minBars) => int hiOff = -ta.highestbars(high, lookback) int loOff = -ta.lowestbars(low, lookback) int minSep = math.min(minBars, math.max(1, lookback - 1)) bool bullish = loOff > hiOff int startIndex = bullish ? bar_index - loOff : bar_index - hiOff int endIndex = bullish ? bar_index - hiOff : bar_index - loOff float startPx = bullish ? lo : hi float endPx = bullish ? hi : lo This function discovers the dominant swing inside the selected lookback. First, it locates the highest bar and lowest bar inside the lookback window. Then it determines which came first in time. If the low occurred earlier and the high occurred later, the swing is bullish. If the high occurred earlier and the low occurred later, the swing is bearish. The function also forces a minimum separation between the swing endpoints. If the raw highest and lowest points are too close together, it searches farther out to build a more meaningful move. So the swing used by the indicator is not just the highest high and lowest low. It is a structurally filtered move with time separation and direction. 5) Fibonacci Price Calculation method fibPrice(Swing s, float ratio) => s.bullish ? s.highPrice - s.swingRange * ratio : s.lowPrice + s.swingRange * ratio This method converts a Fibonacci ratio into an actual price inside the current swing. For bullish swings, ratios are measured downward from the swing high. For bearish swings, ratios are measured upward from the swing low. So the Fibonacci ladder always respects swing direction and preserves the standard premium and discount interpretation. 6) Defining the Six Internal Fibonacci Bands method bandRatioAt(Swing s, int slot) => float r = 0.0 if s.bullish switch slot 0 => r := 1.000 1 => r := 0.786 2 => r := 0.618 3 => r := 0.500 4 => r := 0.382 5 => r := 0.236 6 => r := 0.000 else switch slot 0 => r := 0.000 1 => r := 0.236 2 => r := 0.382 3 => r := 0.500 4 => r := 0.618 5 => r := 0.786 6 => r := 1.000 r These ratio slots define the six profiling bands used in the delta section. The bands span the space between: 1.000 and 0.786 0.786 and 0.618 0.618 and 0.500 0.500 and 0.382 0.382 and 0.236 0.236 and 0.000 The order is reversed automatically for bearish swings so the structure remains directionally consistent. So the delta section is not arbitrary. It measures directional participation inside familiar Fibonacci zones. 7) Mapping Prices Into Profile Rows locateRowIndex(float lowPrice, float highPrice, float step, int rows, float price) => float clampedPrice = math.max(lowPrice, math.min(highPrice, price)) int idx = int(math.floor((clampedPrice - lowPrice) / step)) math.max(0, math.min(rows - 1, idx)) This helper function converts any price into its corresponding profile row. The price is first clamped inside the swing boundaries. Then the script measures how far above the swing low the price sits and divides that by the row step size. This gives the row index where the price belongs. That mapping is necessary for distributing intrabar volume into the correct profile level. 8) Mapping Prices Into Fibonacci Bands locateBandIndex(Swing s, float price) => float clampedPrice = math.max(s.lowPrice, math.min(s.highPrice, price)) int idx = 5 for b = 0 to 5 float p1 = s.bandPriceAt(b) float p2 = s.bandPriceAt(b + 1) float bandLow = math.min(p1, p2) float bandHigh = math.max(p1, p2) bool inside = b == 5 ? (clampedPrice >= bandLow and clampedPrice <= bandHigh) : (clampedPrice >= bandLow and clampedPrice < bandHigh) if inside idx := b break idx This function assigns a price to one of the six Fibonacci bands. It walks through the band boundaries one by one, checks where the price sits, and returns the matching band index. That index is later used when a bar or an intrabar has zero height or when band overlap needs to be accumulated. So this function is the bridge between raw prices and the delta profile zones. 9) Lower Timeframe Data Request string ltf = useCustomLtf ? customLtf : autoLowerTf() = request.security_lower_tf(syminfo.tickerid, ltf, ) This is the intrabar engine. The script first decides whether to use the automatic lower timeframe or the custom user defined one. Then it requests arrays of lower timeframe open, high, low, close, and volume values for each chart bar. This means every bar inside the swing can be broken down into smaller internal bars, allowing a more detailed volume allocation than a single chart timeframe candle would allow. 10) Determining Effective Profile Row Size int ticksPerRow = rowSizeMode == "Auto" ? autoTicksNow : manualTicksPerRow float minRowStep = math.max(syminfo.mintick, ticksPerRow * syminfo.mintick) float rowStep = math.max(minRowStep, swing.swingRange / rowsInput) int rowsEff = math.max(1, int(math.ceil(swing.swingRange / rowStep))) rowStep := swing.swingRange / rowsEff This block finalizes the profile geometry. It first determines the tick size per row, either from the automatic ATR based logic or from the manual input. Then it ensures the row step is not smaller than that minimum. After that, it calculates how many rows are actually needed to cover the full swing range. Finally, it recalculates the row height so the entire swing fits perfectly into the effective row count. So the profile is always both instrument aware and range aligned. 11) Estimating Intrabar Direction int dir = prevDir if ic > io dir := 1 else if ic < io dir := -1 else if not na(prevClose) if ic > prevClose dir := 1 else if ic < prevClose dir := -1 else dir := prevDir else dir := prevDir This block decides whether a lower timeframe bar should be treated as bullish or bearish for volume allocation. If close is above open, the bar is treated as buying. If close is below open, the bar is treated as selling. If the bar is neutral, the script falls back to its relation versus the previous close. If that is also neutral, it inherits the previous direction. This gives the script a practical directional model for classifying intrabar volume into buy side or sell side participation. 12) Distributing Intrabar Volume Into Profile Rows for r = 0 to rowsEff - 1 float rowLow = swing.lowPrice + rowStep * r float rowHigh = rowLow + rowStep float overlap = math.min(ih, rowHigh) - math.max(il, rowLow) if overlap > 0 float frac = overlap / iRange rowBuy.addAt(r, buyV * frac) rowSell.addAt(r, sellV * frac) This is one of the most important calculations in the script. For every lower timeframe bar, the script checks how much of that bar overlaps each profile row. If overlap exists, volume is distributed proportionally according to the fraction of the bar’s range that passed through that row. So if an intrabar spends more range inside a certain row, more of its volume is assigned there. This is much more realistic than placing the full volume into a single price row because it respects the bar’s actual vertical path through price. 13) Distributing Intrabar Volume Into Fibonacci Bands for b = 0 to 5 float p1 = swing.bandPriceAt(b) float p2 = swing.bandPriceAt(b + 1) float bandLow = math.min(p1, p2) float bandHigh = math.max(p1, p2) float bandOverlap = math.min(ih, bandHigh) - math.max(il, bandLow) if bandOverlap > 0 float bFrac = bandOverlap / iRange bandBuy.addAt(b, buyV * bFrac) bandSell.addAt(b, sellV * bFrac) The same overlap logic is then applied to the six Fibonacci bands. Each intrabar contributes buy volume and sell volume into the band or bands it overlaps. The contribution is proportional to the amount of overlap relative to the bar’s own range. So the delta section is not built from row totals. It is built directly from participation inside each Fibonacci segment of the swing. 14) Fallback Logic When Lower Timeframe Arrays Are Empty else float bo = open float bh = high float bl = low float bc = close float bv = math.max(volume , 0) int dir = barDirFromOffset(off) If the lower timeframe request returns no intrabar data for a specific chart bar, the script falls back to the bar itself. It reads the normal chart timeframe OHLCV values, determines a direction using the helper method, and then distributes that bar’s volume into rows and bands using the same overlap logic. This is important because it makes the indicator robust. The profile can still be constructed even when granular intrabar data is unavailable. 15) Point of Control Calculation float pocVol = 0.0 float pocPrice = na for r = 0 to rowsEff - 1 float totalRow = rowBuy.get(r) + rowSell.get(r) if totalRow > pocVol pocVol := totalRow pocPrice := swing.lowPrice + rowStep * (r + 0.5) This block finds the Point of Control. The script scans every profile row, calculates total row volume as buy plus sell, and keeps track of the highest one. The midpoint of that strongest row becomes the Point of Control price. So the POC is the single most active price area inside the swing based on the constructed row profile. 16) Building the Horizontal Volume Profile int totalWidthBars = math.max(1, int(math.round(profileWidthBars * (total / maxRowTotal)))) sellWidthBars := int(math.round(totalWidthBars * (sellVol / total))) buyWidthBars := totalWidthBars - sellWidthBars if sellWidthBars > 0 pushBox(boxPool, profileStartX, rowHigh, profileStartX + sellWidthBars, rowLow, color.new(bearColor, 72), color.new(bearColor, 100)) if buyWidthBars > 0 int buyLeftX = profileStartX + sellWidthBars int buyRightX = buyLeftX + buyWidthBars pushBox(boxPool, buyLeftX, rowHigh, buyRightX, rowLow, color.new(bullColor, 72), color.new(bullColor, 100)) This is the profile drawing engine. Each row’s total participation is scaled relative to the strongest row. That determines how wide the full profile bar should be. Then the script splits that width between sell volume and buy volume according to their relative shares. The selling segment is drawn first, followed by the buying segment. So each row shows both: how much total volume was traded there, and how that volume split between bearish and bullish participation. 17) Delta Calculation by Fibonacci Band float deltaV = buyV - sellV float deltaPct = totalV > 0 ? (deltaV / totalV) * 100.0 : 0.0 color dColor = math.abs(deltaV) <= 0.0000001 ? fibColor : deltaV > 0 ? bullColor : bearColor This block calculates directional delta inside each Fibonacci band. Delta is simply buy volume minus sell volume. Delta percent then normalizes that difference by total volume inside the band. If the result is positive, the band leaned bullish. If the result is negative, the band leaned bearish. If the result is near zero, the band was balanced. So the delta section tells the user not just how much activity occurred in a band, but which side dominated it. 18) Scaling the Delta Bars maxBandAbs := math.max(maxBandAbs, math.abs(buyV - sellV)) int dWidthBars = maxBandAbs > 0 and math.abs(deltaV) > 0 ? math.max(1, int(math.round(deltaWidthBars * (math.abs(deltaV) / maxBandAbs)))) : 1 pushBox(boxPool, deltaStartX, bandHigh, deltaStartX + dWidthBars, bandLow, color.new(dColor, 76), color.new(dColor, 100)) The script first finds the maximum absolute delta among all bands. Then it uses that value as the scaling reference for the delta boxes. A band with the strongest absolute delta receives the widest box. Smaller delta bands receive proportionally narrower boxes. So the delta profile communicates both direction and relative strength across the Fibonacci segments of the swing. 19) Drawing the Core Fibonacci Ladder for i = 0 to fibRatios.size() - 1 float ratio = fibRatios.get(i) float price = swing.fibPrice(ratio) bool keyLevel = math.abs(ratio - projBaseRatio) < 0.0001 or ratio == 0.0 or ratio == 1.0 color lc = keyLevel ? color.new(fibColor, 10) : color.new(fibColor, 68) pushLine(linePool, swing.startIndex, price, fibEndX, price, lc, keyLevel ? line.style_dashed : line.style_dotted, 1) This loop draws the Fibonacci levels across the swing. Every ratio from zero to one is converted into price using the earlier swing based Fibonacci method. The selected projection base level plus the zero and one boundaries are emphasized, while the other internal levels are drawn more softly. So the user gets a full retracement map tied directly to the chosen swing. 20) Building the Projection Path and Targets float cPrice = swing.fibPrice(projBaseRatio) float target1 = swing.bullish ? cPrice + swing.swingRange * 1.000 : cPrice - swing.swingRange * 1.000 float target2 = swing.bullish ? cPrice + swing.swingRange * 1.272 : cPrice - swing.swingRange * 1.272 float target3 = swing.bullish ? cPrice + swing.swingRange * 1.618 : cPrice - swing.swingRange * 1.618 pushLine(linePool, swing.endIndex, swing.endPrice, cX, cPrice, color.new(projColor, 30), line.style_dashed, 2) pushLine(linePool, cX, cPrice, t1X, target1, color.new(projColor, 0), line.style_solid, 2) pushLine(linePool, t1X, target1, t2X, target2, color.new(projColor, 18), line.style_solid, 2) pushLine(linePool, t2X, target2, t3X, target3, color.new(projColor, 35), line.style_solid, 2) This is the forward projection engine. The chosen Fibonacci retracement level becomes point C. From that point, the script projects three forward targets based on the swing range: 100 percent, 127.2 percent, and 161.8 percent. For bullish swings, the targets are projected upward. For bearish swings, the targets are projected downward. The script then connects the swing end to point C and extends the projection path forward through each target. So the projection section transforms the structural swing into a directional roadmap. 21) Drawing Target Boxes float zoneHalf = math.max(swing.swingRange * 0.015, syminfo.mintick * 8) if showTargets pushBox(boxPool, t1X - 1, target1 + zoneHalf, t1X + 2, target1 - zoneHalf, color.new(projColor, 87), color.new(projColor, 55)) pushBox(boxPool, t2X - 1, target2 + zoneHalf, t2X + 2, target2 - zoneHalf, color.new(projColor, 89), color.new(projColor, 60)) pushBox(boxPool, t3X - 1, target3 + zoneHalf, t3X + 2, target3 - zoneHalf, color.new(projColor, 91), color.new(projColor, 68)) Instead of marking the targets as exact single prices only, the script can draw small target boxes around them. The vertical thickness of each box is based on a fraction of the swing range, with a minimum tick based width. This helps present the targets as realistic reaction zones rather than razor thin levels. So the projection module provides both precise target labels and visual target areas.
Pine Script®指標
由UAlgo提供
1
Adaptive Momentum Fusion [WillyAlgoTrader]📡 Adaptive Momentum Fusion is a separate-pane oscillator that replaces the fixed EMAs inside a standard MACD with selectable adaptive moving averages — six different adaptation engines that each respond to a different market dimension (efficiency, volatility, fractal structure, momentum, volume, or a weighted composite of all five). The oscillator line and signal line are then processed through Jurik-style smoothing to reduce jitter without adding lag. The result is a MACD-like oscillator where the core moving averages automatically adjust their speed to current market conditions, producing cleaner crossovers, more meaningful histogram readings, and built-in divergence detection. A standard MACD uses fixed-length EMAs (typically 12/26/9). This means the same smoothing is applied whether the market is trending strongly, ranging sideways, experiencing a volatility spike, or consolidating. The result: late crossovers in trends, whipsaws in ranges, and false divergences during choppy periods. This indicator solves the problem at the source — the moving averages themselves. Instead of fixed EMAs, each adaptation engine dynamically adjusts the smoothing constant (alpha) on every bar based on a real-time market measurement. In a strong trend, the Efficiency engine detects high directional efficiency and increases alpha → faster MA → earlier crossover. In a range, efficiency drops and alpha decreases → slower MA → fewer whipsaws. Each engine uses a different measurement to achieve this adaptation, and the user selects which dimension matters most for their market. 🧩 WHY THESE COMPONENTS WORK TOGETHER A MACD with adaptive MAs alone would still produce a noisy signal line (the EMA of the oscillator). Adding adaptation to the base MAs but keeping a fixed EMA for the signal line creates a mismatch: the oscillator adapts but the signal doesn't, causing crossover lag to reappear at the signal level. This indicator addresses the full signal chain: Adaptive fast MA → Adaptive slow MA → Oscillator (MACD or PPO) → Jurik-smoothed signal line → 4-state histogram → Divergence scanner The adaptive MAs eliminate the fixed-speed problem at the source. The MACD/PPO dual mode lets you choose between absolute (price-scaled) and percentage (normalized) output. The Jurik smoother replaces the standard signal EMA with a 3-stage filter that reduces jitter while preserving crossover timing — critical because adaptive oscillators produce more variable readings than fixed ones. The 4-state histogram (accelerating/decelerating × bullish/bearish) quantifies momentum acceleration, not just direction. And the divergence scanner works on the adaptive oscillator itself, which produces more reliable pivots than a fixed MACD because the adaptive MAs have already filtered out noise-driven fluctuations. Removing the adaptive engines returns you to a standard MACD. Removing the Jurik smoother reintroduces signal line jitter that the adaptive engines amplify. Removing the histogram states loses momentum acceleration information. The full pipeline produces cleaner signals than any subset. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Six selectable adaptation engines. Each engine computes a dynamic smoothing constant (alpha) that controls how fast the moving average reacts. All engines feed into the same adaptive EMA core: result = alpha × source + (1 − alpha) × result . The difference is how alpha is calculated: Efficiency (Kaufman AMA): Computes the Efficiency Ratio: ER = |price − price | / sum(|price − price |, N). ER ranges from 0 (pure chop — price moves a lot bar-to-bar but goes nowhere net) to 1 (pure trend — every bar moves in the same direction). The smoothing constant: sc = (ER × (fastSc − slowSc) + slowSc)², where fastSc = 2/3, slowSc = 2/31. This is the classic Kaufman Adaptive Moving Average approach. Best all-around engine. Volatility (ATR-based): Computes volRatio = ATR(len) / SMA(ATR, len×2). When current volatility exceeds its average (ratio > 1), alpha increases → MA speeds up to track the expanding price action. When volatility contracts (ratio < 1), alpha decreases → MA slows down to avoid noise. Alpha = baseAlpha × volRatio, clamped to . Best for instruments with distinct volatility regimes (crypto, commodities). Fractal (Hurst-inspired): Estimates the fractal dimension of the price series using rescaled range analysis: the full-range is compared to the sum of two half-ranges. fracDim = 1 + log(sumHalf) / log(2 × rangeFull). A fractal dimension near 1.0 indicates trending behavior (smooth), near 2.0 indicates mean-reverting (rough). Alpha = exp(−4.6 × (fracDim − 1)), which maps: fracDim ≈ 1.0 → alpha ≈ 1.0 (fast, trending), fracDim ≈ 2.0 → alpha ≈ 0.01 (slow, ranging). Best for detecting regime changes between trending and mean-reverting markets. Momentum (ROC-based): Computes the Rate of Change normalized against its recent maximum: norm = |ROC| / highest(|ROC|, len×2). When momentum is strong relative to recent history, alpha increases. Alpha = baseAlpha + norm × (1 − baseAlpha) × 0.5. This makes the MA react faster during breakouts and momentum surges while staying smooth during low-momentum drift. Best for breakout-oriented strategies. Volume: Computes volRatio = volume / SMA(volume, len). When volume exceeds its average (institutional participation), the MA speeds up. Alpha = baseAlpha × √(volRatio). The square root prevents extreme volume spikes from making the MA too reactive. Auto-disabled on instruments without volume data (forex) — falls back to baseAlpha. Best for stocks and crypto where volume confirms moves. Composite (weighted blend): Runs all five engines simultaneously and blends the results: with volume = 30% Efficiency + 20% Volatility + 20% Fractal + 15% Momentum + 15% Volume. Without volume = 35% Efficiency + 25% Volatility + 25% Fractal + 15% Momentum. This produces the most robust adaptation but is slightly slower because it averages five different smoothing perspectives. Best for users who don't want to choose a single engine. 2️⃣ Jurik-style signal line smoothing. The standard MACD signal line is a simple EMA of the oscillator. This indicator replaces it with a 3-stage Jurik-inspired filter: beta = 0.45 × (len − 1) / (0.45 × (len − 1) + 2) alphaJ = beta³ e0 = (1 − alphaJ) × source + alphaJ × e0 e1 = (source − e0) × (1 − beta) + beta × e1 e2 = (e0 + phase × e1 − e2 ) × (1 − alphaJ)² + alphaJ² × e2 The three stages progressively remove jitter while maintaining phase alignment. The phase parameter (Jitter Reduction, default 0.7) controls how much additional smoothing is applied: 0.0 = minimal smoothing (fast but noisy), 1.0 = maximum smoothing (smooth but slightly more lag). This is particularly important for adaptive oscillators because the variable-speed MAs produce a more erratic oscillator line than fixed EMAs — the Jurik filter absorbs this variability at the signal level. 3️⃣ MACD/PPO dual output mode. — MACD mode : oscillator = fastMA − slowMA (absolute difference, price-scaled). Readings scale with instrument price — useful for single-instrument analysis. — PPO mode : oscillator = (fastMA − slowMA) / slowMA × 100 (percentage difference, normalized). Readings are comparable across instruments and time — useful for scanning, multi-market analysis, or consistent threshold settings. 4️⃣ 4-state momentum histogram. The histogram (oscillator − signal) is classified into four states based on value and direction of change: — 🟢 Accelerating bullish : histogram > 0 AND rising (momentum strengthening) — 🟢 Decelerating bullish : histogram > 0 AND falling (momentum fading, potential reversal ahead) — 🔴 Accelerating bearish : histogram < 0 AND falling (selling pressure increasing) — 🔴 Decelerating bearish : histogram < 0 AND rising (selling pressure easing, potential bounce) Each state has a distinct color intensity: accelerating = fully saturated, decelerating = faded. This provides immediate visual recognition of whether momentum is building or exhausting — the most actionable information from a histogram. 5️⃣ Divergence detection with adaptive oscillator. The indicator scans for regular divergences between price and the adaptive oscillator: — Regular Bullish Divergence : price makes a lower low, but the oscillator makes a higher low → selling pressure is weakening despite lower prices → potential reversal up — Regular Bearish Divergence : price makes a higher high, but the oscillator makes a lower high → buying pressure is weakening despite higher prices → potential reversal down Pivots are detected using a custom function with configurable lookback (default 30 bars) and a fixed right-bar confirmation of 5 bars. Divergences are labeled on the oscillator pane and optionally drawn as connecting lines. The divergence state persists in the dashboard for 20 bars after detection, then decays. Divergences detected on the adaptive oscillator are more reliable than on a standard MACD because the adaptive MAs have already filtered regime-inappropriate noise — the pivots in the oscillator correspond to genuine momentum shifts, not noise-driven wiggles. 6️⃣ Zero-line cross signals. When enabled, the indicator marks when the oscillator crosses the zero line — which corresponds to the fast adaptive MA crossing the slow adaptive MA. In MACD terms, this is the equivalent of the "MACD crossing zero." Because the MAs are adaptive, these crossovers occur at more structurally meaningful points than with fixed EMAs. 7️⃣ Signal strength scoring (0–100). Each bar's histogram absolute value is normalized against its recent maximum over 50 bars: strength = |histogram| / highest(|histogram|, 50) × 100. This provides a relative measure: 100 = histogram is at its strongest in the last 50 bars, 0 = no momentum. Classified as Strong (≥ 70), Medium (≥ 40), Weak (< 40). Displayed in the dashboard. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Engine selection: The selected adaptation engine computes a dynamic alpha value on each bar based on its specific market measurement (efficiency ratio, ATR ratio, fractal dimension, ROC normalization, volume ratio, or composite blend). Step 2 — Adaptive MA calculation: The fast MA and slow MA are each computed using the adaptive EMA formula: result = alpha × source + (1 − alpha) × result . The same engine is used for both, with different length parameters (fast = default 8, slow = default 21). Step 3 — Oscillator: MACD mode: osc = fastMA − slowMA. PPO mode: osc = (fastMA − slowMA) / slowMA × 100. Step 4 — Signal line: The oscillator is passed through the Jurik 3-stage filter with the configured signal length (default 7) and jitter reduction factor (default 0.7). Step 5 — Histogram: hist = oscillator − signal. Classified into 4 states (accelerating/decelerating × bullish/bearish) based on sign and direction of change. Step 6 — Divergence scan: Custom pivot detection identifies local highs and lows in both the oscillator and price. When a new pivot is found, it's compared to the previous pivot to check for divergence conditions (price lower low + osc higher low, or price higher high + osc lower high). Step 7 — Signals: Crossovers (oscillator crossing signal line) and zero-line crosses are detected. All signals require barstate.isconfirmed + warmup check. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — the adaptive oscillator appears in a separate pane 2. Select an adaptation engine matching your market (Efficiency for general use) 3. Green line above red = bullish momentum, below = bearish 4. Histogram bars show momentum acceleration (bright) vs deceleration (faded) 5. Divergence labels mark potential reversals 👁️ Reading the pane: — 🟢 Green oscillator line above signal line = bullish momentum — 🔴 Red oscillator line below signal line = bearish momentum — 🟢 Bright green histogram = accelerating bullish momentum — 🟢 Faded green histogram = decelerating bullish (momentum fading) — 🔴 Bright red histogram = accelerating bearish momentum — 🔴 Faded red histogram = decelerating bearish (selling easing) — ▲ label = buy crossover signal (oscillator crosses above signal) — ▼ label = sell crossover signal — ● dot on zero line = zero-line cross — "Bull Div" / "Bear Div" labels = detected divergences 🔧 Engine selection guide: — Efficiency : best default for most markets — adapts to trending vs ranging — Volatility : best for instruments with clear vol regimes (crypto, commodities) — Fractal : best for detecting regime shifts (trending ↔ mean-reverting) — Momentum : best for breakout strategies — speeds up on strong moves — Volume : best for stocks/crypto where volume confirms participation — Composite : most robust — blends all dimensions, good when unsure 🔧 Tuning guide: — Too many whipsaws: increase Slow Length, increase Signal Length, increase Jitter Reduction — Signals too late: decrease Fast/Slow Length, decrease Signal Length, decrease Jitter Reduction — Histogram too noisy: increase Jitter Reduction toward 0.8–1.0 — Divergences too frequent: increase Divergence Lookback (40–60) — Cross-market comparison: switch to PPO mode for normalized output ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Adaptation Engine (default Efficiency): Efficiency / Volatility / Fractal / Momentum / Volume / Composite — Fast Length (default 8): fast adaptive MA period — Slow Length (default 21): slow adaptive MA period — Signal Length (default 7): Jurik signal smoothing period — Output Mode (default MACD): MACD (absolute) or PPO (percentage) 🔍 Filters: — Detect Divergences (default On): scan for regular divergences — Divergence Lookback (default 30): pivot search depth — Zero Line Cross Signals (default On): mark zero crossings 🔧 Advanced: — Jitter Reduction (default 0.7): Jurik phase parameter (0.0–1.0) — Auto / Dark / Light theme 📊 Dashboard — Trend: oscillator vs signal line direction (Bullish / Bearish / Neutral) — Signal: last crossover (BUY / SELL / Wait) — Strength: histogram normalized to 50-bar max (Strong / Medium / Weak with %) — Momentum: 4-state acceleration (Accel ▲ / Decel ▽ / Accel ▼ / Decel △) — Divergence: current divergence state (Bull Div / Bear Div / None) — Engine / TF: selected engine and timeframe — Version 🔔 Alerts — 🟢 BUY / 🔴 SELL — oscillator-signal crossover (ticker, price, timeframe, engine) — 🟡 ZERO BULL CROSS / ZERO BEAR CROSS — zero-line crossing — 🔵 BULL DIVERGENCE / BEAR DIVERGENCE — detected divergence All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals and divergences require barstate.isconfirmed. A warmup period (2× slow length, minimum 50 bars) prevents signals during insufficient data. The adaptive MAs are deterministic — once a bar closes, the MA value for that bar never changes. — 📐 This is a separate-pane oscillator, not an overlay. It displays in its own pane below the chart. The oscillator values are momentum readings, not price levels. Use it alongside your chart for confluence, not as a standalone trading system. — ⚖️ The six engines produce different signals on the same data . Efficiency and Composite tend to produce the most similar results. Fractal can diverge significantly during regime transitions. Volume engine auto-falls back to base alpha on instruments without volume data. — 📊 Signal strength is relative to recent 50 bars , not absolute. A "Strong" reading during a low-volatility week may be weaker in absolute terms than a "Weak" reading during a high-volatility week. — 🔄 Divergences use a 5-bar right confirmation — they appear 5 bars after the actual pivot. This delay is inherent to pivot detection and cannot be eliminated without introducing false positives. — 📏 PPO mode normalizes the output as a percentage, making threshold settings (e.g., "divergence when oscillator > 2") comparable across instruments. MACD mode values scale with price — a reading of 5.0 on a $100 stock is different from 5.0 on a $50,000 BTC chart. — 🛠️ This is a momentum analysis tool , not an automated trading bot. It measures and visualizes adaptive momentum — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume engine auto-adapts to available data.
Pine Script®指標
由WillyAlgoTrader提供
HTF Reversal Divergences [LuxAlgo]The HTF Reversal Divergences indicator is a multi-timeframe analysis tool that integrates higher timeframe (HTF) price action patterns, RSI divergences, and advanced candle projections (PO3) to identify potential market reversals. 🔶 USAGE The indicator is designed to provide traders with a comprehensive view of market exhaustion and trend shifts by combining momentum oscillators with structural price patterns. Users can monitor HTF candles (e.g., 1H, 4H) while trading on lower timeframes (e.g., 5m, 15m). When a reversal pattern like an Engulfing candle or a Pin Bar forms on the higher timeframe, the script highlights the specific area on the chart using styled boxes and labels. 🔹 RSI Divergences The script calculates the Relative Strength Index (RSI) and automatically detects regular divergences. These are visualized with connecting lines on both the indicator pane and the main price chart: Bullish Divergence : Occurs when price makes a lower low but the RSI makes a higher low, suggesting waning downward momentum. Bearish Divergence : Occurs when price makes a higher high but the RSI makes a lower high, suggesting waning upward momentum. 🔹 Advanced HTF PO3 (Power of 3) A unique feature of this tool is the projection of Higher Timeframe candles to the right of the current price action. This allows traders to see how the current lower-timeframe bars are contributing to the formation of the larger HTF candle (Open, High, Low, Close). The PO3 projection includes a "Running Delta" which tracks volume-based buying and selling pressure within the current HTF period. Dashed lines connect the projected candle's OHLC levels back to the specific bars where those levels were established on the current timeframe. 🔶 DETAILS The indicator uses request.security() to fetch data from the user-specified higher timeframe. The reversal patterns are defined as follows: Engulfing : A candle that completely overlaps the body of the previous candle in the opposite direction. Pin Bars : Hammers and Shooting Stars, defined by a long wick representing at least 60% of the total candle range. The PO3 (Accumulation, Manipulation, Distribution) logic is reflected in the live candle projection, helping traders visualize where the "open" of the session is relative to current price, and whether the high or low of the HTF bar has likely been set. 🔶 SETTINGS 🔹 HTF Reversal Patterns High Timeframe : Sets the timeframe used for pattern detection and candle projections. Show Engulfing Patterns : Toggles the detection of bullish and bearish engulfing candles. Show Pin Bars : Toggles the detection of Hammers and Shooting Stars. Colors : Customize the visual representation of bullish and bearish structural patterns. 🔹 RSI Divergence Show RSI Divergences : Toggles the calculation and display of momentum divergences. RSI Length : The lookback period for the RSI calculation. Pivot Lookbacks : Determines the sensitivity of the pivot detection used for finding divergence points. 🔹 Advanced: HTF PO3 Show HTF PO3 : Toggles the projected candle interface on the right side of the chart. Candles to Show : The number of historical HTF candles to project alongside the live one. Right Offset : How many bars to the right the projection is rendered. Show PO3 Price Labels/Delta : Toggles specific data points on the projection UI.
Pine Script®指標
由LuxAlgo提供
7
Smart Money SniperSmart Money Sniper combines 5 institutional signal types into one clean overlay — no repainting, no clutter, just high-conviction entries based on real Smart Money Concepts and ICT methodology. SIGNAL TYPES: 🟢 LONG BOS / 🔴 SHORT BOS — Full SMC sequence: liquidity sweep → CHoCH → Break of Structure. Highest conviction entries. 🔵 LONG DIV / 🟠 SHORT DIV — RSI divergence at swing extremes with engulfing candle confirmation. 90-100% win rate in backtesting. 🟡 LONG ST / SHORT ST — Supertrend flip with ADX trend strength filter. Early trend change warning. 🟣 LONG MOM / SHORT MOM — MACD cross + RSI fade + structure break. Catches trendline breaks without waiting for full SMC sequence. ⚪ LONG REJ / SHORT REJ — Real-time resistance and support rejection using live 20-bar highs and lows. No pivot lag. Fires the moment the rejection candle closes. BUILT-IN FILTERS: - ADX trend strength — no signals in weak trends - Volume confirmation — institutional activity only - Ranging market filter — yellow background warning - RSI zone filters tuned per signal type - LONG BOS cooldown timer — prevents cluster entries SETTINGS: All RSI thresholds are adjustable inputs so you can tune the indicator for your preferred timeframe. Recommended defaults are optimized for the 1H chart. Best timeframes: 1H (entries) | 4H (direction) Developed and backtested on BTCUSD across 18 months of data covering both bull and bear market conditions. Alerts included for all 10 signal types plus combined LONG/SHORT any-signal alerts.
Pine Script®指標
由joshuavegahawkins提供
3
[blackcat] L3 Footprint Fusion Pro█ OVERVIEW Footprint Fusion Pro is a professional-grade order flow analysis indicator that leverages TradingView's native request.footprint() function to provide real-time volume footprint visualization. This indicator reveals institutional trading activity through delta analysis, value area tracking, imbalance detection, and cumulative volume delta (CVD) monitoring — essential tools for order flow traders. █ CONCEPTS This indicator utilizes Volume Footprint Analysis methodology to decode market microstructure and identify hidden supply/demand dynamics. Key Principles: • Volume Delta : The difference between buying and selling volume at each price level, revealing true market sentiment • Value Area (VA) : The price range where 70% (configurable) of volume occurred — the "fair value" zone • Point of Control (POC) : The price level with the highest traded volume — the market's equilibrium point • Imbalance Detection : Identifies price levels with significant buy/sell volume asymmetry • Cumulative Volume Delta (CVD) : Running total of delta, tracking institutional accumulation/distribution patterns • Absorption : When aggressive selling/buying is absorbed by passive liquidity, signaling potential reversals █ HOW TO USE 1 — Setup Add the indicator to your chart. Note: This indicator requires a Premium or Ultimate TradingView plan to access the request.footprint() function. 2 — Parameter Guidance • Ticks Per Row : Price granularity for footprint rows (lower = more detailed, higher = smoother) • Value Area Percent : Typically 70%, defines the "fair value" zone boundaries • Imbalance Threshold : 300% means 3:1 buy/sell ratio required for imbalance detection 3 — Signal Interpretation • Green background : Positive delta (buying pressure dominant) • Red background : Negative delta (selling pressure dominant) • Orange clouds : Stacked imbalance zones (support/resistance clusters) Input Parameters: • Ticks Per Row : Price range for each footprint row (default: 10) • Value Area Percent : Volume percentage in value area (default: 70%) • Imbalance Threshold : Buy/sell ratio threshold for imbalance detection (default: 300%) • Minimum Stacked Imbalance Rows : Consecutive imbalances for signal (default: 3) • Divergence Detection Lookback : Bars for pivot detection (default: 5) • Absorption Threshold : POC delta to volume ratio multiplier (default: 2.0) • Volume Bubble Threshold : Volume multiplier for bubble display (default: 1.5x) █ FEATURES 8 Visualization Layers: 1. Delta Heatmap Background • Green gradient intensity shows buying pressure strength • Red gradient intensity shows selling pressure strength • Darker colors = stronger conviction 2. Volume Bubbles • Circle markers at abnormally high volume levels • Green bubbles: Buy volume dominant • Red bubbles: Sell volume dominant • Size indicates relative volume magnitude 3. Imbalance Clouds • Semi-transparent zones highlighting consecutive buy/sell imbalances • Green clouds: Stacked buy imbalances (support zone) • Red clouds: Stacked sell imbalances (resistance zone) 4. Unfinished Auction Markers • 🔺 marker: Low volume at upper wick (potential retracement magnet) • 🔻 marker: Low volume at lower wick (potential retracement magnet) • Indicates price levels where auction was not completed 5. CVD Flow Bar • Real-time cumulative delta progress bar on right side • Shows institutional accumulation/distribution trend • Green: CVD rising (accumulation) • Red: CVD falling (distribution) 6. Delta Divergence Arrows • ⬇️ Bearish Divergence: Price new high + Delta weakening = potential reversal • ⬆️ Bullish Divergence: Price new low + Delta strengthening = potential bounce 7. Mini Volume Profile • Compact volume bars on right side of recent candles • Shows volume distribution at glance • Color indicates delta direction 8. Order Flow Meter • Real-time buy/sell power meter in chart corner • Visual bar display of market conviction • Delta status indicator (Bullish/Bearish/Neutral) Signal Labels: • 🟢 Buy Absorption : Price dropping but POC shows buying pressure • 🔴 Sell Absorption : Price rising but POC shows selling pressure • 🟡 False Breakdown : VAL break with positive delta (bullish trap) • 🟠 False Breakout : VAH break with negative delta (bearish trap) █ SIGNALS Visual Elements: • POC Line (Orange) : Point of Control — highest volume price level • VAH Line (Green) : Value Area High — upper fair value boundary • VAL Line (Red) : Value Area Low — lower fair value boundary • Blue Zone : Value Area fill — the "fair value" trading range Status Table (Top Right): • Volume Delta: Current bar delta value and direction • CVD: Cumulative delta with accumulation/distribution trend • POC Price: Current point of control with proximity indicator • Value Area: VAH-VAL range with inside/outside status • Imbalance Detection: Buy/Sell streak count with signal strength • Absorption Status: Active absorption signals • Divergence Alert: Active divergence signals Alert Conditions: • 🚨 Bearish/Bullish Divergence Alerts • 💚 Buy Absorption Alert • ❤️ Sell Absorption Alert • ⬆️ VAH Breakout Alert • ⬇️ VAL Breakdown Alert • 📈 Stacked Buy Imbalance Alert • 📉 Stacked Sell Imbalance Alert █ LIMITATIONS • Requires Premium/Ultimate Plan : The request.footprint() function is only available on paid TradingView subscriptions • Real-time Data Only : Footprint data is not available for historical bars on some instruments • Tick Data Dependent : Accuracy depends on broker's tick data quality • Not Suitable for All Markets : Best results on high-volume instruments (forex majors, indices, popular stocks) • Visual Clutter : Multiple visualization layers may overlap on lower timeframes — disable unused features • Repainting : Real-time footprint data updates during bar formation; signals are final on bar close █ NOTES • Best used on 5-minute to 4-hour timeframes for optimal signal clarity • Combine with support/resistance and trend analysis for confirmation • Value Area acts as a magnet — price tends to revert to VA zone • POC levels from high-volume bars often become support/resistance • Divergences are more reliable at key market structure levels • Absorption signals are strongest when occurring at known S/R zones Recommended Workflow: 1 — Identify market structure and key levels 2 — Check Value Area position (price inside/outside VA) 3 — Monitor CVD for accumulation/distribution patterns 4 — Watch for absorption signals at key levels 5 — Use divergence signals for reversal confirmation ═════════════════════════════════════════════════════════════════════════ For questions or feedback, use comments section below.
Pine Script®指標
由blackcat1402提供
4
[blackcat] L3 Volume Imbalance Pro█ OVERVIEW Volume Imbalance Pro is a professional-grade order flow analysis indicator that leverages TradingView's native request.footprint() function to detect and visualize volume imbalances in real-time. This indicator reveals institutional trading activity through stacked imbalance detection, divergence analysis, VWAP validation, and multi-signal confirmation — essential tools for order flow traders seeking high-probability entry signals. █ CONCEPTS This indicator utilizes Volume Imbalance Analysis methodology to identify aggressive institutional order flow and potential price direction. Key Principles: • Volume Imbalance : Significant asymmetry between buy and sell volume at adjacent price levels, revealing aggressive institutional activity • Stacked Imbalance : 3+ consecutive imbalance rows forming a "tower" — indicates strong directional conviction with 75-80% win rate • Imbalance Strength : The ratio of dominant volume to passive volume, measuring intensity of institutional pressure • Divergence Confirmation : RSI/MACD divergence combined with imbalance detection for high-probability reversal signals • VWAP Validation : Price position relative to VWAP combined with imbalance direction confirms institutional alignment • Absorption Detection : When price moves against imbalance direction, indicating institutional accumulation/distribution █ HOW TO USE 1 — Setup Add the indicator to your chart. Note: This indicator requires a Premium or Ultimate TradingView plan to access the request.footprint() function. 2 — Parameter Guidance • Ticks Per Row : Price granularity for footprint rows (lower = more detailed, higher = smoother) • Value Area Percent : Typically 70%, defines the "fair value" zone boundaries • Imbalance Threshold : 300% means 3:1 buy/sell ratio required for imbalance detection • Min Stacked Imbalance Rows : Minimum consecutive imbalances for stacked signal (default: 3) 3 — Signal Interpretation • Green heatmap clouds : Buy imbalance zones (potential support) • Red heatmap clouds : Sell imbalance zones (potential resistance) • Tower markers (▲/▼) : Stacked imbalance signals with layer count • Arrow flow lines : Capital flow direction visualization Input Parameters: • Ticks Per Row : Price range for each footprint row (default: 10) • Value Area Percent : Volume percentage in value area (default: 70%) • Imbalance Threshold : Buy/sell ratio threshold for imbalance detection (default: 300%) • Min Stacked Imbalance Rows : Consecutive imbalances for stacked signal (default: 3) • RSI Period : RSI calculation period (default: 14) • RSI Overbought/Oversold : Extreme level thresholds (default: 70/30) • MACD Fast/Slow/Signal : MACD parameters (default: 12/26/9) █ FEATURES 5 Visualization Layers: 1. Imbalance Heatmap Cloud • Semi-transparent boxes highlighting price levels with detected imbalances • Green gradient: Buy imbalance intensity (darker = stronger) • Red gradient: Sell imbalance intensity (darker = stronger) • Intensity based on imbalance strength ratio 2. Stacked Imbalance Tower • ▲ markers: Stacked buy imbalance layers (below price) • ▼ markers: Stacked sell imbalance layers (above price) • Layer count indicates signal strength (3+ layers = high win rate) • Color intensity increases with stack height 3. Dynamic Arrow Flow • Upward arrow: Pure buy imbalance (unidirectional bullish pressure) • Downward arrow: Pure sell imbalance (unidirectional bearish pressure) • Bidirectional arrows: Conflict zone (both buy and sell imbalances present) • Width indicates conviction strength 4. VWAP Imbalance Validation Bar • Real-time VWAP position indicator on right side • Green bar segment: Buy imbalances above VWAP (institutional confirmation) • Red bar segment: Sell imbalances below VWAP (institutional confirmation) • Visual gauge of imbalance alignment with VWAP 5. Imbalance Pulse • Histogram showing combined imbalance strength • Positive pulse: Buy pressure dominance • Negative pulse: Sell pressure dominance • Height proportional to imbalance intensity Signal Labels: • 🏢 Stacked Buy/Sell Imbalance : 3+ consecutive imbalance layers with 75-80% win rate • 💎 RSI+Imbalance Divergence : Divergence confirmed by imbalance — high win rate reversal • ⬆️/⬇️ VWAP Breakout/Breakdown+Imb : VWAP cross with imbalance confirmation • 🔵/🔴 RSI Oversold/Overbought+Imb : RSI extreme with imbalance alignment • 📈/📉 MACD Golden/Death Cross+Imb : MACD cross with imbalance confirmation • 🧽 Buy/Sell Absorption : Institutional accumulation/distribution detected █ SIGNALS Visual Elements: • VWAP Line (Orange) : Volume Weighted Average Price — institutional fair value • POC Line (Yellow) : Point of Control — highest volume price level • Green Triangles : RSI oversold + buy imbalance (bounce warning) • Red Triangles : RSI overbought + sell imbalance (pullback warning) Status Table (Configurable Position): • Buy Imbalance: Count, stacked status, and pressure direction • Sell Imbalance: Count, stacked status, and pressure direction • Imbalance Strength: Buy/Sell strength ratio with dominant side • RSI: Current value, overbought/oversold status, and signal • MACD: Histogram value, bullish/bearish status, and alignment • VWAP Position: Distance from VWAP, position status, and breakout signal • Divergence: Detection count, confirmation status, and type • Absorption: Active absorption type and value indication • Trend Direction: Combined trend assessment with MACD alignment • Strength Score: Composite score (-100 to +100) with action recommendation • Trading Recommendation: Final actionable signal with confidence level Alert Conditions (7 Categories): • 🏢 Stacked Imbalance Alerts : Stacked buy/sell imbalance detection (75-80% win rate) • 💎 Divergence Alerts : RSI/MACD divergence confirmed by imbalance • ⬆️/⬇️ VWAP Alerts : VWAP breakout/breakdown with imbalance confirmation • 🔵/🔴 RSI Extreme Alerts : RSI oversold/overbought with imbalance alignment • 📈/📉 MACD Cross Alerts : MACD golden/death cross with imbalance confirmation • 🧽 Absorption Alerts : Institutional accumulation/distribution detection • 🟢/🔴/⚔️ General Imbalance Alerts : Unidirectional or conflicting imbalance detection █ SIGNAL STRENGTH SCORING Composite Score Calculation (+/- 100): • Buy Imbalance Present: +20 • Stacked Buy Imbalance: +20 • RSI Oversold + Buy Imbalance: +15 • MACD Bullish + Buy Imbalance: +15 • Price Above VWAP + Buy Imbalance: +15 • Buy Absorption: +15 • Sell Imbalance Present: -20 • Stacked Sell Imbalance: -20 • RSI Overbought + Sell Imbalance: -15 • MACD Bearish + Sell Imbalance: -15 • Price Below VWAP + Sell Imbalance: -15 • Sell Absorption: -15 Score Interpretation: • +80 to +100: ⭐⭐⭐ STRONG BUY (Multi-Confirmed) • +50 to +79: 🟢 ACTIVE BUY (Trend Confirmed) • -50 to -79: 🔴 ACTIVE SELL (Trend Confirmed) • -80 to -100: ⭐⭐⭐ STRONG SELL (Multi-Confirmed) • Divergence Confirmed: 💎 Special Signal (Reversal Opportunity) • Absorption Detected: Institutional Activity Signal █ LIMITATIONS • Requires Premium/Ultimate Plan : The request.footprint() function is only available on paid TradingView subscriptions • Real-time Data Only : Footprint data is not available for historical bars on some instruments • Tick Data Dependent : Accuracy depends on broker's tick data quality • Not Suitable for All Markets : Best results on high-volume instruments (forex majors, indices, popular stocks) • Visual Clutter : Multiple visualization layers may overlap on lower timeframes — disable unused features • Repainting : Real-time footprint data updates during bar formation; signals are final on bar close • Max Drawing Objects : Limited to 500 lines, 500 labels, 200 boxes — historical signals will be truncated █ NOTES • Best used on 5-minute to 4-hour timeframes for optimal signal clarity • Combine with support/resistance and trend analysis for confirmation • Stacked Imbalances (3+ layers) have historical 75-80% win rate • Imbalance zones often act as support/resistance after initial move • Divergences + Imbalance signals are more reliable at key market structure levels • Absorption signals are strongest when occurring at known S/R zones • VWAP alignment confirms institutional participation in the direction Recommended Workflow: 1 — Identify market structure and key levels 2 — Check for stacked imbalance signals (3+ layers = high conviction) 3 — Confirm with VWAP position (above = bullish, below = bearish) 4 — Watch for divergence signals at extreme RSI levels 5 — Monitor absorption signals for institutional activity 6 — Use composite score for final entry confirmation Pro Tips: • Stacked buy imbalances at session lows often mark intraday bottoms • Stacked sell imbalances at session highs often mark intraday tops • Conflicting imbalances (both buy and sell) indicate consolidation — wait for breakout • Combine with Volume Profile POC for confluence zones • Use absorption signals to identify institutional entry/exit points ═════════════════════════════════════════════════════════════════════════ For questions or feedback, use comments section below.
Pine Script®指標
由blackcat1402提供
Delta MTF v3 BTC Delta MTF v3 — Enhanced A multi-timeframe delta volume dashboard that measures buying and selling pressure behind every candle using volume delta, intrabar CVD, DV flow, and volume structure analysis. Works on any timeframe combination — set your main TF, sub TF, and trend TF freely to match your trading style. Most indicators react to price after it moves. BTC Delta MTF v3 reads what is happening inside the candle in real time — tracking who controls the volume before the candle closes. Built specifically for BTC scalping and Polymarket UP/DOWN trading. The Problem With Price-Based Indicators RSI, MACD, Bollinger Bands, and most popular indicators are all derived from price. Price is the result of the battle between buyers and sellers — it tells you what already happened. By the time a price-based indicator fires, the move has started, the spread has widened, and you are entering late. Volume tells a different story. Every transaction has two sides. When someone buys, someone else sells. The question is not whether volume is high or low — it is who initiated the transaction. A buyer who crosses the ask is aggressive. A seller who crosses the bid is aggressive. The delta is the net of those two forces: aggressive buying minus aggressive selling. This is the actual engine of price movement, not price itself. elta Volume — The Core Engine In a perfect world, delta would be calculated from tick data: every single transaction tagged as buyer-initiated or seller-initiated at the tape level. TradingView does not provide this for most traders. The indicator approximates it using the High-Low-Close formula: Buy volume = Total Volume × (Close - Low) / (High - Low) Sell volume = Total Volume × (High - Close) / (High - Low) Delta = Buy volume - Sell volume DV Ratio = Buy volume / Total volume → expressed as 0.0 to 1.0 A DV Ratio of 0.70 means 70% of the candle's volume was buyer-initiated. A ratio of 0.30 means sellers dominated. Near 0.50 means balance — a contested candle. The power is not in the absolute number but in the conflict between the ratio and the candle color. A green candle with DV Ratio 0.35 is fundamentally weak — price moved up but sellers were in control of the volume. That candle is a lie. The market will correct it. Hidden Signal — Detecting Institutional Activity Large institutions cannot buy or sell a significant position in a single aggressive order. If they did, they would move the market against themselves. Instead they work orders slowly — buying into selling pressure, selling into buying pressure — deliberately keeping price from moving in their direction while they fill. This creates a specific fingerprint: a candle that moves in one direction while volume flows in the opposite direction. Red candle + DV Ratio > 0.55 → price fell, but buyers controlled volume → Hidden Buy Green candle + DV Ratio < 0.45 → price rose, but sellers controlled volume → Hidden Sell This is not a random noise event. It requires sustained effort over the entire candle duration for a large participant to push price down while quietly absorbing everything the market offers. When this appears in the last minute of a candle at 65%+ buy volume on a red candle, the probability of reversal on the next candle is very high — not because of magic, but because the entity doing this has already positioned itself for exactly that reversal. Absorption — The Volume Trap Absorption is a specific subset of the hidden signal concept but looks at the size of the effort rather than just the direction. The indicator calculates two ratios in real time: Volume spike ratio = Current candle volume / 20-bar SMA of volume Delta flatness = |Net delta| / Total volume (inverted: 1 - this = absorption %) A volume spike of 1.4x with 85% absorption means: volume is 40% above average, and nearly all of it is being absorbed — buyers and sellers are meeting in unusually large size, but neither side is winning. This is the market equivalent of two large forces in equilibrium. When that equilibrium breaks at candle close, the direction of the break is telegraphed by the DV Ratio and the CVD. On 5-minute BTC candles this pattern appears most clearly at support and resistance levels, VWAP touches, and at the end of extended directional moves. It is the institutional footprint of someone defending a position or building one. CVD — Cumulative Volume Delta The Cumulative Volume Delta tracks the running sum of delta across sub-candles within the current bar. It answers: over the entire life of this candle so far, which side has been net aggressive? A candle that opens and immediately shows CVD running positive while price drifts sideways or down is telling you that buyers have been persistently aggressive but have not been rewarded with price — someone is selling into every bid. This is distribution. Conversely, negative CVD with flat or rising price is accumulation. The CVD conflict signal fires when the CVD direction opposes the candle's price movement. The severity is weighted: Strong conflict (CVD fully reversed vs price) → +20 points toward reversal Mild conflict (CVD partially opposing) → +12 points This is distinct from the Hidden Signal because CVD measures the trajectory of delta across time within the candle, while DV Ratio measures the final balance. Together they catch both sudden late-candle institutional activity and sustained multi-minute pressure. Exhaustion — When a Move Runs Out of Fuel Every directional move requires continued aggressive participation to sustain itself. If buyers push price up for 3 minutes but each successive sub-candle shows smaller and smaller net buying delta, the move is decelerating even if price has not yet reflected it. This is delta exhaustion. The indicator tracks sub-candle delta flips — moments when delta switches from positive to negative or vice versa within the candle. A healthy trend has few flips and growing magnitude. An exhausted trend has many flips and shrinking magnitude. When flip count exceeds the threshold (default 3) with declining magnitude, the candle is tagged as exhausted. The theory is grounded in order flow: the buyers who wanted to buy have bought. The remaining participants are not adding to the move — they are waiting. Without new aggressive participation, the next candle will either stall or reverse as the other side sees the weakness and acts. VWAP — The Institutional Anchor VWAP (Volume Weighted Average Price) is not a retail indicator. It is the benchmark that institutional execution desks use to measure trade quality. A fund buying 10,000 BTC wants to execute at or below the daily VWAP — beating VWAP is how they prove their execution was good. This creates a self-fulfilling gravitational pull. Price above VWAP means the average participant who traded today is profitable — there is latent selling pressure from those looking to exit at a gain. Price below VWAP means the average participant is underwater — there is support from those averaging down or defending positions. The stretch signal fires when price is significantly away from VWAP against the candle direction. This combination — price already extended, candle moving further away, volume opposing — is one of the highest probability reversal setups available on a 5-minute chart. The Next Candle Prediction — Putting It Together The prediction score combines all seven factors into a single 0–100% probability. The phase multiplier is critical: early in the candle, the score is deliberately pulled toward 50% because there is insufficient evidence. As the candle matures and more sub-candle data accumulates, the multiplier increases toward 1.0 and the score reflects the full weight of all factors. Phase multiplier = max(0.4, candle_phase_pct / 100) Scaled score = 50 + (raw_score × 0.5 × phase_multiplier) At 40% through the candle, even a perfect signal is suppressed toward 50%. At 80%+, the full score is expressed. This is intentional — it mirrors how a skilled order flow trader thinks. You do not commit to a directional bias in the first minute of a 5-minute candle. You wait for evidence to accumulate. The last minute is when the picture is clearest and the entry timing for the next candle is most actionable.
Pine Script®指標
由RafaelZioni提供
1
Premium / Discount ZonesPremium and Discount Zones This indicator visualizes Premium, Discount, and Equilibrium areas based on a rolling price range calculated from the highest high and lowest low over a user-defined lookback period. The script is designed as a chart-structuring tool. Its purpose is to help traders see where current price is positioned inside a recent range, using three simple zones: - Premium zone: upper part of the range - Discount zone: lower part of the range - Equilibrium zone: middle area of the range What the script does The indicator continuously measures the highest high and lowest low over the selected Range Length. Once that range is established, it divides the full range into three visually distinct areas: - Premium - Equilibrium - Discount These zones are then drawn directly on the chart as dynamic boxes that update as the rolling range changes. How it works 1. Range calculation The script looks back over the selected number of bars and finds: - the highest high of the range - the lowest low of the range These two values define the active trading range used by the indicator. 2. Premium zone The Premium zone is calculated near the top of the range. It represents the upper pricing area relative to the current measured range. 3. Discount zone The Discount zone is calculated near the bottom of the range. It represents the lower pricing area relative to the same measured range. 4. Equilibrium zone The Equilibrium zone is plotted around the midpoint of the range. Instead of using only a single middle line, the script creates a narrow middle band to make the equilibrium area easier to visualize on the chart. 5. Dynamic updates As new candles form, the highest and lowest values of the selected rolling window may change. When that happens, the boxes are deleted and redrawn so that the zones always reflect the most recent active range. Why this script can be useful This script can help traders organize chart context by showing whether price is trading in the upper, middle, or lower section of a recent range. Possible use cases include: - identifying whether price is extended toward the top of a recent range, - identifying whether price is trading at relatively lower range levels, - visualizing a midpoint area for balance or reversion analysis, - combining the zones with a separate market structure, trend, liquidity, or confirmation model. The script does not generate direct buy or sell signals by itself. It is intended as a visual framework for price location within a defined range. Inputs - Range Length (bars): Defines how many bars are used to build the rolling high-low range. - Style: Allows switching between Colored and Monochrome display modes. - Premium Color: Sets the box color for the Premium area in colored mode. - Equilibrium Color: Sets the box color for the Equilibrium area in colored mode. - Discount Color: Sets the box color for the Discount area in colored mode. - Show Labels: Shows or hides the Premium, Discount, and Equilibrium labels on the chart. Visual logic - Premium is displayed at the upper section of the active range. - Discount is displayed at the lower section of the active range. - Equilibrium is displayed around the center of the range. - The zones extend across the currently measured lookback window. How to use it - Increase Range Length if you want wider and slower-moving zones. - Decrease Range Length if you want the zones to react faster to recent price changes. - Use Colored mode for stronger visual separation. - Use Monochrome mode for a cleaner chart appearance. - Combine the zones with your own analysis method if you want entry confirmation. Notes - This script is range-based, not prediction-based. - The zones are recalculated from the recent rolling high-low structure. - Because the range is dynamic, the boxes can shift when new highs or lows appear inside the selected lookback period. - This tool is intended for chart analysis and visual reference.
Pine Script®指標
由trade_w_samet提供
Whale System: Volume Tunnel & Delta Aggression (V5)The Whale System: Volume Tunnel is an advanced order flow visualization tool designed to identify institutional liquidity zones and real-time market aggression. By combining a historical Volume Profile with a dynamic Delta Summary, it allows traders to see not only where the price is likely to react but also the strength of the buyers or sellers at those specific levels. Key Components * EMA 450 (The Trend Filter): Acts as the ultimate "Whale Line." It defines the long-term trend direction and serves as a major dynamic support or resistance level. * Volume Profile (The Grey Tunnel): Displays total traded volume per price level over a specified lookback period. Long bars represent High Volume Nodes (HVN), indicating where institutions have established positions. * Dynamic Delta Summary (The Color Bars): Visualizes the percentage of market aggression. * Green Bars: Dominance of market buy orders (Aggressive Buying). * Red Bars: Dominance of market sell orders (Aggressive Selling). * Dynamic Scaling: The length of the bar is proportional to the percentage (e.g., an 85% bar is significantly longer than a 30% bar), highlighting "climax" zones. * Whale POC (Point of Control): A dashed yellow line highlighting the single price level with the highest total volume. This is the "Fair Value" zone where major players are most active. How to Read the Signals 1. Supply & Demand Walls: Look for long grey bars (Volume Profile) that align with high Delta percentages (>60%). These "Order Flow Tunnels" act as heavy barriers where price typically bounces or consolidates. 2. Institutional Absorption: If the price approaches a major resistance and you see a 100% Red Delta bar that fails to push the price lower, it indicates that a "Whale" is absorbing all sell orders, often leading to a sharp reversal. 3. Trend Confirmation: When price is above the EMA 450 and bounces off the Whale POC with a strong green Delta, it confirms a high-probability "Buy" setup. Technical Settings * Lookback Period: Customizable range to analyze historical volume. * Panel Offset: Adjustable horizontal positioning to keep the workspace clean and prevent overlapping with price candles. * Delta Precision: Calculated as a ratio of (Bull Volume - Bear Volume) / Total Volume, providing a pure reflection of market sentiment.
Pine Script®指標
由Jarass1080提供
Tick Asymmetry Index [DAFE]Tick Asymmetry Index Overview Tick Asymmetry Index (TAI) is a market imbalance oscillator designed to quantify the distribution of aggressive buying versus aggressive selling inside each bar. It combines tick‑level estimation, volume weighting, momentum, acceleration, divergence detection, and optional footprint data into a unified pressure model. TAI does not predict price. It measures structural imbalance and internal auction dynamics. 1. Core Tick Estimation Engine TAI estimates the ratio of buy‑side to sell‑side participation using one of five selectable methods: • Footprint (Real) — uses buy_volume / sell_volume when available • Close Position — relative close within bar range • Wick Analysis — upper/lower wick structure • Multi‑Factor — blend of close position, open/close bias, and trend • OHLC Sequence — sequence‑based directional bias If footprint data is enabled but unavailable from the data feed, the engine automatically falls back to proxy estimation. Functionality is preserved. The base oscillator is calculated as: TAI = Σ(weighted tick ratios) / Σ(weights) × 100 Volume weighting is optional. 2. Momentum & Acceleration Layer TAI computes: • Momentum = ΔTAI over lookback • Acceleration = ΔMomentum • Z‑score normalization of both This allows detection of: • Building imbalance • Deceleration before reversal • Statistically extreme displacement Momentum alignment can optionally be required for signals. 3. HFT & Liquidity Detection A composite score detects high‑frequency microstructure activity by analyzing: • Directional flip frequency • Volume spikes relative to price impact • Spread proxy (Corwin–Schultz estimator) High Z‑score values indicate abnormal short‑term liquidity distortion. This is an environmental signal, not a trade trigger by itself. 4. Divergence & Exhaustion Engine TAI compares price momentum to internal imbalance momentum. Divergence occurs when: • Price rises but imbalance weakens • Price falls but imbalance strengthens Exhaustion detection considers: • Extreme oscillator levels • Momentum Z‑score extremes • Acceleration reversal • Absorption patterns A composite reversal probability score (0–100) summarizes multi‑factor reversal risk. 5. Footprint Integration (Optional) When footprint data is available: • True delta (buy − sell volume) • Buy volume percentage • Value Area behavior are used directly. If footprint data is unavailable, proxy logic estimates imbalance using OHLC and volume distribution. The engine automatically detects and adapts to data availability. 6. Signal Filtering Controls Signal strictness modes allow filtering by structural context: • Loose — any qualifying condition • Standard — requires midline alignment • Strict — requires oversold/overbought zone Optional acceleration alignment can further restrict signals. This prevents raw oscillator crossings from triggering low‑quality entries. 7. Visualization Modes Four lower‑pane visualization engines are available: Footprint Battle Normalized buy vs sell columns around equilibrium (50 line). Quantum Vortex Adaptive volatility bands around smoothed TAI basis. Neon Pulse Momentum histogram representation. Aura Ribbon Dynamic ribbon scaled by acceleration magnitude. The core TAI line and event markers remain visible in all modes. 8. Dashboard The dashboard displays: • Current TAI value • Momentum Z‑score • HFT activity status • Divergence detection • Footprint delta (if available) • Absorption detection • Reversal probability • Signal state Dashboard placement can be set to chart overlay or indicator panel. Signal Logic Signals trigger when: • Divergence, exhaustion, absorption, or reversal probability conditions align • Momentum shifts in the expected direction • Strictness filter conditions are satisfied • Acceleration alignment (if enabled) agrees Signals represent structural imbalance shifts, not guaranteed reversals. Important Notes • Footprint features require supported exchange data. • Proxy mode automatically activates if footprint data is unavailable. • No slippage, commission, or execution modeling is included. • HFT detection and absorption flags are statistical indicators. • This indicator does not guarantee profitability. Past performance does not guarantee future results. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script®指標
由DskyzInvestments提供
VWAP Z-Score & Exhaustion Matrix [AlgoPoint]AlgoPoint VWAP Z-Score & Order Flow Matrix Overview The AlgoPoint VWAP Z-Score Matrix is a quantitative oscillator designed to identify statistical extremes in price action relative to a dynamic volume-weighted baseline. By combining a Rolling VWAP, Volume-Weighted Standard Deviation, Volume Exhaustion, and an Intrabar Order Flow Delta proxy, this indicator provides a comprehensive framework for modeling mean-reversion (fade) setups. Mathematical Core & Components This indicator relies on three primary quantitative mechanics:Rolling VWAP & Z-Score: Unlike a traditional anchored VWAP that resets daily, this script calculates a Rolling VWAP over a user-defined lookback window. The standard deviation is volume-weighted, ensuring that high-volume nodes have a proportional impact on the variance. The Z-Score normalizes the price deviation from the VWAP, creating a 0-centered oscillator. - Volume Exhaustion: The script compares the current bar's volume against a Simple Moving Average (SMA) of volume. If the current volume is lower than the average, it flags a state of "exhaustion," indicating a potential deceleration in the current price push. - Order Flow Delta Proxy: To evaluate microstructure without requiring lower timeframe data, the indicator estimates intrabar buying and selling pressure. It apportions the total bar volume into "Up Volume" and "Down Volume" based on where the close occurs relative to the high-low range. The net difference establishes the Volume Delta. Visual Elements & Interpretation Dual-Gradient Bar Coloring: The main chart candles and the oscillator line are dynamically colored using a dual-gradient system. The color smoothly transitions from a neutral gray at the mean (0) to green at negative extremes and red at positive extremes. Reference Thresholds: Default extreme limits are set at +2.5 and -2.5 Z-Scores.Exhaustion Nodes: Circular nodes appear on the oscillator line when the price reaches an extreme Z-Score simultaneously with volume exhaustion. Quant Dashboard: A real-time table displaying the current Z-Score, Volume Status (Active/Exhausted), Order Flow Delta (Net Buyers/Sellers), and the absolute Rolling VWAP price. Signal Generation "Fade Long" and "Fade Short" labels are generated only when all structural conditions are met and the bar is confirmed (barstate.isconfirmed) Fade Short: Z-Score > Upper Threshold AND Volume is Exhausted AND Delta is Negative (Sellers taking control). Fade Long: Z-Score < Lower Threshold AND Volume is Exhausted AND Delta is Positive (Buyers taking control). Alerts The indicator includes standard alert conditions and dynamic JSON webhook strings for automated trading systems, providing real-time data on the asset, price, Z-Score, and Delta values upon signal generation.
Pine Script®指標
由Iamalala提供
1
Effort & Result [UAlgo]Effort & Result is a volume spread relationship oscillator inspired by the classic idea that market effort and market result do not always move in balance. The script compares how unusual current volume is versus how unusual current price range is, then measures the gap between those two conditions. The result is a compact oscillator that helps reveal whether the market is showing heavy participation with limited progress, or strong price expansion with relatively weak participation. The core concept is simple. Volume represents effort, while true range represents result. When effort rises much faster than result, the market may be meeting opposing liquidity and progress can become inefficient. When result rises much faster than effort, price may be moving through thinner liquidity with relatively little resistance. This script transforms that relationship into standardized values so both dimensions can be compared on the same scale. To make the comparison more useful, the script converts both volume and true range into rolling z scores. That means each bar is judged relative to its own recent context rather than by raw magnitude alone. A large volume bar may not mean much in a market that always trades large volume, while the same raw value could be highly unusual in another market. The same logic applies to price range. By standardizing both series, the indicator focuses on anomaly versus normal behavior rather than on absolute size. The final oscillator is the difference between effort z score and result z score. Positive readings suggest effort is leading result, while negative readings suggest result is leading effort. The script also highlights two special regimes. Absorption appears when effort is strongly positive but result remains weak. Vacuum appears when result is strongly positive but effort remains weak. These conditions are then labeled directly on the oscillator. In practical use, the indicator can help identify hidden resistance to price movement, low liquidity expansion, or moments where market participation and delivered movement are out of balance. It is best used as a context tool rather than a standalone entry engine. 🔹 Features 🔸 Effort Versus Result Framework The script separates market behavior into two dimensions. Volume is treated as effort, and true range is treated as result. This creates a clean and intuitive model for comparing participation versus delivered movement. 🔸 Rolling Z Score Standardization Both effort and result are transformed into rolling z scores over the selected lookback window. This makes the oscillator adaptive to the recent environment and allows direct comparison between volume and range. 🔸 Delta Oscillator The final plotted value is the difference between effort z score and result z score. This gives the user a direct read on whether volume is leading range or range is leading volume. 🔸 Absorption Detection When effort is strongly positive but result is weak or negative, the script flags absorption. This can indicate that strong participation is being met by opposing liquidity and price progress is being contained. 🔸 Vacuum Detection When result is strongly positive but effort is weak or negative, the script flags a vacuum condition. This can indicate that price is moving through thin liquidity with little resistance. 🔸 Context Aware Histogram Coloring The histogram changes color depending on whether the bar reflects absorption, vacuum, or neutral conditions. This makes regime identification faster and more visual. 🔸 Threshold Guides The oscillator includes reference lines for equilibrium as well as absorption and vacuum alert thresholds, making it easier to interpret extremes. 🔸 Direct Chart Labels Special conditions are labeled directly on the oscillator so absorption and vacuum events stand out immediately without requiring separate scanning. 🔹 Calculations 1) Defining the Flow Metrics Container type FlowMetrics float totalVol float spread float effortZ float resultZ This object stores the four main values used by the indicator. totalVol stores the current bar volume. spread stores the current bar range measure. effortZ stores the standardized effort reading. resultZ stores the standardized result reading. So before any signal logic is built, the script already has a clean structure for the raw inputs and their normalized forms. 2) Measuring Effort and Result Inputs float v = nz(volume, 1) float tr = ta.tr(true) This block defines the two core raw inputs of the indicator. v is the current volume, with a fallback of 1 in case the symbol does not provide volume data. tr is the true range of the bar, which is used as the result measure. The reason true range is used instead of a simpler high minus low calculation is that true range also accounts for gaps relative to the prior close. This makes it a more complete measure of actual delivered price movement. So the indicator begins with one participation variable and one movement variable. 3) Rolling Mean and Standard Deviation for Effort float volMean = ta.sma(vol, len) float volStd = ta.stdev(vol, len) this.effortZ := volStd == 0 ? 0 : (vol - volMean) / volStd This is the effort standardization step. The script first computes the rolling average volume over the chosen window. Then it computes the rolling volume standard deviation over the same window. Finally, it converts the current volume into a z score: effortZ = (current volume minus mean volume) divided by volume standard deviation This means: a positive effort z score implies current volume is above normal, a negative effort z score implies current volume is below normal, and zero means current volume is near its rolling average. So effort is not judged by raw volume alone. It is judged by how unusual that volume is relative to recent history. 4) Safe Spread Handling for Result Calculation float safeSpread = r == 0 ? syminfo.mintick : r This line prevents division and standardization issues when the range is zero. If the current true range is zero, the script substitutes the instrument’s minimum tick size instead. This ensures that the result side of the calculation always has a valid positive value and avoids unstable behavior in rare flat bars. So the script remains numerically stable even when a bar has no measurable range. 5) Rolling Mean and Standard Deviation for Result float spreadMean = ta.sma(safeSpread, len) float spreadStd = ta.stdev(safeSpread, len) this.resultZ := spreadStd == 0 ? 0 : (safeSpread - spreadMean) / spreadStd This is the result standardization step. Just like effort, the script calculates the rolling average and rolling standard deviation for the bar spread. It then converts the current spread into a z score: resultZ = (current spread minus mean spread) divided by spread standard deviation This means: a positive result z score implies current movement is above normal, a negative result z score implies current movement is below normal. So result becomes directly comparable to effort on the same statistical scale. 6) Full Metric Calculation Method method calcMetrics(FlowMetrics this, float vol, float r, int len) => this.totalVol := vol this.spread := r float volMean = ta.sma(vol, len) float volStd = ta.stdev(vol, len) this.effortZ := volStd == 0 ? 0 : (vol - volMean) / volStd float safeSpread = r == 0 ? syminfo.mintick : r float spreadMean = ta.sma(safeSpread, len) float spreadStd = ta.stdev(safeSpread, len) this.resultZ := spreadStd == 0 ? 0 : (safeSpread - spreadMean) / spreadStd This method combines the full effort and result workflow into one place. It first stores the raw bar volume and raw spread. Then it calculates the effort z score from rolling volume statistics and the result z score from rolling spread statistics. So each bar receives: a raw effort reading, a raw result reading, a normalized effort score, and a normalized result score. This normalized pair is what the rest of the oscillator uses. 7) Building the Main Oscillator Value FlowMetrics flow = FlowMetrics.new() flow.calcMetrics(v, tr, length) float deltaZ = flow.effortZ - flow.resultZ This is the main oscillator formula. After the metrics object is updated, the script computes: deltaZ = effortZ minus resultZ This value answers the central question of the indicator: is effort stronger than result, or is result stronger than effort? If deltaZ is positive, effort is outrunning result. If deltaZ is negative, result is outrunning effort. If deltaZ is near zero, effort and result are more balanced. So the oscillator is really a normalized imbalance measure between participation and delivered movement. 8) Absorption Condition bool isAbsorption = flow.effortZ > 1.5 and flow.resultZ < 0.0 This is the first special regime filter. Absorption is defined as: effort significantly above normal, while result remains weak. The threshold 1.5 means effort must be at least 1.5 standard deviations above its rolling average. At the same time, result must still be below zero, meaning current movement is not even above its recent average. This combination suggests that strong participation is entering the market but price is not expanding proportionally. That can imply opposing liquidity, passive absorption, or resistance to movement. So absorption is the classic high effort, low result condition. 9) Vacuum Condition bool isVacuum = flow.resultZ > 1.5 and flow.effortZ < 0.0 This is the second special regime filter. Vacuum is defined as: result significantly above normal, while effort remains weak. Here, price is delivering unusually large movement, but volume is not confirming that move with above average participation. This can imply thin liquidity, poor resistance, or fast movement through lightly traded space. So vacuum is the classic low effort, high result condition. 10) Histogram Color Logic color histColor = isAbsorption ? color.new(color.fuchsia, 30) : isVacuum ? (close >= open ? color.new(color.aqua, 30) : color.new(color.orange, 30)) : color.new(color.gray, 70) This block determines how the histogram is colored. If the current bar meets the absorption condition, the histogram is colored fuchsia. If it meets the vacuum condition, the histogram is colored aqua when the candle is bullish and orange when the candle is bearish. If neither special regime is active, the histogram is colored neutral gray. So the visual layer helps the user distinguish ordinary imbalance readings from the two emphasized special states. 11) Plotting the Oscillator plot(deltaZ, "Effort/Result Delta", style=plot.style_columns, color=histColor) This line plots the main effort versus result delta as a column histogram. The use of columns is helpful because it emphasizes relative magnitude and direction around the zero line. Positive columns show effort leading result. Negative columns show result leading effort. So the visual output is both directional and strength sensitive. 12) Threshold and Equilibrium Lines hline(1.5, "Vacuum Alert", color=color.new(color.aqua, 50), linestyle=hline.style_dashed) hline(-1.5, "Absorption Alert", color=color.new(color.fuchsia, 50), linestyle=hline.style_dashed) hline(0, "Equilibrium", color=color.new(color.gray, 50)) These reference lines give the oscillator context. The zero line marks equilibrium, where effort and result are more balanced. The positive 1.5 line acts as a visual vacuum threshold. The negative 1.5 line acts as a visual absorption threshold. These levels do not define the regime conditions directly by themselves, because the actual logic checks the separate effort and result z scores. But they still give the user a useful visual frame for interpreting the size of the delta reading. 13) Labeling Absorption Events if isAbsorption label.new(bar_index, deltaZ, text="Absorbed", color=color.new(color.fuchsia, 100), textcolor=color.fuchsia, style=label.style_none, size=size.small, yloc=yloc.price) When an absorption condition is detected, the script prints an Absorbed label directly at the oscillator value for that bar. This makes the event easier to spot when scanning history and also helps separate truly qualified absorption conditions from merely positive delta readings. So the label is not attached to every strong positive bar, only to the bars that meet the specific high effort and weak result rule. 14) Labeling Vacuum Events if isVacuum label.new(bar_index, deltaZ, text="Vacuum", color=color.new(color.aqua, 100), textcolor=color.aqua, style=label.style_none, size=size.small, yloc=yloc.price) This block does the same for vacuum events. When a bar shows unusually strong range with weak volume participation, the script prints a Vacuum label at the oscillator level. So the chart distinguishes not only statistical imbalance in general, but specifically the regime where result is outrunning effort.
Pine Script®指標
由UAlgo提供
Initial Balance - Olly Watts This indicator converts the Initial Balance (IB) into a dynamic Fibonacci-style retracement framework for intraday trading. It detects the first hour range automatically, identifies the first wick breakout, and then plots retracement levels from the breakout side. This creates a clear structure for pullbacks, continuation trades, and range expansions. The indicator also includes optional IB expansion levels for projecting potential targets beyond the opening range. Designed for traders who use opening range and initial balance concepts to structure intraday price action.
Pine Script®指標
由wattsolly提供
2
Lumina Trend Channels [Pineify]Lumina Trend Channels The Lumina Trend Channels is a dynamic, volatility-adaptive channel system that combines an Exponential Moving Average (EMA) baseline with Average True Range (ATR) band projections and slope-based trend detection to create a visually intuitive, all-in-one trend-following overlay. Unlike static channel indicators that use fixed-width bands, Lumina Trend Channels automatically expands and contracts its four-band envelope in real time as market volatility changes, keeping the channel structure relevant across all market conditions. The channel color shifts between bullish and bearish states based on the direction of the baseline slope, and buy/sell signals are generated only when price crosses the baseline in alignment with the confirmed trend — filtering out counter-trend noise and providing cleaner entry timing for trend traders. Key Features EMA baseline with ATR-scaled bands — a responsive center line surrounded by four symmetrical bands whose width adapts dynamically to current volatility via ATR measurement. Slope-based trend detection — trend direction is determined by whether the EMA baseline has risen or fallen for two consecutive bars, providing a simple yet effective trend filter. Trend-aligned buy/sell signals — BUY signals trigger only when price crosses above the baseline during a confirmed uptrend; SELL signals trigger only during a confirmed downtrend, eliminating counter-trend false entries. Gradient-style visual channel — layered fills with progressive transparency create a glowing channel effect that fades outward from the baseline, making trend direction and volatility state immediately visible. Trend change markers — circle markers appear on the baseline at the exact bar where the trend flips, providing clear visual anchors for regime changes. Built-in alert conditions — configurable alerts for buy signals, sell signals, and trend changes for hands-free monitoring. How It Works The indicator follows a three-stage calculation process to construct the channel and generate signals: Baseline calculation via EMA: The closing price is smoothed using an Exponential Moving Average with a configurable period (default: 21). The EMA was chosen over SMA because it assigns greater weight to recent prices, producing a center line that reacts faster to price changes while maintaining smoothness. This baseline serves as both the channel center and the reference line for signal generation. Volatility measurement via ATR: The Average True Range is calculated over the same lookback period as the EMA. ATR measures the average bar range (accounting for gaps), providing a robust volatility metric. Four bands are then projected symmetrically around the baseline: inner bands at basis ± ATR × inner multiplier (default: 1.0) and outer bands at basis ± ATR × outer multiplier (default: 2.0). As volatility expands, the bands widen; as it contracts, they narrow — keeping the channel proportional to actual market conditions. Trend detection via baseline slope: The trend state is determined by checking whether the EMA baseline has been rising (increasing for 2 consecutive bars) or falling (decreasing for 2 consecutive bars). If rising, the trend is set to bullish; if falling, bearish. If neither condition is met, the previous trend state is maintained. This persistence mechanism prevents rapid trend flipping during sideways consolidation. Trading Ideas and Insights The Lumina Trend Channels is designed to serve multiple trading approaches across different timeframes and markets: Trend-following entries: The primary use case — when a BUY triangle appears below a bar, it means price has crossed above the EMA baseline while the channel is green (bullish). This confirms that the immediate price action and the broader trend are aligned. Enter long and consider the upper inner or outer band as a potential profit target. The SELL triangle is the mirror setup for short entries during bearish channels. Volatility-based position sizing: The ATR-driven band width provides a built-in volatility gauge. When the channel is wide, the market is volatile — consider smaller position sizes or wider stops. When the channel is narrow, volatility is compressed — tighter stops may be appropriate, and a breakout from the narrow channel often precedes a strong directional move. Dynamic support and resistance: The inner and outer bands act as dynamic support/resistance levels. In an uptrend, pullbacks to the lower inner band often find support; in a downtrend, rallies to the upper inner band often meet resistance. The outer bands represent extreme volatility extensions where price is statistically stretched. Trend change detection: The circle markers on the baseline highlight the exact moment the trend flips. These are valuable for swing traders who want to exit positions when the trend turns against them, or for traders looking to enter early in a new trend direction. How Multiple Indicators Work Together The Lumina Trend Channels integrates three technical components into a unified system, each serving a distinct analytical role: Exponential Moving Average (trend center): The EMA provides the structural backbone of the channel. It defines the center line around which all bands are constructed and serves as the crossover reference for signal generation. Its low-lag property ensures the channel tracks price closely, keeping the entire system responsive to current market conditions. Average True Range (volatility scaling): ATR transforms the channel from a fixed-width envelope into a volatility-adaptive one. By scaling band distances with ATR, the channel automatically adjusts to the market's current behavior — wide during volatile periods, narrow during quiet ones. This means the bands always represent statistically meaningful distance from the baseline, regardless of the instrument or timeframe. Slope-based trend filter (directional bias): The trend detection layer adds a directional gate to the entire system. Without it, every EMA crossover would generate a signal — including counter-trend ones during choppy markets. By requiring the baseline to be actively rising (for buys) or falling (for sells), the trend filter ensures signals only fire when the broader directional context supports the trade. The synergy is layered: EMA establishes the trend center → ATR scales the channel to current volatility → slope detection determines the trend state → signals fire only when price action and trend direction agree. This multi-layer filtering produces a system where each component reinforces the others, resulting in higher-conviction signals than any single component could provide alone. Unique Aspects Volatility-adaptive channel with trend coloring: While many channel indicators use either fixed bands (like Bollinger Bands with standard deviation) or trend coloring separately, Lumina Trend Channels combines ATR-driven dynamic width with slope-based trend coloring in a single overlay. The result is a channel that communicates both volatility state and trend direction simultaneously through its shape and color. Gradient transparency design: The four-layer fill system uses progressive transparency — inner zones are more opaque, outer zones more transparent — creating a natural visual gradient that draws the eye toward the baseline. This design choice makes it immediately obvious where the channel center is and how far price has extended from it. Trend-gated signals: Rather than generating signals on every baseline crossover, the indicator requires trend confirmation before triggering entries. This simple but effective filter dramatically reduces false signals during sideways or transitional market phases, where most crossover-based systems struggle. Minimal parameter design: With only three calculation inputs (length, outer multiplier, inner multiplier), the indicator avoids over-parameterization. The single length parameter controls both the EMA and ATR simultaneously, ensuring the baseline and volatility measure are always in sync. How to Use Add the indicator to your chart. It overlays directly on the price chart, displaying a four-band channel with a central baseline, all colored according to the current trend direction. Observe the channel color: green indicates a bullish trend (baseline is rising), red indicates a bearish trend (baseline is falling). Trade in the direction of the channel color for higher-probability setups. Watch for BUY triangles (green, below bars) — these appear when price crosses above the baseline during a confirmed uptrend. Consider entering long with a stop below the lower inner or outer band. Watch for SELL triangles (red, above bars) — these appear when price crosses below the baseline during a confirmed downtrend. Consider entering short with a stop above the upper inner or outer band. Use the circle markers on the baseline to identify trend changes. These mark the exact bar where the channel flipped color, useful for timing exits or preparing for new trend entries. Monitor the channel width as a volatility gauge — wide channels mean high volatility, narrow channels mean low volatility and potential breakout setups. Set up alerts using the built-in alert conditions for buy signals, sell signals, and trend changes to automate your monitoring. Customization Channel Length (default: 21): Controls both the EMA baseline period and the ATR lookback. Lower values (e.g., 10–14) make the channel more responsive and generate more signals, suitable for shorter timeframes or scalping. Higher values (e.g., 34–55) produce a smoother, more stable channel for swing trading or higher timeframes. Outer Band Multiplier (default: 2.0): Scales the distance of the outer bands from the baseline. Increase for wider outer bands that capture more extreme price extensions; decrease for tighter outer bands that stay closer to price action. Inner Band Multiplier (default: 1.0): Scales the distance of the inner bands from the baseline. Adjust to control the width of the inner channel zone. A value of 0.5 creates a narrow inner zone; a value of 1.5 widens it. Bullish Color (default: green): The color applied to all channel elements during uptrends. Customize to match your chart theme. Bearish Color (default: red): The color applied to all channel elements during downtrends. Customize to match your chart theme. Conclusion The Lumina Trend Channels delivers a clean, volatility-adaptive channel overlay that combines EMA-based trend tracking, ATR-driven dynamic band scaling, and slope-based trend detection into a single, cohesive indicator. Its gradient-style visual design provides immediate, at-a-glance understanding of trend direction, volatility state, and price position within the channel. By gating buy and sell signals with trend confirmation, the indicator filters out counter-trend noise and delivers higher-conviction entries aligned with the prevailing market direction. Whether you trade stocks, forex, crypto, or futures, the Lumina Trend Channels adapts to your instrument and timeframe, offering a refined approach to trend-following and volatility-aware trading decisions.
Pine Script®指標
由Pineify提供
SMT Divergence [UAlgo]SMT Divergence is a comparative market structure indicator designed to detect disagreement between a primary instrument and a second reference symbol. The script looks for situations where the main chart prints a stronger structural move, while the comparison symbol fails to confirm that move. This kind of disagreement is often referred to as SMT divergence and is commonly used to identify potential weakness in continuation or hidden strength into reversal conditions. The script works by tracking confirmed swing highs and swing lows on both instruments. Once enough pivots are stored, it compares the latest structural movement in the primary chart against the latest comparable movement in the reference symbol. If the primary chart makes a lower low while the comparison symbol makes a higher low, the script identifies bullish SMT divergence. If the primary chart makes a higher high while the comparison symbol makes a lower high, the script identifies bearish SMT divergence. What makes this script especially practical is its flexible comparison logic. It can work in a time matched mode, where the comparison swings must occur near the same bars as the primary swings, or in an independent mode, where the script simply uses the most recent valid swings from both instruments. It also supports inverse correlation logic, allowing the user to compare instruments that normally move in opposite directions. The indicator can then display SMT labels directly on the main chart, draw structure lines between the relevant swing points, show a live information table, and optionally render the comparison symbol as candles inside the oscillator pane. This creates a complete workflow for divergence monitoring instead of only printing occasional labels. In practical use, SMT Divergence can help traders identify moments when the primary symbol appears to be making an aggressive structural move without proper confirmation from a related market. These moments can provide useful context for potential exhaustion, liquidity events, or directional imbalance between correlated instruments. 🔹 Features 🔸 Dual Symbol Market Structure Comparison The script compares the active chart against a second user selected symbol. Both instruments are processed using the same pivot logic, which creates a consistent framework for structural comparison. 🔸 Bullish SMT Detection Bullish SMT is identified when the primary chart makes a lower low while the comparison symbol makes a higher low. This can suggest hidden relative strength in the comparison instrument or possible exhaustion in the primary one. 🔸 Bearish SMT Detection Bearish SMT is identified when the primary chart makes a higher high while the comparison symbol makes a lower high. This can suggest weakening confirmation and possible vulnerability in the primary move. 🔸 Positive and Inverse Correlation Modes The script supports both normal and inverse correlation logic. In normal mode, lows are compared with lows and highs are compared with highs. In inverse mode, lows are compared with highs and highs are compared with lows. This makes the tool flexible enough for both positively correlated and negatively correlated markets. 🔸 Time Matched and Independent Swing Modes The user can choose whether swing comparison should require approximate time alignment or simply use the most recent valid swings from each symbol. This allows the script to be either stricter or more flexible depending on the relationship between the two markets. 🔸 Pivot Strength Control Swing highs and lows are built from confirmed pivots using user defined left and right bar settings. This allows the user to control how sensitive or how selective the swing structure should be. 🔸 Minimum Price Difference Filter A minimum price difference percentage can be required before a divergence is accepted. This helps avoid labeling very small and potentially insignificant swing differences. 🔸 Max Swing Memory Control The script stores a limited number of recent swings for both the primary and comparison symbol. This keeps the logic focused on relevant structure and prevents unnecessary buildup of stale pivots. 🔸 On Chart Labels and Lines Detected SMT events can be labeled directly on the main chart. The script can also draw structure lines across the primary and comparison swing legs used in the divergence. 🔸 Live Info Table An information table can display the active comparison symbol, correlation mode, divergence count, and the latest signal direction. This makes the script easier to monitor in real time. 🔸 Optional Compare Candle Panel The comparison symbol can be plotted as candles in the indicator pane. This allows the user to visually inspect whether the second instrument is confirming or rejecting the move seen in the primary chart. 🔸 Alert Support The script includes separate alerts for bullish SMT, bearish SMT, and any SMT event. 🔹 Calculations 1) Defining Swing and Divergence Objects type SwingPoint int barIdx int barTm float price bool isHigh type SMTDivergence int barIdx int barTm bool isBullish float primaryPrice float comparePrice string primarySymbol string compareSymbol label lbl line ln1 line ln2 type SymbolData float h float l float c This is the structural base of the whole script. A SwingPoint stores one confirmed pivot with its bar index, time, price, and whether it is a high or a low. An SMTDivergence object stores the final event once a divergence is confirmed. It keeps the primary and comparison prices, the involved symbols, the direction, and the visual references used for labels and lines. A SymbolData object is used as a clean container for each symbol’s high, low, and close series. So before any logic runs, the script already has a full structure for swing storage and divergence output. 2) Requesting the Comparison Symbol Data = request.security(compareSymbolInput, timeframe.period, , lookahead = barmerge.lookahead_off) SymbolData primaryData = SymbolData.new(high, low, close) SymbolData compareData = SymbolData.new(compareHigh, compareLow, compareClose) This block loads the second symbol on the same chart timeframe. The primary chart uses the current symbol’s own high, low, and close. The comparison symbol is requested with request.security , and its values are placed into a matching data structure. This means both symbols are analyzed on an equal timeframe basis, which is essential for consistent swing comparison. 3) Finding Pivot Highs and Pivot Lows on Both Symbols float primaryPivotHigh = ta.pivothigh(primaryData.h, pivotLeftBars, pivotRightBars) float primaryPivotLow = ta.pivotlow(primaryData.l, pivotLeftBars, pivotRightBars) float comparePivotHigh = ta.pivothigh(compareData.h, pivotLeftBars, pivotRightBars) float comparePivotLow = ta.pivotlow(compareData.l, pivotLeftBars, pivotRightBars) This is the swing discovery engine. The script uses the same pivot settings for both instruments. A pivot high or pivot low is only confirmed after the required number of bars has passed on each side. This means the divergence engine is built from confirmed structure, not from temporary highs and lows that can disappear before confirmation. 4) Storing Swings in Memory method addSwing(array swings, SwingPoint newSwing) => swings.push(newSwing) if swings.size() > maxSwingsToStore swings.shift() swings if not na(primaryPivotHigh) primarySwings.addSwing(SwingPoint.new(bar_index - pivotOffset, time , primaryPivotHigh, true)) if not na(primaryPivotLow) primarySwings.addSwing(SwingPoint.new(bar_index - pivotOffset, time , primaryPivotLow, false)) if not na(comparePivotHigh) compareSwings.addSwing(SwingPoint.new(bar_index - pivotOffset, time , comparePivotHigh, true)) if not na(comparePivotLow) compareSwings.addSwing(SwingPoint.new(bar_index - pivotOffset, time , comparePivotLow, false)) Once a pivot is confirmed, it is pushed into the appropriate swing array. The true pivot bar is pivotRightBars bars in the past, so the script subtracts that offset from the current bar index and time. Each array only keeps the latest user defined number of swings. So the script maintains a rolling structural memory for both markets without allowing the arrays to grow indefinitely. 5) Retrieving the Latest and Previous Swings method getLastSwing(array swings, bool isHigh) => SwingPoint result = na if swings.size() > 0 for i = swings.size() - 1 to 0 SwingPoint sw = swings.get(i) if sw.isHigh == isHigh result := sw break result method getPreviousSwing(array swings, bool isHigh) => SwingPoint result = na int count = 0 if swings.size() > 1 for i = swings.size() - 1 to 0 SwingPoint sw = swings.get(i) if sw.isHigh == isHigh count += 1 if count == 2 result := sw break result These two helper methods are used to build the swing pairs required for divergence detection. getLastSwing returns the most recent high or low swing of the requested type. getPreviousSwing returns the swing before that. This is important because SMT logic always compares two consecutive structure points on the primary side and two corresponding structure points on the comparison side. 6) Enforcing Maximum Distance Between Swing Points method isWithinRange(SwingPoint sw1, SwingPoint sw2) => not na(sw1) and not na(sw2) and math.abs(sw1.barIdx - sw2.barIdx) <= maxBarsLookback This method makes sure the two swings being compared are not too far apart in time. If the latest and previous swing are separated by more than the allowed bar distance, the setup is ignored. This helps keep the analysis focused on fresh and structurally related moves rather than comparing swings that are too old or too distant to be meaningful together. 7) Time Matched Swing Search method findSwingNearBar(array swings, int targetBar, bool isHigh, int toleranceBars) => SwingPoint result = na int minDiff = 999999 if swings.size() > 0 for i = swings.size() - 1 to 0 SwingPoint sw = swings.get(i) if sw.isHigh == isHigh int diff = math.abs(sw.barIdx - targetBar) if diff <= toleranceBars and diff < minDiff minDiff := diff result := sw result This method is used only when the user selects time matched mode. The idea is to find a comparison symbol swing that occurred near the same bar as the primary swing. The script searches for the nearest swing of the correct type inside the allowed tolerance window. So time matched mode is stricter because it requires approximate timing alignment between the two instruments. 8) Minimum Price Difference Filter method pctDiff(float price1, float price2) => math.abs(price1 - price2) / ((price1 + price2) / 2) * 100 This function measures the percentage difference between two prices. The result is later used as an optional minimum swing magnitude filter. If the primary chart’s new swing differs only slightly from its previous one, the script can ignore that divergence candidate. So the minimum difference filter helps reduce weaker signals that are based on very small structure changes. 9) Bullish SMT Detection Logic if not na(primaryPivotLow) and not na(primaryLastLow) and not na(primaryPrevLow) SwingPoint usedCompareLast = na SwingPoint usedComparePrev = na bool targetSwingHigh = inverseCorrelation ? true : false if useTimeMatching usedCompareLast := compareSwings.findSwingNearBar(primaryLastLow.barIdx, targetSwingHigh, timeToleranceBars) usedComparePrev := compareSwings.findSwingNearBar(primaryPrevLow.barIdx, targetSwingHigh, timeToleranceBars) else usedCompareLast := compareSwings.getLastSwing(targetSwingHigh) usedComparePrev := compareSwings.getPreviousSwing(targetSwingHigh) This is the setup stage for bullish SMT. The script only begins the test when a new primary pivot low has just been confirmed and both the latest and previous primary lows are available. Then it decides what kind of comparison swings are needed. In normal correlation mode, bullish SMT compares primary lows to comparison lows. In inverse correlation mode, bullish SMT compares primary lows to comparison highs. Then the script either uses time matched lookup or independent swing retrieval depending on the chosen mode. So before the bullish condition itself is tested, the script first builds the proper comparison pair according to both timing mode and correlation mode. 10) Bullish SMT Confirmation Conditions if not na(usedCompareLast) and not na(usedComparePrev) if primaryLastLow.isWithinRange(primaryPrevLow) bool primaryLL = primaryLastLow.price < primaryPrevLow.price bool compareHL = inverseCorrelation ? (usedCompareLast.price < usedComparePrev.price) : (usedCompareLast.price > usedComparePrev.price) bool meetsMinDiff = minPriceDiff == 0.0 or (primaryLastLow.price.pctDiff(primaryPrevLow.price) >= minPriceDiff) Bullish SMT is confirmed when three things happen. First, the primary chart must make a lower low: primaryLastLow.price < primaryPrevLow.price Second, the comparison symbol must fail to confirm that weakness. In normal correlation mode this means the comparison symbol makes a higher low. In inverse correlation mode the logic is adjusted accordingly because the relationship is reversed. Third, if the minimum difference filter is enabled, the primary low must differ enough from the previous low. So bullish SMT is essentially a lower low in the main chart that is not properly confirmed by the comparison market. 11) Creating the Bullish Divergence Event if primaryLL and compareHL and meetsMinDiff and primaryLastLow.barIdx != lastBullPrimaryIdx bullishSMT := true lastBullPrimaryIdx := primaryLastLow.barIdx SMTDivergence newDiv = SMTDivergence.new(primaryLastLow.barIdx, primaryLastLow.barTm, true, primaryLastLow.price, usedCompareLast.price, syminfo.tickerid, compareSymbolInput, na, na, na) newDiv.drawVisuals(primaryPrevLow.barTm, primaryPrevLow.price, usedCompareLast.barTm, usedComparePrev.barTm, usedComparePrev.price) divergences.push(newDiv) Once the bullish conditions are met, the script creates a new SMT divergence object. It stores the primary swing information, the comparison swing information, the involved symbols, and the bullish direction. Then it calls the visual drawing method and pushes the divergence into the history array. The duplicate protection check against lastBullPrimaryIdx prevents the same primary swing from being labeled repeatedly. 12) Bearish SMT Detection Logic if not na(primaryPivotHigh) and not na(primaryLastHigh) and not na(primaryPrevHigh) SwingPoint usedCompareLastH = na SwingPoint usedComparePrevH = na bool targetSwingHigh = inverseCorrelation ? false : true if useTimeMatching usedCompareLastH := compareSwings.findSwingNearBar(primaryLastHigh.barIdx, targetSwingHigh, timeToleranceBars) usedComparePrevH := compareSwings.findSwingNearBar(primaryPrevHigh.barIdx, targetSwingHigh, timeToleranceBars) else usedCompareLastH := compareSwings.getLastSwing(targetSwingHigh) usedComparePrevH := compareSwings.getPreviousSwing(targetSwingHigh) This is the mirror setup stage for bearish SMT. It begins only when a new primary pivot high has been confirmed and the required primary highs exist. Then it selects the proper comparison swing type according to the chosen correlation mode. In normal correlation mode, bearish SMT compares highs with highs. In inverse correlation mode, bearish SMT compares highs with lows. So this block prepares the correct structural pair for the bearish test. 13) Bearish SMT Confirmation Conditions if not na(usedCompareLastH) and not na(usedComparePrevH) if primaryLastHigh.isWithinRange(primaryPrevHigh) bool primaryHH = primaryLastHigh.price > primaryPrevHigh.price bool compareLH = inverseCorrelation ? (usedCompareLastH.price > usedComparePrevH.price) : (usedCompareLastH.price < usedComparePrevH.price) bool meetsMinDiff = minPriceDiff == 0.0 or (primaryLastHigh.price.pctDiff(primaryPrevHigh.price) >= minPriceDiff) Bearish SMT is confirmed when the primary chart makes a higher high while the comparison symbol fails to confirm that strength. In normal correlation mode, the comparison symbol must make a lower high. In inverse correlation mode the logic is adjusted to preserve the intended structural disagreement. The minimum difference filter is applied here as well. So bearish SMT is the opposite structure of bullish SMT, focused on unconfirmed upside continuation. 14) Creating the Bearish Divergence Event if primaryHH and compareLH and meetsMinDiff and primaryLastHigh.barIdx != lastBearPrimaryIdx bearishSMT := true lastBearPrimaryIdx := primaryLastHigh.barIdx SMTDivergence newDiv = SMTDivergence.new(primaryLastHigh.barIdx, primaryLastHigh.barTm, false, primaryLastHigh.price, usedCompareLastH.price, syminfo.tickerid, compareSymbolInput, na, na, na) newDiv.drawVisuals(primaryPrevHigh.barTm, primaryPrevHigh.price, usedCompareLastH.barTm, usedComparePrevH.barTm, usedComparePrevH.price) divergences.push(newDiv) Once the bearish rules are satisfied, the script creates a bearish SMT divergence object, draws its visuals, and stores it in the divergence history array. The duplicate protection check against lastBearPrimaryIdx prevents repeated labeling of the same primary high. 15) Drawing Labels and Lines method drawVisuals(SMTDivergence div, int prevTime, float prevPrice, int compareTime, int prevCompareTime, float prevComparePrice) => if showLabels string labelText = div.isBullish ? "🔺 SMT" : "🔻 SMT" string tooltipText = str.format("{0} SMT Divergence {1} vs {2} Price: {3}", div.isBullish ? "Bullish" : "Bearish", div.primarySymbol, div.compareSymbol, str.tostring(div.primaryPrice, format.mintick)) color labelColor = div.isBullish ? bullishColor : bearishColor div.lbl := label.new(div.barIdx, div.primaryPrice, labelText, xloc = xloc.bar_index, yloc = div.isBullish ? yloc.belowbar : yloc.abovebar, color = labelColor, textcolor = color.white, style = div.isBullish ? label.style_label_up : label.style_label_down, tooltip = tooltipText, size = size.small, force_overlay = true) if showLines and not na(prevTime) and not na(prevPrice) color lineColor = div.isBullish ? bullishColor : bearishColor div.ln1 := line.new(prevTime, prevPrice, div.barTm, div.primaryPrice, xloc = xloc.bar_time, color = lineColor, width = 2, style = line.style_solid, force_overlay = true) if not na(prevComparePrice) and not na(prevCompareTime) and not na(compareTime) div.ln2 := line.new(prevCompareTime, prevComparePrice, compareTime, div.comparePrice, xloc = xloc.bar_time, color = lineColor, width = 2, style = line.style_solid) This method creates the chart visuals for each divergence. The label is placed directly at the primary swing location, above price for bearish SMT and below price for bullish SMT. If line drawing is enabled, the script also draws one line across the primary chart’s two relevant swing points and another line across the comparison symbol’s swing leg. So the user can see both the signal marker and the underlying structural disagreement that produced it. 16) Limiting Divergence History if divergences.size() > maxDivergencesToShow SMTDivergence rmDiv = divergences.shift() rmDiv.cleanup() This block controls object history. If the stored divergence count exceeds the chosen limit, the oldest divergence is removed from the array and all its visuals are deleted. This keeps the chart clean and prevents unlimited buildup of old labels and lines. 17) Building the Information Table var table infoTable = table.new(position.top_right, 2, 6, bgcolor = color.new(#2222b3, 10), border_width = 1, border_color = color.new(color.white, 80), frame_width = 2, frame_color = color.new(color.white, 70)) if showTable and barstate.islast table.cell(infoTable, 0, 1, "Primary", text_color = color.gray, text_size = size.tiny) table.cell(infoTable, 1, 1, syminfo.tickerid, text_color = color.white, text_size = size.tiny) table.cell(infoTable, 0, 2, "Compare", text_color = color.gray, text_size = size.tiny) table.cell(infoTable, 1, 2, compareSymbolInput, text_color = color.white, text_size = size.tiny) table.cell(infoTable, 0, 3, "Correlation", text_color = color.gray, text_size = size.tiny) table.cell(infoTable, 1, 3, inverseCorrelation ? "Inverse" : "Positive", text_color = inverseCorrelation ? color.orange : color.aqua, text_size = size.tiny) table.cell(infoTable, 0, 4, "Divergences", text_color = color.gray, text_size = size.tiny) table.cell(infoTable, 1, 4, str.tostring(divergences.size()), text_color = color.white, text_size = size.tiny) This table provides a compact real time summary. It shows: the primary symbol, the comparison symbol, the current correlation mode, the number of stored divergences, and the most recent signal direction. So the table functions as a monitoring dashboard rather than only a decorative element. 18) Determining the Last Signal for the Table string lastSignal = "None" color signalColor = color.gray if divergences.size() > 0 SMTDivergence lastDiv = divergences.get(divergences.size() - 1) lastSignal := lastDiv.isBullish ? "🔺 Bullish" : "🔻 Bearish" signalColor := lastDiv.isBullish ? bullishColor : bearishColor This block determines what the table should show as the latest signal. If at least one divergence has been stored, the script reads the newest one and displays whether it was bullish or bearish, along with the corresponding color. So the info table always reflects the current state of the divergence history. 19) Alert Conditions alertcondition(bullishSMT, title = "Bullish SMT Divergence", message = "🔺 Bullish SMT Divergence detected on {{ticker}}! Primary made Lower Low while {{interval}} comparison made Higher Low.") alertcondition(bearishSMT, title = "Bearish SMT Divergence", message = "🔻 Bearish SMT Divergence detected on {{ticker}}! Primary made Higher High while {{interval}} comparison made Lower High.") alertcondition(bullishSMT or bearishSMT, title = "Any SMT Divergence", message = "SMT Divergence detected on {{ticker}}!") The script provides three alert types. One triggers only on bullish SMT. One triggers only on bearish SMT. One triggers on any SMT event. This makes the indicator useful both for visual study and for live event monitoring. 20) Compare Candle Panel color compareBodyColor = compareClose >= compareOpen ? color.new(#00E676, 0) : color.new(#FF5252, 0) color compareWickColor = compareClose >= compareOpen ? color.new(#00E676, 30) : color.new(#FF5252, 30) color compareBorderColor = compareClose >= compareOpen ? color.new(#00C853, 0) : color.new(#D50000, 0) plotcandle(compareOpen, compareHigh, compareLow, compareClose, title = "Compare Symbol Candles", color = compareBodyColor, wickcolor = compareWickColor, bordercolor = compareBorderColor, display = showCandlePanel ? display.all : display.none) This block renders the comparison symbol as candles inside the indicator pane. The candle colors are determined by the comparison symbol’s own open and close direction. If the user enables the candle panel, this gives a quick visual reference for how the second instrument is behaving without needing to open a separate chart. So the user can study SMT signals and the comparison structure in the same pane.
Pine Script®指標
由UAlgo提供
Wave Velocity Directional 2.1Wave Velocity Directional 2.1 Wave Velocity Directional 2.1 is an analytical tool designed to evaluate the structural quality of Wave 1 vs Wave 2 using velocity comparison, momentum filtering, and trend alignment. The indicator measures the directional velocity of waves, determines whether the impulse structure is healthy, and adds momentum and trend filters (CCI and EMA200) locked to the end of Wave 2. This helps traders evaluate whether a potential Wave 3 expansion has favorable structural conditions. Core Concept The script compares the velocity of Wave 1 and Wave 2. Velocity is defined as: Directional Range / Number of Bars A strong impulse structure typically shows: Wave 1 faster than Wave 2 Wave 2 slower corrective movement The ratio between the velocities indicates the structural strength of the setup. Velocity Ratio Interpretation Ratio Interpretation > 1.5 Strong impulse 1.2 – 1.5 Healthy structure 1.0 – 1.2 Weak impulse < 1.0 Structural warning This provides a quick diagnostic of whether the market structure behaves like a typical impulse–correction sequence. CCI Filter (Momentum) The indicator evaluates CCI at the exact candle where Wave 2 ends. Rules: Longs are blocked if CCI ≥ Long Max Shorts are blocked if CCI ≤ Short Min Default values: Long Max = 80 Short Min = -80 This prevents entering trades when the market is already overextended. EMA200 Trend Filter The script also checks trend alignment using EMA200. Conditions evaluated at Wave 2 end: LONG allowed if: Close > EMA200 EMA200 is rising SHORT allowed if: Close < EMA200 EMA200 is falling This ensures trades are aligned with the dominant trend. Compact Dashboard The indicator displays a compact table with: Wave 1 velocity Wave 2 velocity Velocity ratio Structural status CCI value at Wave 2 end CCI trade permissions EMA200 value at Wave 2 end Trend-based trade permissions Everything is calculated relative to manually selected wave anchors. How to Use Select the four anchor points: Wave 1 start Wave 1 end Wave 2 start Wave 2 end The indicator automatically calculates: velocity structural ratio momentum condition trend alignment Use the combined signals to evaluate the probability of a Wave 3 continuation. Version 2.1 Improvements Compared to the previous version: Added CCI momentum filter Added EMA200 trend filter Added trade permission status (LONG / SHORT) Improved dashboard diagnostics Important Notes This tool is designed as a structure validation assistant, not a standalone trading system. It is most effective when used together with: wave structure analysis liquidity / imbalance concepts higher timeframe context
Pine Script®指標
由daniv_roman提供
QuantumPips RSI Pro - Strip Overlay QuantumPips RSI Pro - Strip Overlay QuantumPips RSI Pro, Strip Overlay is a momentum visualization tool that places a compact RSI strip directly on the price chart, so you can read overbought/oversold pressure without using a separate lower pane. This indicator is designed to help traders answer three practical questions in real time: Is momentum stretched (OB/OS)? Has momentum reset back inside a level (Reclaim)? Is the current move supported by volume and trend bias (Panel)? What you will see 1) RSI Strip on the chart A mini RSI band is plotted near the bottom of your chart: Red zone = overbought region Green zone = oversold region RSI is highlighted more strongly when it is actually inside those zones. 2) Reclaim markers (main chart) The indicator prints Reclaim↑ and Reclaim↓ labels on your candles: Reclaim↑ (bullish reclaim): RSI dipped into oversold and then reclaimed back above the oversold level. Reclaim↓ (bearish reclaim): RSI pushed into overbought and then reclaimed back below the overbought level. These are not “guaranteed entries.” They are momentum reset events that can be used as confirmation alongside your own structure, support/resistance, or session strategy. 3) Side panel (quick decision dashboard) The top-right panel summarizes the current state: Overbought (Yes/No) Oversold (Yes/No) Reclaim: Up / Down / None Volume: High / Normal (based on volume vs its moving average) Trend Bias: Bull / Bear / Flat (EMA-based, optional) The goal is to reduce hesitation and make the “market condition” easy to read quickly. How to use it A simple workflow: Look at the strip If RSI is deep in green, price may be stretched down (watch for recovery). If RSI is deep in red, price may be stretched up (watch for cooling). Wait for a reclaim Reclaim↑ suggests momentum is recovering from oversold. Reclaim↓ suggests momentum is cooling from overbought. Use the panel for confluence If reclaim aligns with Trend Bias and Volume, it often becomes a cleaner setup environment. If reclaim fights the trend bias, treat it more cautiously. Recommended markets / timeframes Works well for intraday momentum reading on instruments like Gold (XAUUSD) and Nasdaq, especially on 5m–15m charts. Higher timeframes can be used for smoother signals, while lower timeframes will react faster but produce more noise.
Pine Script®指標
由QuantumPipsio提供
Trinity POC BreakoutTrinity POC Breakout Indicator: User Guide ## Introduction The POC Breakout Indicator is a custom TradingView tool designed for short-term trading of SPY options on 3-minute and 5-minute timeframes, with adaptability for higher frames like 1-hour and above. It leverages volume footprint data to identify breakout opportunities around the Point of Control (POC), a key level where the most volume traded in a bar. This helps spot potential momentum shifts for call or put entries, such as buying calls on upside breakouts with positive delta or puts on downside breakouts with negative delta. The indicator includes visual POC zones, breakout signals with arrows, and optional filters for delta and a 34 EMA trend bias. It's ideal for scalping or intraday setups, combining order flow analysis with price action, and can be extended to swing trading on longer charts. Note: This indicator makes use of the new features from TradingView, specifically Pine Script version 6 and the advanced `request.footprint()` function, which provides access to detailed volume footprint data. This is a relatively new beta feature that enables granular buy/sell volume analysis at price levels, offering insights not available in older Pine versions. Ensure your TradingView account supports the latest updates, as footprint data may require a premium subscription for optimal performance on symbols like SPY. The indicator overlays directly on your price chart, so it won't create a separate pane. ## Indicator Components and How It Works The indicator requests volume footprint data for each bar using TradingView's new `request.footprint()` feature, breaking down buy/sell volume into rows (default 100 ticks per row) and calculating a 70% Value Area. It focuses on the POC row, which has the highest volume, and uses its upper and lower price edges as dynamic breakout levels. Key elements include: - POC Zone Visualization: If enabled via the "Show POC Zone Fill" input, it draws persistent orange lines and a semi-transparent fill between the POC upper and lower prices. This highlights the POC area across bars, acting as potential support/resistance. The zone updates each bar but persists for continuity, powered by Pine v6's enhanced drawing capabilities. - Breakout Signals: The core feature detects when price closes above the POC upper edge (bullish) or below the lower edge (bearish). Signals are filtered optionally by delta (requiring positive/increasing delta for calls, negative/decreasing for puts) and a 34 EMA (calls only above EMA, puts below). When triggered, it displays: - For longs: A green label below the bar with "Bull BR" and an upward-pointing arrow. - For shorts: A red label above the bar with "Bear BR" and a downward-pointing arrow. These visuals make it easy to spot entries at a glance, utilizing Pine v6's improved label styling for clearer, directional arrows. - Delta in Data Window: For additional context, it plots the bar's overall delta (buy minus sell volume) in TradingView's Data Window (hover over bars to see it), helping confirm order flow strength. This ties directly into the footprint data for real-time insights. The script processes data only when footprint is available, avoiding errors on incomplete bars, and benefits from TradingView's new beta footprint tools for more accurate volume breakdowns. ## Inputs and Customization All settings are accessible via the indicator's "Settings" menu in TradingView. Here's what each does, along with tips and hints for adapting to different timeframes like scalping (3min/5min) or higher ones (1hr+). For scalping breakouts, focus on tighter settings for quick signals; for 1hr+ charts, loosen them for broader context and fewer but higher-quality trades. Tooltips in the code provide in-panel guidance when hovering over inputs. - Ticks per Footprint Row: Default 100. This controls the granularity of volume breakdown in each bar. Tip: For scalping on 3min/5min, lower to 50–100 for finer details and more responsive POC levels during fast moves. For 1hr+ timeframes, increase to 150–300 to capture larger volume clusters, reducing noise from minor fluctuations and emphasizing major institutional levels. - Value Area %: Default 70. This defines the percentage of volume for the Value Area in the footprint calculation; adjust higher for a wider POC zone. Hint: In scalping, keep at 60–70% for narrower zones that highlight precise breakout points. On 1hr+ charts, raise to 75–90% to encompass more of the bar's volume, making the POC a stronger pivot for swing trades or longer option holds. - Show POC Zone Fill: Toggle on/off to display the orange POC fill; disable if it clutters your chart. Tip: Enable for visual scalping to quickly see breakout failures (e.g., price rejects the zone). On higher timeframes, it's useful for marking multi-bar support/resistance, but toggle off during backtesting to focus on signals alone. - Use Delta Increase Filter: Toggle on/off. When on, calls require positive and increasing delta, puts require negative and decreasing delta, for stronger conviction. Hint: Essential for scalping to filter out weak breakouts in choppy markets—turn on to avoid false signals during low-volume periods. For 1hr+ setups, consider turning off if you want more signals, as delta trends build slower and the filter might miss gradual shifts. - Use 34 EMA Trend Filter: Toggle on/off. When on, calls only trigger above the 34-period EMA, puts below, aligning with trend-following strategies like yours. Tip: For breakout scalping, enable to bias toward the trend (e.g., only upside calls in uptrends), reducing whipsaws. On 1hr+ charts, this shines for positional trading—pair with a longer EMA (adjust the next input) to capture major trends, ensuring breakouts align with the bigger picture. - EMA Length (for Trend Filter): Default 34. Change if you use a different EMA period. Hint: Stick to 34 for your style, but for scalping, shorten to 21–34 for quicker trend detection. For 1hr+ timeframes, extend to 50–100 to smooth out noise and focus on sustained breakouts, ideal for weekly options or swing plays. Experiment with these on historical SPY data using TradingView's replay feature to fine-tune for your style. For scalping breakouts, prioritize lower ticks and strict filters to catch fast edges; for 1hr+ (e.g., daily swings), use higher ticks and wider VA% for robust levels that hold over time. ## Usage Tips for SPY Options Trading Apply this on SPY charts for 3-minute (faster, more signals) or 5-minute (smoother) timeframes during active market hours. For higher timeframes like 1hr+, switch charts accordingly and adjust settings as noted above. - Interpreting Signals: A "bull br" arrow suggests potential upside momentum—consider buying ATM or slightly OTM calls for quick scalps, especially if delta is positive and price is above your 34 EMA. A "bear br" arrow indicates downside—buy puts. Use these as entry triggers, but confirm with overall market context or other indicators like volume delta from our #1 script. - Entry/Exit Strategies: Enter on the signal bar close. Set stops below the POC lower for calls (or above upper for puts). Target 0.5–2% SPY moves for 0DTE options on short TFs; on 1hr+, aim for larger targets like 3–5% with multi-day holds. Exit on opposite signals or trailing stops. - Risk Management: Only trade high-volume bars (check Data Window). Avoid signals during low-liquidity periods like pre-market. Backtest on past sessions to gauge win rates, especially comparing scalping vs. higher TF performance. ## Troubleshooting and Best Practices - If no POC zone appears: Ensure footprint data is available (premium feature); try reloading the chart or switching symbols. - Errors in Pine Editor: Verify the code is pasted correctly with proper indentation. If "na" issues occur, it's usually on the first few bars—normal behavior. For syntax errors like line continuation, ensure multi-line expressions are formatted as single lines or with consistent 4-space indents. - Performance: On mobile or slow connections, disable the POC fill for smoother loading.
Pine Script®指標
由EMA34TRADER提供