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RQ OSCILLATOR v0.1 RQ OSCILLATOR v0.1 Regression Quantum Momentum RQ Oscillator detects momentum expansion and exhaustion using a regression baseline instead of traditional averages. ━━━━━━━━━━━━━━━━ ENGLISH The RQ Oscillator is a momentum indicator designed to measure how far price moves away from its statistical equilibrium. Instead of relying purely on traditional moving averages, the indicator uses Linear Regression as a mathematical baseline. This helps reveal structural price movement while reducing lag. The result is a responsive oscillator that highlights momentum expansion, exhaustion, and potential mean-reversion zones. ━━━━━━━━━━━━━━━━ HOW IT WORKS 1. A Linear Regression line defines the equilibrium of price. 2. The oscillator measures the distance between price and that equilibrium. 3. Light smoothing is applied to reduce market noise while preserving reaction speed. When price stretches away from the regression baseline, the oscillator exposes that imbalance. ━━━━━━━━━━━━━━━━ STEM CHART VISUALIZATION The indicator uses a Stem Chart style visualization to make momentum shifts instantly readable. 🔵 Bright Blue — Strong Bullish Momentum Momentum is above zero and strengthening. 🔵 Dim Blue — Weakening Bullish Momentum Momentum is above zero but fading. 🟠 Bright Orange — Strong Bearish Momentum Momentum is below zero and accelerating downward. 🟠 Dim Orange — Weakening Bearish Momentum Momentum is below zero but losing strength. ━━━━━━━━━━━━━━━━ HOW TO READ THE INDICATOR Above Zero Bullish pressure dominates. Below Zero Bearish pressure dominates. Expanding Histogram Momentum is increasing. Contracting Histogram Momentum is weakening. Momentum turning near extremes can signal a potential shift in market control. ━━━━━━━━━━━━━━━━ WHY RQ OSCILLATOR • Regression-based baseline • Reduced lag compared to classic averages • Clear momentum visualization • Data-driven structure • Designed for fast markets Works on Crypto • Forex • Indices • Stocks ━━━━━━━━━━━━━━━━ ━━━━━━━━━━━━━━━━ РУССКАЯ ВЕРСИЯ RQ Oscillator определяет расширение и затухание моментума, используя регрессионный базис вместо традиционных скользящих средних. RQ Oscillator — это индикатор моментума, который измеряет, насколько далеко цена отклонилась от своего статистического равновесия. Вместо традиционных скользящих средних используется Линейная Регрессия как математический базис. Это помогает увидеть структуру движения цены и уменьшает запаздывание сигналов. В результате получается быстрый осциллятор, который показывает усиление импульса, его ослабление и возможные зоны возврата к среднему. ━━━━━━━━━━━━━━━━ КАК ЭТО РАБОТАЕТ 1. Линия линейной регрессии определяет равновесие цены. 2. Осциллятор измеряет расстояние между ценой и этим уровнем. 3. Лёгкое сглаживание используется для уменьшения рыночного шума. Когда цена сильно отклоняется от линии регрессии, индикатор показывает этот дисбаланс. ━━━━━━━━━━━━━━━━ ВИЗУАЛИЗАЦИЯ STEM CHART 🔵 Ярко-синий — Сильный бычий моментум Осциллятор выше нуля и усиливается. 🔵 Тускло-синий — Ослабевающий бычий моментум Осциллятор выше нуля, но начинает снижаться. 🟠 Ярко-оранжевый — Сильный медвежий моментум Осциллятор ниже нуля и ускоряется вниз. 🟠 Тускло-оранжевый — Ослабевающий медвежий моментум Осциллятор ниже нуля, но давление уменьшается. ━━━━━━━━━━━━━━━━ КАК ЧИТАТЬ ИНДИКАТОР Выше нуля Преобладает бычье давление. Ниже нуля Преобладает медвежье давление. Расширение гистограммы Импульс усиливается. Сужение гистограммы Импульс ослабевает. Смена направления моментума вблизи экстремумов может сигнализировать о потенциальном перехвате контроля над рынком. ━━━━━━━━━━━━━━━━ CODE // © Karpychev Igor Sergeevich //@version=6 // RQ OSCILLATOR // RQ = REGRESSION QUANTUM indicator("RQ OSCILLATOR v0.1", shorttitle="RQ Osc v0.1", format=format.price, precision=2) // ========================================== // 1. НАСТРОЙКИ (Version 0.1) // ========================================== length = input.int(20, title="Regression Length", minval=2) src = input.source(close, title="Source") smoothLength = input.int(3, title="Smoothing (SMA)", minval=1) // ========================================== // 2. МАТЕМАТИКА // ========================================== linReg = ta.linreg(src, length, 0) osc = src - linReg smoothedOsc = ta.sma(osc, smoothLength) // ========================================== // 3. ВИЗУАЛИЗАЦИЯ (Stem Chart Design) // ========================================== // Профессиональная палитра color pos_strong = #2962FF // Electric Blue color pos_weak = color.new(#2962FF, 60) color neg_strong = #FF6D00 // Deep Orange color neg_weak = color.new(#FF6D00, 60) // Логика определения цвета isRising = smoothedOsc > nz(smoothedOsc ) isAboveZero = smoothedOsc >= 0 color dotColor = isAboveZero ? (isRising ? pos_strong : pos_weak) : (isRising ? neg_weak : neg_strong) // Нулевая линия hline(0, title="Baseline", color=color.new(#787B86, 60), linestyle=hline.style_solid) // Отрисовка слоев RQ OSC v0.1 plot(smoothedOsc, title="Stems", style=plot.style_columns, color=color.new(dotColor, 75), linewidth=2) plot(smoothedOsc, title="Thread", style=plot.style_line, color=color.new(dotColor, 40), linewidth=1, display=display.pane, editable=false) plot(smoothedOsc, title="Data Points", style=plot.style_circles, color=dotColor, linewidth=3, display=display.pane, editable=false)
Pine Script® indicator
by karpychev_i_s
KDE Reversals [UAlgo]KDE Reversals is a statistical reversal oscillator that measures where the current price sits inside its recent distribution using a Kernel Density Estimation based cumulative probability model. Instead of relying on fixed momentum formulas or classic overbought and oversold oscillators, the script builds a rolling sample of recent source values, estimates a smoothed empirical distribution, and converts the current value into a percentile style reading from 0 to 100. The result is a non parametric probability oscillator that answers a simple question: how extreme is the current price relative to the recent sample? Very high readings mean the current value is located near the upper tail of the recent distribution. Very low readings mean it is near the lower tail. The script then uses user defined upper and lower reversal zones to detect potential turning points when the percentile reading exits those extreme regions. The indicator runs in a separate pane ( overlay=false ) and combines: A rolling KDE based empirical CDF oscillator Upper and lower statistical reversal zones Gradient coloring based on percentile position Background highlighting in extreme conditions Optional reversal labels when the percentile exits an extreme zone This makes the tool especially useful for traders who want a more distribution aware approach to reversal detection rather than a fixed oscillator threshold based only on momentum formulas. Educational tool only. Not financial advice. 🔹 Features 🔸 1) KDE Based Empirical CDF Oscillator The core output of the script is a percentile style oscillator built from Kernel Density Estimation. It estimates the cumulative distribution position of the current source value relative to a rolling lookback sample and expresses that result as a percentage from 0 to 100. This gives a probabilistic location measure rather than a raw momentum reading. 🔸 2) Rolling Lookback Distribution Model The script stores a rolling window of recent source values in an internal array. As new bars arrive, the oldest values are removed once the array reaches the configured length. This keeps the distribution adaptive to recent market behavior. Because the model is rolling, the oscillator can adjust as the market shifts from one regime to another. 🔸 3) Non Parametric Reversal Logic Unlike indicators that assume a fixed normal distribution of prices, this script uses a kernel smoothed empirical distribution. That means the reversal zones are based on the actual recent sample shape, not a rigid assumption about how price should be distributed. This can make the signal more responsive to skewed, compressed, or uneven recent market structure. 🔸 4) Custom Upper and Lower Reversal Zones Users can define: An upper reversal zone in percentile terms A lower reversal zone in percentile terms These thresholds determine what counts as statistically stretched relative to the recent sample. This allows the indicator to be tuned for more aggressive or more selective reversal detection. 🔸 5) Reversal Triggers on Exit from Extremes The script does not trigger simply because the oscillator enters an extreme zone. Instead, it triggers when the percentile reading exits the extreme zone: A sell trigger occurs when the oscillator crosses back below the upper threshold A buy trigger occurs when the oscillator crosses back above the lower threshold This design aims to catch reversal confirmation after an extreme condition begins to unwind. 🔸 6) Dynamic Gradient Coloring The percentile line is colored with a gradient between bullish and bearish colors based on its position between the lower and upper thresholds. This makes it easy to identify whether the current reading is leaning toward lower tail, neutral, or upper tail conditions. 🔸 7) Upper and Lower Zone Fills The script includes gradient fills above and below the midline so the oscillator visually emphasizes upper tail and lower tail behavior. This improves readability and helps the user quickly identify whether the current reading is operating in a statistically stretched region. 🔸 8) Extreme Zone Background Highlighting When the oscillator is above the upper threshold or below the lower threshold, the pane background is lightly highlighted. This creates an immediate visual cue that the current reading is inside a high probability reversal watch zone. 🔸 9) Optional Reversal Labels When enabled, the script prints: A downward label after a bearish reversal trigger An upward label after a bullish reversal trigger These labels are intentionally simple and keep the pane clean while still marking the event clearly. 🔸 10) Flexible Source Selection The user can choose which source series to analyze, not only close. This allows the KDE engine to be applied to other price derived series if desired. 🔹 Calculations 1) Rolling Data Queue The script stores recent source values in a custom KDEData object: type KDEData array prices int length Each bar, the new value is pushed into the array: this.prices.push(val) if this.prices.size() > this.length this.prices.shift() This creates a fixed length rolling sample used for the KDE calculation. 2) Interquartile Range (IQR) Calculation To make the bandwidth estimate more robust, the script computes the interquartile range from a sorted copy of the rolling sample: int q1_idx = int(math.floor(n * 0.25)) int q3_idx = int(math.floor(n * 0.75)) sorted.get(q3_idx) - sorted.get(q1_idx) The IQR is later used as part of the spread estimate for kernel bandwidth selection. 3) Robust Spread Estimate The script combines sample standard deviation and IQR based scaling: float stdev = this.prices.stdev() float iqr = this.get_iqr() float spread = math.min(stdev, iqr / 1.34) Interpretation: iqr / 1.34 is a robust estimate of standard deviation under near normal assumptions. Taking the minimum of stdev and iqr / 1.34 helps reduce the effect of extreme outliers when setting the kernel width. If the spread collapses to zero, the script falls back to a very small positive value. 4) KDE Bandwidth Selection The kernel bandwidth is computed using a Silverman style rule: float h = 1.06 * spread * math.pow(n, -0.2) This gives the smoothing width used in the Gaussian kernel estimation. Larger sample size reduces the bandwidth, while larger spread increases it. If the calculated bandwidth is zero, the script forces a small fallback: if h == 0 h := 0.0001 5) Gaussian Error Function Approximation The script defines its own approximation of the error function: erf(float x) => ... This function is then used to build the standard normal cumulative distribution function: norm_cdf(float z) => float sqrt2 = math.sqrt(2) 0.5 * (1.0 + erf(z / sqrt2)) This is the mathematical core that converts standardized distances into cumulative probabilities. 6) KDE Based Empirical CDF Calculation For the current price, the script computes a smoothed empirical CDF by averaging the Gaussian CDF centered on every historical sample point: for i = 0 to n - 1 float xi = this.prices.get(i) float z = (current_price - xi) / h sum_prob += norm_cdf(z) Then: (sum_prob / n) * 100.0 Interpretation: Each historical observation contributes a smooth cumulative probability curve. Averaging them creates a KDE smoothed empirical percentile estimate for the current price. This is more stable than a raw rank percentile because it smooths the distribution instead of using hard cutoffs only. 7) Warm Up Condition The indicator only computes the KDE percentile once the rolling sample is fully populated: if kde.prices.size() == lengthInput cdf_percent := kde.get_kde_cdf(srcInput) Before that, the output remains na , which prevents incomplete early calculations. 8) Oscillator Interpretation The resulting cdf_percent is a percentile style value: Near 0 means the current source is near the lower tail of the recent distribution Near 50 means it is near the middle of the recent distribution Near 100 means it is near the upper tail of the recent distribution This is not a momentum ratio. It is a location measure inside the recent smoothed distribution. 9) Threshold Logic The user defines: float upperThreshold = input.float(95.0, ...) float lowerThreshold = input.float(5.0, ...) These thresholds define statistically extreme regions. For example: A 95 reading means the source is near the top tail of the recent sample A 5 reading means the source is near the bottom tail 10) Reversal Trigger Conditions The script does not trigger on entry into the zone. It triggers when the oscillator exits the zone: Bearish reversal trigger: bool sellTrigger = ta.crossunder(cdf_percent, upperThreshold) Bullish reversal trigger: bool buyTrigger = ta.crossover(cdf_percent, lowerThreshold) Interpretation: A sell trigger means the percentile was above the upper threshold and then moved back below it. A buy trigger means the percentile was below the lower threshold and then moved back above it. This acts more like a reversion confirmation than an early warning. 11) Visual Gradient Line The main oscillator line color is derived from its current percentile position: color cdfColor = color.from_gradient(cdf_percent, lowerThreshold, upperThreshold, col_bull, col_bear) This creates a smooth transition from bullish coloring in the lower reversal area toward bearish coloring in the upper reversal area. 12) Gradient Fill Zones The script fills the area between the percentile line and the hidden midline (50) separately for upper and lower halves: fill(p_cdf, p_mid, top_value=100, bottom_value=50, ...) fill(p_cdf, p_mid, top_value=50, bottom_value=0, ...) This gives the oscillator a cleaner and more informative visual structure than a plain line alone. 13) Background Highlighting When the oscillator is inside an extreme zone, the pane background is lightly shaded: bgcolor(cdf_percent >= upperThreshold ? ... : cdf_percent <= lowerThreshold ? ... : na) This does not trigger a signal by itself. It simply highlights that the reading is currently in a statistically extreme region. 14) Reversal Labels If labels are enabled, the script marks reversal exits with simple directional arrows: For bearish reversal: label.new(bar_index, cdf_percent + 3, "▼", ...) For bullish reversal: label.new(bar_index, cdf_percent - 3, "▲", ...) The labels are plotted near the oscillator value, not on price, which keeps the indicator self contained in its own pane.
Pine Script® indicator
by UAlgo
VWAP First Return Stats TableFirst VWAP Return Half-Hour Table (9:30–4:00 EST) This clean, real-time statistics table shows exactly which 30-minute window has historically been the most common for the first return to daily VWAP during regular trading hours (9:30 AM – 4:00 PM EST). For each of the 5 major instruments (ES1!, CL1!, GC1!, 6E1!, BTCUSD), the table displays the percentage of trading days where the very first touch of the daily volume-weighted average price occurred in each half-hour bucket. Perfect for: VWAP traders & mean-reversion strategies Intraday scalpers looking for high-probability reversion windows Futures & crypto day traders who want data-driven timing edges Key Features 13 precise half-hour buckets from 9:30 all the way to 15:30 (covers the 16:00 close bar) Percentages always sum to 100% for days that touched VWAP at least once by 4:00 PM EST Accurate daily VWAP anchored to EST midnight (same as your main VWAP Deviation Table) Full EST timezone handling — works regardless of your chart timezone Clean black table with customizable text size (tiny → large) Updates live as new days complete Works on any timeframe (1-min to 15-min recommended for best accuracy) Symbols included: ES1! CL1! GC1! 6E1! BTCUSD How to use: Simply add the indicator to any chart. The table appears in the top-right corner and shows historical probabilities instantly. Use it to quickly spot which time window has the highest chance of the first VWAP touch for your favorite symbol — extremely useful for planning entries, exits, or alerts. Combine this with the original “VWAP Deviation Table” for a complete intraday VWAP dashboard. Note: Percentages are calculated from all available historical data. The more days loaded, the more stable the stats become.
Pine Script® indicator
by Resonant_Trader
Automatic Fibonacci Levels [WillyAlgoTrader]Automatic Fibonacci Levels is an overlay indicator that detects the dominant swing high and swing low within the visible chart area, draws a full Fibonacci retracement and extension grid between them, highlights the Optimal Trade Entry (OTE) zone at 61.8%–78.6%, marks a target zone at the −50% to −61.8% extension, and labels four take-profit levels — all updating automatically as you scroll or zoom the chart. Most Fibonacci tools on TradingView are either manual (you draw them yourself and they become stale as price evolves) or pivot-based (anchored to a fixed lookback period that may not match the swing you're actually looking at). This indicator takes a different approach: it uses the visible chart range as its context. It finds the highest high and lowest low within what you can currently see, determines trend direction based on which came first, and draws the full Fibonacci grid accordingly. When you scroll or zoom to a different area, the grid adapts — making it a dynamic analysis companion rather than a static drawing tool. 🔍 WHAT MAKES IT ORIGINAL 1. Visible-range swing detection. Instead of using a fixed pivot lookback or requiring manual anchor placement, the indicator scans the chart's visible window (chart.left_visible_bar_time to chart.right_visible_bar_time) to find the absolute high and low. This means the Fibonacci grid always reflects the swing structure you are currently analyzing. Zoom into a 50-bar range to see intraday retracements; zoom out to 500 bars to see the macro structure — the grid adjusts automatically. When the visible range changes (scroll or zoom), swing detection resets and recalculates. 2. Automatic trend direction from swing sequence. The indicator determines bullish or bearish bias by comparing when the swing low and swing high occurred. If the swing low formed first and the swing high formed later, the trend is classified as bullish (retracement levels are drawn down from the high, extensions project upward). If the swing high came first, the trend is bearish (retracement down from the low, extensions project downward). No manual input is needed — the grid orientation follows the price structure. 3. OTE Entry Zone + Target Zone as highlighted boxes. Two key zones are highlighted with semi-transparent boxes: — Entry Zone (61.8%–78.6%) : the Optimal Trade Entry area from ICT/SMC methodology — the deep retracement zone where institutional re-entry is most likely — Target Zone (−50% to −61.8%) : the extension zone where breakout moves frequently reach Both zones have configurable colors and optional text labels ("ENTRY ZONE" / "TARGET ZONE") inside them. Zone-touch alerts fire when price enters either box for the first time. 4. Four labeled take-profit levels. TP labels are placed at key Fibonacci levels to provide a structured scale-out framework: — TP1 at 38.2% (first retracement target — conservative exit) — TP2 at 0% (full swing retest — swing high in uptrend, swing low in downtrend) — TP3 at −27.2% (first Fibonacci extension) — TP4 at −61.8% (deep extension — runner target) Each TP level is only displayed if the corresponding Fibonacci line is enabled, keeping the chart clean. 5. 16 individually toggleable levels. The indicator supports a comprehensive set of levels: 0%, 23.6%, 38.2%, 50%, 61.8%, 70.6%, 78.6%, 100% (standard retracements), plus 18%, 150%, 200% (deep retracements), and −18%, −27.2%, −50%, −61.8%, −100% (extensions). Each level can be toggled on or off independently, so you can configure exactly the grid density you prefer — from a minimal 4-level setup to a full 16-level deep analysis. ⚙️ HOW IT WORKS Swing detection: On every bar, the script checks whether the current bar falls within the chart's visible time window (using chart.left_visible_bar_time and chart.right_visible_bar_time). Within this window, it tracks the highest high and lowest low, along with their bar indices. When the visible window changes (scroll/zoom), all swing data resets and recalculates from scratch. This ensures the grid always reflects your current view. Trend direction: If swingLowBarIdx < swingHighBarIdx (low came first), the trend is classified as bullish — Fibonacci levels count downward from the swing high (0% = high, 100% = low), and extensions project above the high. If the high came first, the trend is bearish — levels count upward from the swing low, extensions project below. Level calculation: Each Fibonacci level is calculated as: price = anchor ± (swingRange × ratio), where the anchor and direction depend on the trend bias. For a bullish trend: 0% = swingHigh, 61.8% = swingHigh − range × 0.618, −50% = swingHigh + range × 0.5. For bearish: mirrored. Zone detection: The Entry Zone (61.8%–78.6%) and Target Zone (−50% to −61.8%) are computed as price ranges. On each confirmed bar, the script checks if the close falls within either zone. A zone-touch alert fires on the first confirmed bar inside the zone (no repeated alerts while price stays in the zone). The inEntryZone / inTargetZone state resets when price leaves, allowing re-entry detection. Drawing: All visual elements (lines, labels, boxes) are drawn on barstate.islast and cleaned up on each redraw to prevent accumulation. Lines extend from 2 bars before the current bar to the label offset position. Zones use extend.right so they remain visible as new bars form. 📖 HOW TO USE Reading the chart: — Orange horizontal lines = Fibonacci levels (retracement + extensions) — Optional % labels next to each line = level identification — Gold semi-transparent box = Entry Zone (61.8%–78.6% OTE) — Gold semi-transparent box with "TARGET ZONE" = extension target (−50% to −61.8%) — TP1–TP4 labels = structured take-profit levels — Optional diagonal line = swing connection (low-to-high or high-to-low) Suggested workflow: — Zoom to the swing you want to analyze — the grid adapts automatically — In a bullish trend: look for buy entries when price retraces into the Entry Zone (61.8%–78.6%), with stop loss below 100% (swing low), targeting TP1 (38.2%) → TP2 (0% / swing high) → TP3 (−27.2%) → TP4 (−61.8%) — In a bearish trend: look for sell entries when price retraces up into the Entry Zone, stop above swing high, targeting downward extensions — Use the dashboard to confirm trend direction and monitor whether price is currently in the Entry or Target zone — Set alerts for zone touches to get notified when price reaches OTE or target levels without watching the chart Customization tips: — For a clean chart: enable only 0%, 61.8%, 78.6%, 100%, −27.2%, −61.8% — this gives you the OTE boundaries, swing anchors, and two extension targets — For deep analysis: enable all 16 levels to see the full Fibonacci structure — Adjust Label Offset to move level labels further right if your chart is crowded — Toggle Show Diagonal Swing Line to visually confirm which high/low pair is being used ⚙️ KEY SETTINGS REFERENCE — Show All Elements (default On): master toggle for all Fibonacci visuals — Line Width (default 1): thickness of Fibonacci lines (1 = subtle, 5 = bold) — Line Style (default Dashed): solid, dashed, or dotted — Label Offset (default 17 bars): how far right of the last bar to place labels — Individual Levels : 16 toggleable levels from 200% to −100% — Show Entry Zone (default On): highlight the 61.8%–78.6% OTE box — Show Target Zone (default On): highlight the −50% to −61.8% extension box — Show Text in Zones (default On): display "ENTRY ZONE" / "TARGET ZONE" labels — Show TP Labels (default On): display TP1–TP4 at key levels — Show Level % Labels (default Off): display percentage text next to each line 📊 Dashboard The info panel displays: — Trend direction (Bullish / Bearish) based on swing sequence — Signal status (Entry Zone / Target Zone / —) when price enters a key zone — Swing range in price units — Current timeframe and indicator version 🔔 Alerts Two alert conditions (each fires once per zone entry on bar close): — Entry Zone touch : price closes inside the 61.8%–78.6% retracement zone — Target Zone touch : price closes inside the −50% to −61.8% extension zone Both support standard text and JSON webhook format. ⚠️ IMPORTANT NOTES — This indicator anchors to the visible chart range — it recalculates when you scroll or zoom. This is a feature, not a bug: it lets you analyze any swing by simply framing it on your screen. However, it means the grid will change if you move the chart. — Fibonacci levels are not predictive — they are reference points based on the measured swing range. Price may or may not react at any given level. — The Entry Zone (61.8%–78.6%) is derived from the OTE concept used in ICT/SMC methodology. It represents a high-probability retracement area, but no retracement zone guarantees a reversal. — Zone alerts require bar-close confirmation and fire once per entry — they do not repeat while price remains in the zone. — Works across all asset classes and timeframes. No volume data required.
Pine Script® indicator
by WillyAlgoTrader
4
Fibonacci levels for Future Trading + Tokyo, London and NYFibonacci Retracement RealTime (Futures Sessions) Fibonacci Retracement RealTime is an intraday futures-focused indicator that combines dynamic RTH Fibonacci levels with key session-based reference lines from Tokyo, London, and previous-day RTH extremes. It is designed to help traders frame market structure quickly, identify reaction zones, and maintain a consistent session workflow using New York session logic. This tool is especially useful for traders who track: U.S. Regular Trading Hours (RTH) expansion/contraction Overnight liquidity and range development Institutional session highs/lows as potential support/resistance Fibonacci retracement behavior inside the evolving daily range What the indicator does 1) Real-time RTH Fibonacci framework During the RTH session, the script continuously tracks the current daily high and daily low and recalculates the Fibonacci structure in real time. Displayed levels: 1.000 (Daily High) 0.786 0.618 0.500 0.382 0.236 0.000 (Daily Low) As new highs/lows are created during RTH, the levels are redrawn and extended to the current bar, so you always see the latest active retracement map for the day. 2) Automatic session logic (New York time) The indicator includes session-aware behavior for: RTH (default: 09:30–16:00 NY) Tokyo (default: 19:00–02:00 NY) London (default: 02:00–08:00 NY) Each session can be used as a structural reference, and the session timezone is configurable (default is America/New_York). 3) Previous-day RTH high/low projected overnight After RTH closes, the script stores the RTH high and low. During overnight trading (Tokyo/London), it projects these as horizontal references: YHoD (Yesterday High of Day) YLoD (Yesterday Low of Day) This helps identify potential overnight reaction zones and directional bias around prior U.S. cash extremes. 4) Tokyo and London session range levels Once each session ends, the indicator locks in and projects: Tokyo High / Tokyo Low London High / London Low These lines are extended forward toward the current trading day’s RTH timeline, making it easier to monitor whether U.S. price action is accepting/rejecting overnight session ranges. Why traders use it To align intraday decisions with session structure To combine Fibonacci pullback zones with session highs/lows To detect high-probability reaction areas (confluence between fib + session level) To keep chart context clean and systematic without drawing everything manually Visual design and labels The indicator prints clear labels for: Daily High / Daily Low Fibonacci percentages YHoD / YLoD Tokyo High / Tokyo Low London High / London Low All key line/tag colors are customizable so you can adapt visibility to your chart theme. Inputs and customization You can control: Session timezone RTH, Tokyo, and London session windows Show/hide toggles for session line groups Line and tag colors for each session family This allows adaptation across futures products and personal chart templates while keeping the same operational logic.
Pine Script® indicator
by BINUT_BNT
Polynomial Regression Moving Average (PRMA)1. WHAT IS PRMA? PRMA is a non-repainting, smoothed moving average that uses the endpoint of polynomial regression as its core value. It generalizes the classic Linear Regression Moving Average (LSMA) to any polynomial degree — including fractional values — and adds a comprehensive multi-method, multi-iteration smoothing layer on top. In Simple Terms PRMA fits a mathematical curve (polynomial) to recent price history, takes the last point of that curve as the current value, then optionally smooths the result using your choice of 9 different smoothing algorithms — applied up to 10 times in sequence. 2. CORE ARCHITECTURE text ┌─────────────────────────────────────────────────────┐ │ PRMA PIPELINE │ │ │ │ Price Data ──► Polynomial Regression ──► Endpoint │ │ (OLS with degree d) Extraction │ │ │ │ │ ▼ │ │ Raw PRMA Value │ │ │ │ │ ▼ │ │ Smoothing Layer │ │ (Method × Iterations)│ │ │ │ │ ▼ │ │ Final PRMA Output │ │ │ │ │ ▼ │ │ Signal Generation │ │ (Direction Change) │ └─────────────────────────────────────────────────────┘ 3. MATHEMATICAL FOUNDATION 3.1 Polynomial Regression (OLS) For the last n bars, a polynomial of degree d is fitted: text ŷ(x) = β₀ + β₁x + β₂x² + ... + βₐxᵈ The coefficients are solved via the Normal Equation: text β = (XᵀX)⁻¹ · Xᵀ · y Where X is the Vandermonde matrix: text X = | 1 0 0² ... 0ᵈ | | 1 1 1² ... 1ᵈ | | 1 2 2² ... 2ᵈ | | . . . ... . | | 1 n-1 (n-1)² ... (n-1)ᵈ | 3.2 The Weight Kernel (Efficiency Innovation) Instead of solving full regression every bar, a fixed weight kernel is precomputed once: text Kernel K = x_last · (XᵀX)⁻¹ · Xᵀ Where x_last = Then each bar simply computes: text PRMA_raw = Σ K × price for i = 0 to n-1 This is a constant-time weighted sum — extremely efficient. 3.3 Fractional Degree Interpolation For degree = 3.7: text kernel_3 = compute_kernel(degree=3) kernel_4 = compute_kernel(degree=4) final_kernel = 0.3 × kernel_3 + 0.7 × kernel_4 This allows infinitely fine-grained control over responsiveness. 3.4 Smoothing Layer The raw PRMA value passes through a selectable smoothing function, applied iteratively: text smoothed₁ = smooth(raw_PRMA) smoothed₂ = smooth(smoothed₁) smoothed₃ = smooth(smoothed₂) ... smoothedₙ = smooth(smoothedₙ₋₁) Each iteration further reduces noise while adding controlled lag. 4. ALL PARAMETERS EXPLAINED 4.1 Core Parameters Parameter Default Range Description Source close Any price The price data fed into the regression Period 100 ≥ 2 Number of bars in the regression lookback window Degree 4.0 ≥ 1.0 (step 0.1) Polynomial degree — controls curve complexity 4.2 Color Parameters Parameter Default Description Up Green rgb(36,223,23) PRMA line color when rising Down Fuchsia PRMA line color when falling 4.3 Smoothing Parameters Parameter Default Range Description Smoothing Method EMA 10 options Type of smoothing filter applied Smoothing Length 5 ≥ 1 Lookback for the smoothing algorithm Smoothing Iterations 1 1–10 Number of sequential smoothing passes 4.4 Signal Parameters Parameter Default Description Show Signals true Toggle buy/sell labels on chart 5. SMOOTHING METHODS IN DETAIL 5.1 Complete Smoothing Method Comparison Method Formula Concept Lag Smoothness Best For None No smoothing Zero Raw Fastest response, noisy SMA Equal-weight average High Moderate Simple baseline smoothing EMA Exponential decay Medium Good General purpose WMA Linear weight decay Medium Good Recent-data emphasis RMA Wilder's smoothing High Very High Ultra-smooth trending HMA Hull method Low Good Low-lag smoothing DEMA Double EMA Low Good Lag reduction TEMA Triple EMA Very Low Moderate Minimum lag VWMA Volume-weighted mean Medium Good Volume-aware smoothing Gaussian Bell-curve kernel Medium Excellent Natural, artifact-free 5.2 Smoothing Method Formulas text SMA(n) = (P₁ + P₂ + ... + Pₙ) / n EMA(n) = α × P + (1-α) × EMA_prev where α = 2/(n+1) WMA(n) = (n×P₁ + (n-1)×P₂ + ... + 1×Pₙ) / (n×(n+1)/2) RMA(n) = (1/n) × P + (1 - 1/n) × RMA_prev HMA(n) = WMA(√n, 2×WMA(n/2) - WMA(n)) DEMA(n) = 2×EMA(n) - EMA(EMA(n)) TEMA(n) = 3×(EMA - EMA²) + EMA³ VWMA(n) = Σ(P×V) / Σ(V) Gaussian(n) = Σ(P × e^(-0.5×(i/σ)²)) / Σ(e^(-0.5×(i/σ)²)) where σ = n/3 5.3 Multi-Iteration Effects text Iterations: 1 2 3 4+ │ │ │ │ Noise: Low Very Low Minimal Near Zero Lag: Low Moderate Higher Highest Shape: Sharp Rounded Very Round Gaussian-like Iterations Equivalent Behavior 1 Standard single-pass filter 2 Similar to Butterworth 2nd-order 3 Approaching Gaussian response 4+ Ultra-smooth, trend-only extraction 6. SIGNAL LOGIC 6.1 Direction Detection text PRMA Rising → prma > prma → Bullish PRMA Falling → prma < prma → Bearish 6.2 Buy Signal (Long — "L") text Conditions (ALL must be true): ✅ PRMA turns UP (was falling on previous bar, now rising) ✅ Close > PRMA (price confirms above the moving average) ✅ Show Signals ON Displayed as: Green "L" label below the bar 6.3 Sell Signal (Short — "S") text Conditions (ALL must be true): ✅ PRMA turns DOWN (was rising on previous bar, now falling) ✅ Close < PRMA (price confirms below the moving average) ✅ Show Signals ON Displayed as: Fuchsia "S" label above the bar 6.4 Signal Flow Diagram text PRMA Direction │ ┌─────────┴──────────┐ ▼ ▼ Rising Falling │ │ │ Was Falling? │ Was Rising? │ │ │ │ ▼ ▼ ▼ ▼ Yes No Yes No │ └── No Signal │ └── No Signal │ │ ▼ ▼ Close > PRMA? Close < PRMA? │ │ Yes ──► BUY "L" Yes ──► SELL "S" No ──► No Signal No ──► No Signal 7. NON-REPAINTING GUARANTEE Why PRMA Never Repaints Factor Explanation Fixed kernel Weight matrix computed once on first bar, never recalculated Fixed lookback Each bar uses exactly length bars ending at length bars ago No future data Uses source through source — all confirmed Deterministic smoothing All smoothing methods are causal (backward-looking only) One value per bar Once a bar closes, its PRMA value is permanently locked Important Note The indicator uses source check, meaning the PRMA value is plotted with a length-bar delay from the source data. This ensures that ALL input data is from closed, confirmed bars — the ultimate non-repainting guarantee. Repainting vs Non-Repainting Comparison text REPAINTING Polynomial Regression Channel: Bar 100: Draws curve across bars 1-100 Bar 101: REDRAWS curve across bars 2-101 ← ALL previous values change! NON-REPAINTING PRMA: Bar 100: Computes endpoint of regression on bars 1-100 → single fixed value Bar 101: Computes endpoint of regression on bars 2-101 → new single fixed value Bar 100's value NEVER changes ✅ 8. USE CASES 8.1 Trend Following Goal: Identify and ride medium-to-long-term trends Setup: text Period: 150–200 Degree: 1.5–2.5 Smoothing: EMA, Length 10, Iterations 2 Strategy: Go Long when PRMA turns green (rising) + price above PRMA Go Short when PRMA turns fuchsia (falling) + price below PRMA Exit on opposite signal or when price crosses PRMA against position Example: text SELL signal ↓ Price: ──╱╲──╱╲──╱╲──╲╱──╲──╲╱──╲── PRMA: ────────╱──────╲────────╲──── Color: ████████GREEN███FUCHSIA██████ ↑ BUY signal Markets: Stocks, ETFs, Forex (trending pairs like EUR/USD, USD/JPY) Risk Management: Stop loss: Below PRMA line (for longs) or recent swing low Take profit: When opposite signal appears or fixed R:R ratio Position sizing: Based on ATR distance from PRMA 8.2 Swing Trading Goal: Capture medium-term price swings with clean entry/exit signals Setup: text Period: 50–100 Degree: 3.0–4.0 Smoothing: HMA, Length 5, Iterations 1 Strategy: Enter Long on "L" signal when price is above a higher-timeframe support Enter Short on "S" signal when price is below a higher-timeframe resistance Use PRMA direction color as bias filter Example — Multi-Timeframe Approach: text Daily PRMA (Period 100, Degree 2): Rising → BULLISH BIAS 4H PRMA (Period 50, Degree 4): "L" signal appears Action: Enter Long (aligned with daily bias) Markets: Stocks, Crypto (BTC, ETH), Commodities 8.3 Scalping / Day Trading Goal: Quick entries and exits on short timeframes Setup: text Period: 20–50 Degree: 1.0–2.0 Smoothing: TEMA, Length 3, Iterations 1 Strategy: Use on 1m–15m charts Enter on signal in direction of PRMA slope Exit quickly — target 1:1 or 1:1.5 R:R Avoid signals during consolidation (flat PRMA) Example — 5-Minute Chart: text 09:30 ─────────╱── PRMA turns green 09:35 ── "L" signal, price > PRMA → BUY 09:50 ── Target hit, close position 10:15 ──╲──── PRMA turns fuchsia → flat/reverse Markets: Futures (ES, NQ), Forex (major pairs), Crypto 8.4 Mean Reversion Goal: Trade pullbacks to the PRMA line Setup: text Period: 100–150 Degree: 2.0–3.0 Smoothing: Gaussian, Length 8, Iterations 2 Strategy: Identify trend direction via PRMA color Wait for price to pull back TO the PRMA line (touch or cross slightly) Enter in the direction of the PRMA trend when price bounces off PRMA Stop loss: Beyond the PRMA line Example: text Uptrend (PRMA green): Price: ──╱──╱──╲──╱──╱──╲──╱── PRMA: ────╱────╱────╱────╱──── ↑ ↑ Pullback Pullback to PRMA to PRMA = BUY = BUY Markets: Stocks with strong trends, Index ETFs (SPY, QQQ) 8.5 Volatility Regime Detection Goal: Determine if market is trending or ranging Setup: text Period: 100 Degree: 4.0 (high responsiveness) Smoothing: SMA, Length 15, Iterations 3 (ultra-smooth) Strategy: Flat PRMA (minimal direction changes) → Ranging market → Use mean reversion strategies Clearly sloped PRMA (consistent color) → Trending market → Use trend following strategies Frequent color changes → Choppy market → Reduce position size or stay out Example: text Trending Phase: Choppy Phase: Ranging Phase: PRMA: ────╱──╱── PRMA: ╱╲╱╲╱╲╱╲ PRMA: ────────── Color: GREEN GREEN Color: G F G F G F Color: GREEN (flat) Action: TREND FOLLOW Action: STAY OUT Action: MEAN REVERT Markets: All — this is a meta-strategy for selecting other strategies 8.6 Multi-PRMA System Goal: Use multiple PRMA instances for confluence-based trading Setup (3 PRMA instances on same chart): Instance Period Degree Smoothing Role Fast PRMA 30 3.0 TEMA, 3, 1 Entry trigger Medium PRMA 80 2.5 EMA, 5, 1 Trend filter Slow PRMA 200 1.5 SMA, 10, 2 Major trend direction Strategy: text STRONG BUY: ✅ Slow PRMA rising (major uptrend) ✅ Medium PRMA rising (confirmed trend) ✅ Fast PRMA gives "L" signal (entry timing) ✅ Price > all 3 PRMAs STRONG SELL: ✅ Slow PRMA falling (major downtrend) ✅ Medium PRMA falling (confirmed trend) ✅ Fast PRMA gives "S" signal (entry timing) ✅ Price < all 3 PRMAs AVOID: ❌ PRMAs disagree on direction ❌ Price between fast and slow PRMA Markets: All — particularly effective on Daily charts for position trading 8.7 Crossover System with Other Indicators Goal: Combine PRMA with traditional indicators for confirmation PRMA + RSI: text Setup: PRMA (100, 3.0, EMA 5) + RSI(14) Long Entry: ✅ PRMA "L" signal ✅ RSI > 50 (bullish momentum) ✅ RSI not overbought (< 70) Short Entry: ✅ PRMA "S" signal ✅ RSI < 50 (bearish momentum) ✅ RSI not oversold (> 30) PRMA + MACD: text Setup: PRMA (80, 2.5, HMA 5) + MACD(12,26,9) Long: PRMA "L" + MACD histogram positive + MACD above signal line Short: PRMA "S" + MACD histogram negative + MACD below signal line PRMA + Volume: text Setup: PRMA (100, 3.0, VWMA 5) — already volume-aware via VWMA smoothing Long: "L" signal + Volume > 1.5× average volume = HIGH CONVICTION Long: "L" signal + Volume < average = LOW CONVICTION (smaller position) 8.8 Crypto-Specific Use Case Goal: Navigate volatile crypto markets with adaptive smoothing Setup: text Chart: 4H BTC/USDT Period: 60 Degree: 3.5 Smoothing: Gaussian, Length 8, Iterations 2 Strategy: Crypto moves fast → higher degree (3.5) catches reversals quickly Crypto is noisy → Gaussian smoothing + 2 iterations removes whipsaws Only trade signals aligned with Daily PRMA direction Use wider stops (crypto volatility is 3-5× traditional markets) Example — BTC Bull Run: text $40,000 ──────╱── PRMA green, "L" signal → ENTER LONG $45,000 ──╱───── PRMA still green → HOLD $48,000 ──╲───── PRMA turns fuchsia, "S" signal → EXIT $44,000 ──╲───── PRMA still fuchsia → SHORT or FLAT $42,000 ──╱───── PRMA green, "L" → ENTER LONG again 8.9 Portfolio / Asset Allocation Goal: Use PRMA as a filter for risk-on/risk-off decisions Setup: text Asset: SPY (S&P 500 ETF) Period: 200 Degree: 1.5 Smoothing: RMA, Length 20, Iterations 3 Strategy: text Weekly PRMA Rising (Green): → 100% Equities allocation → Overweight growth stocks → Risk-on positioning Weekly PRMA Falling (Fuchsia): → Reduce to 50% Equities → Increase bonds / cash → Risk-off positioning Weekly PRMA Flat / Choppy: → 70% Equities → Diversified allocation → Neutral positioning 8.10 Adaptive Degree Selection Guide Goal: Choose the right degree for current market conditions text Market Condition → Recommended Degree ───────────────────────────────────────────── Strong linear trend → 1.0 - 1.5 Gradual curve/acceleration→ 2.0 - 2.5 Trend with pullbacks → 3.0 - 3.5 Complex / oscillating → 4.0 - 5.0 Very choppy → 1.0 (with heavy smoothing) 9. PARAMETER OPTIMIZATION TABLE Trading Style Timeframe Period Degree Smooth Method Smooth Length Iterations Scalping 1m–5m 20–30 1.0–2.0 TEMA 3 1 Day Trading 5m–15m 30–60 2.0–3.0 HMA 5 1 Swing Trading 1H–4H 50–100 3.0–4.0 EMA 5–8 1–2 Position Trading Daily 100–200 2.0–3.0 Gaussian 8–12 2 Investing Weekly 50–100 1.0–2.0 RMA 10–20 2–3 Crypto Trading 4H 50–80 3.0–4.0 Gaussian 8 2 Forex 1H 60–120 2.0–3.0 DEMA 5 1 Futures 5m–30m 30–60 2.0–3.0 HMA 5 1 Low Noise Any Any 1.5–2.5 SMA 15–20 3–4 Fast Response Any 20–50 4.0–5.0 None – – 10. DEGREE COMPARISON VISUAL text Degree 1.0 (Linear): Price: ╱╲╱──╱╲──╱╲╱╲──╱╲ PRMA: ────────╱────────── Very smooth, slow to turn Signals: ▲ Rare signals Degree 2.0 (Quadratic): Price: ╱╲╱──╱╲──╱╲╱╲──╱╲ PRMA: ──────╱──────╲──── Moderate curvature Signals: ▲ ▼ Balanced signals Degree 3.0 (Cubic): Price: ╱╲╱──╱╲──╱╲╱╲──╱╲ PRMA: ────╱──╱──╲──╲╱─── Catches inflections Signals: ▲ ▲ ▼ ▲ More signals Degree 4.0 (Quartic): Price: ╱╲╱──╱╲──╱╲╱╲──╱╲ PRMA: ──╱╲─╱╲──╲╱╲─╱╲── Very responsive Signals: ▲▼ ▲▼ ▼▲▼ ▲▼ Many signals (may whipsaw) Degree 4.0 + Smoothing (EMA 5, Iter 2): Price: ╱╲╱──╱╲──╱╲╱╲──╱╲ PRMA: ───╱───╱───╲───╲── Responsive but clean Signals: ▲ ▲ ▼ ▼ Filtered, reliable signals ✅ 11. SMOOTHING ITERATIONS VISUAL text Raw PRMA (No Smoothing): ╱╲╱╲╱──╱╲──╲╱╲╱╲──╱╲ Noisy, many direction changes 1 Iteration (EMA 5): ─╱╲╱───╱╲───╲╱╲───╱─ Some noise removed 2 Iterations (EMA 5): ──╱─────╱─────╲────╱─ Much cleaner 3 Iterations (EMA 5): ───╱─────╱──────╲───╱ Very smooth, clear trend 5 Iterations (EMA 5): ────╱──────╱───────╲─ Ultra-smooth, trend only 12. STRENGTHS & LIMITATIONS ✅ Strengths Feature Benefit Non-repainting Reliable for backtesting and live trading — what you see is what you get Fractional degree Unprecedented fine-tuning between integer polynomial degrees 10 smoothing methods Adapt to any market condition or trading style Multi-iteration smoothing Cascaded filtering for noise-free output Precomputed kernel Computationally efficient — fixed weights, simple weighted sum Generalizes LSMA Degree 1 = LSMA; higher degrees capture curves Confirmed signals Price must be on the correct side of PRMA for signal validation Visual clarity Color-coded direction makes trend identification instant ⚠️ Limitations Limitation Mitigation Lag (inherent in all MAs) Use lower period, higher degree, or TEMA/HMA smoothing Overfitting (high degree + short period) Keep degree ≤ period/20 as rule of thumb Whipsaws in ranging markets Increase smoothing iterations or add trend filter No prediction — shows current state, not forecast Combine with leading indicators (RSI, MACD) Runge's phenomenon at extreme degrees Stay below degree 8–10 for practical use Fixed lag offset of length bars This ensures non-repainting — a deliberate trade-off Over-smoothing possible with high iterations Start with 1–2 iterations, increase only if needed 13. QUICK-START RECOMMENDATIONS Beginner Setup (Start Here) text Period: 100 | Degree: 2.0 | Smooth: EMA | Length: 5 | Iterations: 1 → Clean, balanced, works on most markets and timeframes Intermediate Setup text Period: 80 | Degree: 3.0 | Smooth: HMA | Length: 5 | Iterations: 1 → More responsive to curves, low-lag smoothing Advanced Setup text Period: 60 | Degree: 3.5 | Smooth: Gaussian | Length: 8 | Iterations: 2 → Captures complex patterns with natural noise reduction 14. SUMMARY PRMA bridges the gap between simple moving averages and complex curve-fitting analysis. It transforms polynomial regression from a repainting analytical overlay into a practical, non-repainting trading tool with: Fractional polynomial degrees for precision tuning 9 smoothing methods + multi-iteration for adaptive noise reduction Clean directional signals validated by price confirmation Zero repainting guaranteed by fixed kernel architecture Whether you're scalping crypto on a 1-minute chart or managing a portfolio on weekly timeframes, PRMA's configurable parameters can be optimized for your specific trading style and market conditions.
Pine Script® indicator
by ZakAlgoTrade
Pullback SAR ProPullback SAR Pro is a trend-following pullback strategy built around the Parabolic SAR indicator. The script detects pullbacks within an established SAR trend and generates re-entry signals when price resumes the trend direction. To improve signal quality and reduce noise, multiple institutional-style filters are included: • VWAP filter to align trades with intraday bias • Volume filter to confirm participation and avoid low-liquidity moves • Session filter to restrict signals to specific trading hours • Signal limits per session and per trend change • Automatic Take-Profit levels plotted directly on the chart This tool is designed for intraday traders seeking structured pullback entries in trending markets such as indices, futures, or liquid stocks. Best used on lower timeframes (1m–15m) during active trading sessions.
Pine Script® indicator
by szymonsobkowiak
2
Market Gravity: Relative Value Engine--- **Relative Value Model (Enhanced)** This indicator calculates a statistically-derived fair value for your asset by modeling its historical relationship with a reference symbol (default: USDT Dominance). It supports three model types — Linear Range, Linear Regression, and Logarithmic Range — and outputs a prediction line, residual bands, Z-Score signals, and a full metrics dashboard. --- **What Does This Indicator Do?** This indicator builds a statistical price model output by comparing your current chart's price to a reference symbol. It calculates what your asset's price *should* be based on the historical relationship between the two symbols, then measures how far the actual price deviates from that prediction. In short: it answers the question — *"Is this asset overvalued or undervalued relative to a correlated market driver?"* --- **How the Three Models Work** **Linear Range** Maps the reference symbol's high/low range to the current chart's high/low range using a simple slope/intercept formula. Best for assets that move in proportion to the reference linearly. **Linear Regression (Correlation)** *(Default)* Uses Pearson correlation, standard deviation, and rolling means to calculate a beta (slope) and alpha (intercept) — essentially a rolling OLS regression. This is the most statistically rigorous method and handles non-proportional relationships better. **Logarithmic Range** Performs the same range mapping as Linear Range but in log space, then exponentiates back. Ideal for assets with exponential price behavior (e.g., crypto over long timeframes). --- **Dashboard Panel — What Each Row Means** **Regime** — Whether price is above (Premium) or below (Discount) the model. Green = overpriced vs model; Red = underpriced. **Diff %** — Percentage deviation of actual price from predicted price. +5% means price is 5% above the model estimate. **Prediction** — The model's estimated fair price for the current bar. Your fair value anchor. **Z-Score** — How many standard deviations price is from the prediction. Above +2 or below -2 is considered statistically extreme. **Z-Score State** — Normal or Extreme based on your threshold setting. Extreme signals a potential mean-reversion setup. **R²** — R-squared, goodness of fit from 0 to 1. ≥0.6 = Strong, 0.35–0.6 = Moderate, below 0.35 = Weak. Only trust the model when quality is at least Moderate. **Model Quality** — Text label derived from R². Use signals only when this reads Moderate or Strong. **MAE** — Mean Absolute Error in price units. Lower = model tracks price more closely. **MAPE %** — Mean Absolute Percentage Error. Lower percentage = more accurate model overall. **Smoothing** — Shows the active moving average type and length applied to the prediction line. --- **Visual Elements on the Chart** - Yellow line — The predicted fair-value price line - Aqua bands — Upper and lower residual bands (predicted ± multiplier × standard deviation). Price outside these bands is statistically stretched. - Green fill — Premium zone, price is above the model - Red fill — Discount zone, price is below the model - LONG label — Price crossed above the prediction line, bullish regime shift - SHORT label — Price crossed below the prediction line, bearish regime shift - Z+ triangle — Z-Score crossed above the extreme threshold, potential reversal warning - Z- triangle — Z-Score crossed below the negative threshold, potential reversal warning --- **Settings Guide** *Data and Model* - Reference Symbol: Default is USDT Dominance. Try DXY, SPX, BTC, or any asset correlated to your chart. - Reference Timeframe: Leave blank to match your chart, or set a higher timeframe for macro-level signals. - Model Type: Start with Linear Regression. Switch to Logarithmic Range for crypto on long-term charts. - Lookback Period: Use 10–20 on lower timeframes (1H, 4H), and 50–100 on daily or weekly charts. *Smoothing* - Smoothing Type: EMA reacts faster, RMA is smoother, None gives the raw model output. - Smoothing Length: Increase to reduce noise, decrease for more responsiveness. *Signals and Risk* - Residual Band Multiplier: Default 1.5. Try 1.0–2.5. Higher = wider bands, fewer signals. - Z-Score Threshold: Default 2.0. Use 1.5 for more frequent signals, 2.5 for rarer and stronger ones. *Visualization* - All colors, band visibility, and panel on/off are fully customizable. Auto theme detects your chart background automatically. --- **Built-in Alerts** Three alert conditions are included: 1. Z-Score Premium Threshold Crossed — price enters extreme overvalued territory above the model. 2. Z-Score Discount Threshold Crossed — price enters extreme undervalued territory below the model. 3. Price Crossed Model — price crosses the prediction line in either direction, possible regime change. To activate, go to Alerts → Create Alert → Condition → select this indicator. --- *This indicator is for educational and analytical purposes only. Not financial advice.*
Pine Script® indicator
by hasanaksoy199264
3
Sector Correlation Matrix [LuxAlgo]The Sector Correlation Matrix indicator provides a quantitative measure of the statistical relationship between a selected asset and a benchmark to help traders identify market synchronization and relative strength. 🔶 USAGE This tool is particularly useful for relative strength analysis. For example, if a stock is "Decoupled" while the benchmark is crashing, it may indicate idiosyncratic strength. Conversely, traders can use "Strong Positive" states to confirm that a price move is part of a broader market trend rather than an isolated event. The indicator categorizes market relationships into five distinct states based on the coefficient value: Strong Positive (> 0.7): High degree of synchronization; the assets move together closely. Moderate Positive (> 0.3): General tendency to move in the same direction. Decoupled / Neutral (-0.3 to 0.3): No significant linear relationship; the asset is moving independently. Moderate Negative (< -0.3): General tendency to move in opposite directions. Strong Negative (< -0.7): High degree of inverse synchronization. 🔶 DETAILS The script utilizes the Pearson Correlation Coefficient to calculate the rolling correlation between the current chart's closing price and a user-defined benchmark (such as SPY, QQQ, or BTC). This statistical method measures the linear correlation between two sets of data, resulting in a value between -1 (perfect inverse correlation) and 1 (perfect positive correlation). The visual output includes a dedicated pane with a correlation oscillator and an on-screen dashboard that provides real-time metrics, allowing for a quick assessment of the current market state without manually comparing multiple charts. // Core Calculation Logic correlationValue = ta.correlation(close, benchClose, corrLenInput) 🔶 SETTINGS 🔹 Logic Settings Benchmark Asset: The ticker symbol to compare the current asset against (e.g., SPY, QQQ, BTCUSDT). Correlation Length: The lookback period used to calculate the Pearson Correlation Coefficient. 🔹 Dashboard Show Dashboard: Enable or disable the on-screen information table. Position: Select the dashboard location (Top Right, Bottom Right, or Bottom Left). Size: Adjust the size of the dashboard text and cells (Tiny to Huge).
Pine Script® indicator
by LuxAlgo
Push-Pull OscillatorPush-Pull Oscillator is a regime oscillator that measures the relative dominance of two LR-derived forces: directional path persistence versus instantaneous mispricing pressure. Conceptually, it’s a spread between a multi-length LR forecast-path imbalance and a multi-length LR residual-imbalance, designed to separate “the model wants to keep walking” from “price is stretched away from fit.” The forecast component is built by chaining the per-length LR forecast point and accumulating signed step changes across lengths, then mapping that to a bias via pos/abs normalization. In practice this behaves like a persistence metric on the implied LR forecast curve: sustained one-sided stepping across lengths produces a strong push reading even when candles are not visually large. The residual component computes the current bar’s deviation from each LR fit (expressed as a percent of price), aggregates positive versus negative residual mass across lengths, and maps that to . This acts like a multi-horizon imbalance of “how far above/below fit” the current bar is, rather than a traditional return/RSI-style momentum. The published oscillator is spread = Residual − Forecast. Positive values indicate residual dominance (stretch/mean-reversion pressure outweighs path persistence), negative values indicate forecast dominance (path persistence outweighs stretch). That framing is deliberate: you’re not reading “trend strength” or “overbought/oversold” directly, you’re reading which side of the push–pull balance is winning, which is often a cleaner control signal for regime switching, filtering entries, or timing partial exits. Two optional power transforms are applied only in spread space to shape the response profile. By default the forecast side uses pow < 1 to emphasize mid-range structure (reduce the need for extreme readings before it matters), while the residual side uses pow > 1 to emphasize tail events (make true dislocations stand out). This lets you tune the oscillator toward “earlier regime detection” versus “only signal when dislocation is real,” without altering the underlying LR computations. Raw mode keeps the full spread range (approximately ); Normalized halves it to an easier viewing range. Practical reads: zero-cross and post-cross acceptance can be treated as regime transitions; large positive spikes often correspond to liquidation/stop-run style dislocations relative to fit; large negative excursions tend to align with persistent directional stepping across horizons. The most useful structural signal is usually compression-to-expansion: when the spread compresses around zero and then expands, you’re often seeing the market pick a side between persistence and mispricing. Divergences are also meaningful here, but interpret them as “balance divergence” (price extends while the residual-vs-forecast balance fails to confirm), which can precede either mean reversion or trend decay depending on which component is fading. If you want transparency, enable component plots to see whether changes in the spread are being driven by forecast-path persistence collapsing, residual pressure building, or both. This makes it easy to build rules like “only fade when residual dominates and forecast is weakening” or “only trend-follow when forecast dominates and residual is muted,” and it plays nicely as a filter layer on top of existing structure/orderflow frameworks rather than trying to replace them.
Pine Script® indicator
by Tradenometry
1
Linear Regression Projection Channel [CongTrader]📌 Indicator Name Linear Regression Projection Channel 📝 Description (chuẩn SEO & Policy-safe) Linear Regression Projection Channel combines a dynamic Linear Regression Channel with pivot-based price projection to help traders visualize trend structure, volatility range, and potential future price zones. The indicator calculates a rolling linear regression to define the central trendline and channel boundaries using standard deviation. In addition, confirmed pivot highs/lows are used to project a possible price path and highlight potential BUY/SELL ZONE areas. This tool is designed for trend analysis, structure recognition, and projection visualization — not as a standalone trading system. ⚙️ Features • Linear Regression Channel • Dynamic trend slope detection • Volatility-based channel width (StdDev) • Pivot-based swing projection • BUY ZONE / SELL ZONE labeling • Clean overlay visualization 📊 How It Works 1️⃣ Regression Channel A rolling linear regression defines the main trend direction and channel boundaries. 2️⃣ Trend Detection Slope > 0 → Uptrend Slope < 0 → Downtrend 3️⃣ Pivot Structure Confirmed pivots identify swing points. 4️⃣ Projection Logic The latest swing slope is extended forward to estimate potential price direction. 5️⃣ Projection Zones BUY ZONE appears in uptrend projections SELL ZONE appears in downtrend projections 🎯 Typical Use Cases ✅ Trend continuation analysis ✅ Pullback context within trend ✅ Visual projection reference ✅ Structure-based confluence ✅ Volatility envelope assessment ⚠️ Important Notes • Pivot signals use confirmed pivots and may appear with delay • Projection is an estimation, not a prediction • Not financial advice • Best used with confluence tools (S/R, Volume, PA…) 👤 Author Created by CongTrader linear regression, regression channel, trend projection, price projection, buy sell zones, market structure, technical analysis
Pine Script® indicator
by CongTrader_
Isotonic Regression Oscillator [LuxAlgo]The Isotonic Regression Oscillator indicator aims to quantify the degree of trendiness and structural complexity in price movement by comparing non-decreasing and non-increasing fits. It uses the Pool Adjacent Violators Algorithm (PAVA) to determine the best-fitting monotonic sequence for a given period, providing a normalized oscillator that highlights the strength and direction of the underlying trend. Note: The isotonic regression fit displayed on the price chart is subject to repainting and is displayed retrospectively to illustrate the most recent calculation window. 🔶 USAGE The indicator consists of an oscillator oscillating between -100 and 100, and a visual fit line displayed on the price chart. 🔹 Interpretation Positive Values: Indicate that a non-decreasing (bullish) fit has a lower Mean Squared Error (MSE) than a non-increasing fit. Higher values suggest a more complex, multi-step bullish structure. Negative Values: Indicate that a non-increasing (bearish) fit has a lower MSE. Lower values suggest a more complex bearish structure. Zero Crosses: A crossing of the zero line indicates a shift in the "best fit" direction, signaling a potential change in the dominant trend bias. 🔹 Fit Complexity The magnitude of the oscillator is determined by the number of "pools" or steps in the regression fit. A value near 100 or -100 suggests a highly granular fit that closely follows the price movement, while values near 0 suggest a very simple, flat, or linear-like monotonic structure. 🔶 DETAILS 🔹 The PAVA Algorithm Isotonic regression involves finding a series of non-decreasing (or non-increasing) values that are as close as possible to the original data points. The script implements the Pool Adjacent Violators Algorithm (PAVA). This algorithm works by iteratively averaging adjacent values that violate the monotonic constraint (e.g., in a non-decreasing fit, if a previous value is greater than the current value, they are pooled together and averaged). 🔹 MSE-Based Selection For every bar, the indicator calculates two regressions: one forced to be non-decreasing and one forced to be non-increasing. It calculates the Mean Squared Error (MSE) for both. The fit with the lower MSE is selected as the representative model for the current price action. 🔹 Normalization The oscillator value is normalized based on the number of unique "pools" (constant segments) found by the PAVA. The formula used is: ((Number of Pools - 1) / (Period - 1)) * 100 This scales the complexity of the trend into a readable range of 0 to 100 (or -100 for bearish fits). 🔶 SETTINGS Period: The lookback window used to calculate the isotonic regression fits. Source: The price data used for the calculations (defaults to Close). 🔹 Style Bullish Color: The color used for the oscillator and fit line when the bullish fit is dominant. Bearish Color: The color used for the oscillator and fit line when the bearish fit is dominant. Fit Line Width: Controls the thickness of the polyline fit displayed on the chart. Fit Line Style: Sets the visual style (Solid, Dashed, or Dotted) of the regression fit line.
Pine Script® indicator
by LuxAlgo
1
Indicator Configuration Forecasting [LuxAlgo]The Indicator Configuration Forecasting tool identifies historical market regimes that share a similar technical configuration to the current market and projects future price action based on those historical outcomes. By encoding multiple technical indicators into a state vector and employing a K-Nearest Neighbors (KNN) search, the script provides a probabilistic forecast including a median path and confidence intervals. 🔶 USAGE The indicator works by "memorizing" the state of various user-selected technical indicators at every bar. When the current bar's configuration matches or closely resembles a previous historical state, the script records how the price moved in the subsequent N bars from that point in time. 🔹 Forecast Interpretation Median Forecast (Dashed Gray): Represents the 50th percentile (median) of all matched historical outcomes. This is the central tendency of the forecast. Upper Bound (Dashed Green): Represents the 75th percentile of historical outcomes, suggesting a bullish boundary for the projected move. Lower Bound (Dashed Red): Represents the 25th percentile of historical outcomes, suggesting a bearish boundary for the projected move. Match Labels: Small labels appearing on the historical price action indicate exactly where the most similar configurations were found in the past. 🔹 Configuration Strategy Users can toggle various indicators to define what constitutes a "similar" market state. For example, if only "SMA Cross" and "Supertrend" are enabled, the script will look for historical periods where the trend relationship and SMA positioning were identical to the current bar, regardless of RSI or MACD values. 🔶 DETAILS The script utilizes a state-encoding methodology to calculate distances between the current market environment and the past. Each enabled indicator is converted into a discrete value (e.g., 1 for bullish, -1 for bearish, 0 for neutral). These values form a vector for the current bar. The algorithm then scans through the "Historical Lookback" period to find the "Top K" neighbors—the points in history where the vector distance to the current state is minimized. To ensure variety in the forecast, the script includes logic to prevent overlapping matches, ensuring that the selected historical points are distinct events. Once the matches are identified, the script calculates the percentage returns for the specified "Forecast Horizon (N)" and projects those returns onto the current price to generate the visual forecast. 🔶 SETTINGS 🔹 Parameters Top K Neighbors: The number of similar historical configurations to include in the forecast calculation. Forecast Horizon (N): How many bars into the future the forecast should extend. Historical Lookback: The maximum number of historical bars the script will search through to find matches. 🔹 Indicator Configuration RSI/SMA/Supertrend/MACD/ADX/etc.: Toggle switches to include or exclude specific technical conditions from the similarity search. RSI: Looks for similar overbought (>70) or oversold (<30) states. SMA Cross: Looks for similar Fast/Slow SMA relationships. Supertrend: Matches the current direction of the Supertrend. MACD: Matches the relationship between the MACD Line and Signal Line. 🔹 Visibility & Style Show Individual Match Paths: When enabled, draws the actual historical price paths from the match points directly on the current chart for visual comparison. Median/Upper/Lower Colors: Customizes the colors of the forecast lines and the shaded confidence intervals. Dashboard: Toggles the information panel showing the number of matches found and forecast confidence.
Pine Script® indicator
by LuxAlgo
Isotonic Regression [LuxAlgo]The Isotonic Regression indicator provides a monotonic fit to price data, ensuring the resulting line is either non-decreasing or non-increasing over a specified lookback period. This tool is particularly useful for identifying underlying trends and significant price plateaus without the lagging or "overshooting" common in standard moving averages or linear regressions. Note: This indicator calculates its values based on a historical lookback window, which means the regression line will repaint as new bars are added and the window shifts. 🔶 USAGE Isotonic regression is used to find the best-fitting line to a set of data points under the constraint that the line must move in a specific direction (always up or always down). This creates a "staircase" effect where the model alternates between trending segments and flat plateaus. 🔹 Direction Modes The indicator offers three ways to determine the fit direction: Auto: Automatically detects the trend by comparing the start and end prices of the lookback period. If the end price is higher, it fits a non-decreasing line; otherwise, it fits a non-increasing line. Non-Decreasing: Forces the fit to only move upwards or stay flat, ideal for analyzing bullish structures. Non-Increasing: Forces the fit to only move downwards or stay flat, ideal for analyzing bearish structures. 🔹 Flat Period Extensions One of the most powerful features of isotonic regression is the identification of "blocks" or price levels where the trend pauses. When the duration of such a plateau exceeds the Flat Period Threshold , the indicator extends a dashed horizontal line to the current bar, highlighting potential support or resistance levels derived from the regression model. 🔶 DETAILS The script implements the Pool Adjacent Violators Algorithm (PAVA) , which is the standard method for computing isotonic regression. The algorithm works by partitioning the data into "blocks." If a subsequent data point violates the monotonicity constraint (e.g., price drops in a "non-decreasing" fit), the algorithm pools the current block with the previous one and calculates a weighted average. This process repeats until the entire sequence is monotonic. For performance efficiency, the indicator utilizes the polyline.new() function to render the regression line as a single continuous object rather than hundreds of individual line segments. 🔶 SETTINGS Lookback Length: The number of bars used to calculate the isotonic fit. Source: The price data used for the calculation (default is Close). Direction: Sets the monotonicity constraint (Auto, Non-Decreasing, or Non-Increasing). Flat Period Threshold: The minimum number of bars a price plateau must last to be highlighted with an extension line. 🔹 Style Fit Bullish/Bearish: Colors for the regression line based on the detected trend. Fit Style/Width: Controls the visual representation (Solid, Dashed, Dotted) and thickness of the main regression line. Ext Bullish/Bearish: Colors for the flat period extension levels. Ext Style/Width: Controls the visual representation and thickness of the plateau extensions.
Pine Script® indicator
by LuxAlgo
1
Rolling Correlation & Breakdown Detector [LuxAlgo]The Rolling Correlation & Breakdown Detector indicator is a specialized "trust meter" designed for statistical arbitrage and pairs trading that monitors the stability of the relationship between two assets to identify when mean-reversion strategies are likely to fail. 🔶 USAGE This indicator functions as a decision filter rather than a standalone entry signal generator. It is intended to be used alongside spread indicators or Z-score models to determine if the underlying relationship between two assets is healthy enough to trade. The script monitors two primary factors: the raw Pearson correlation and the stability of that correlation. This helps traders avoid the "divergence trap," where a price gap looks like a mean-reversion opportunity, but the assets have actually undergone a structural regime shift. 🔹 The Three-State System The indicator categorizes the relationship into three distinct regimes: Healthy (Green): The correlation is high and stable. This is the optimal environment for statistical arbitrage trades. Warning (Orange): The correlation is weakening or becoming volatile. New trades should be approached with caution, and existing positions should be managed tightly. Breakdown (Red): The assets have "divorced." The correlation has collapsed or is moving erratically. In this state, mean-reversion signals should be ignored as the assets are no longer moving in tandem. 🔹 Statistical Arbitrage Filtering Valid Trade: Your spread indicator shows an extreme (e.g., Z-Score > 2) AND the detector is Green. Invalid Trade: Your spread indicator shows an extreme, but the detector is Red. This suggests a "regime shift" where one asset is repricing independently of the other. 🔶 DETAILS While most traders only look at the absolute correlation value, this indicator introduces the concept of Correlation Stability. A pair with a lower but stable correlation is often more tradable than a pair with high correlation that is rapidly collapsing. The script calculates the standard deviation of the correlation over a "Stability Window." If the correlation fluctuates wildly, the stability metric will spike, triggering a Warning or Breakdown state even if the raw correlation value remains relatively high. This acts as a "circuit breaker" to protect traders from macro-driven divergences or structural news events. 🔶 SETTINGS 🔹 General Settings Asset B: The secondary symbol you wish to compare against the current chart symbol. Correlation Length: The rolling lookback window used for the Pearson correlation calculation. Stability Window: The window used to measure the volatility (standard deviation) of the correlation. 🔹 Breakdown Detection Thresholds Healthy Threshold: The minimum correlation value required to be considered in a "Healthy" state. Breakdown Threshold: The level below which the relationship is considered "Broken." Stability Threshold: The maximum allowed volatility in the correlation before the state shifts to a Warning or Breakdown. 🔹 Dashboard * Dashboard: Toggles the visibility of the real-time information table. * Position/Size: Customizes the location and scale of the on-screen dashboard.
Pine Script® indicator
by LuxAlgo
BTC Macro Trend & Valuation [Final Fixed]This indicator is a comprehensive Bitcoin trading system designed to capture both generational bottoms (Macro) and swing trading opportunities (Trend). It simulates institutional on-chain metrics using high-correlation technical moving averages, allowing users to identify "Deep Value" zones and "Trend Invalidation" levels without requiring paid external data. The system combines three core components: 1. Macro Bottom Detector (The Purple Floor) Logic: Simulates the CVDD (Cumulative Value-Days Destroyed) and Realized Price using the 200-Week SMA. Usage: Historically, this line represents the absolute "hard floor" for Bitcoin price. Signal: Displays a red "BOTTOM" label when price dips into the deep value zone (default: 5% below the floor), indicating a high-conviction accumulation zone. 2. Bull Market Support Band (The Trend Cloud) Logic: Simulates the Short-Term Holder Cost Basis using the 20-Week SMA (Green) and 21-Week EMA (Blue). Usage: In a Bull Market: This band acts as dynamic support. In a Bear Market: This band acts as resistance. Signals: "DIP" (Yellow Triangle): Appears when the price retests the band during an uptrend but closes above support. Ideal for "buying the dip." "STOP/EXIT" (Pink Label): Appears when the price closes below the 20W SMA (Green Line), signaling that the bullish trend is broken and it is time to exit or defend capital. 3. Smart Status Dashboard (Top Right) A real-time information panel that provides: Macro Status: Are we in "Deep Value," "Fair Value," or "Overheated"? Current Strategy: Tells you whether to "Buy/Accumulate," "Hold," or "Stay Cash/Stop Loss." Key Levels: Dynamically displays the exact price you should watch. In Uptrend: Displays the Stop-Loss price (Green Line). In Downtrend: Displays the Target Bottom price (Purple Line). How to Trade with this Script: Long Term: Accumulate aggressively when price is near the Purple Line ("BOTTOM" signal). Swing Trade: Enter on Yellow "DIP" signals during a bull run. Risk Management: Exit positions immediately if the Pink "STOP/EXIT" signal appears. Disclaimer: This script is for educational purposes only. It simulates on-chain data using technical analysis proxies. Always do your own research (DYOR). Macro Bottom Detector: 宏观底部探测器（模拟 CVDD/Realized Price）。 Bull Market Support Band: 牛市支撑带（模拟短手成本）。 Smart Status Dashboard: 智能状态面板（右上角那个表格）。 Key Levels: 关键点位（它会根据趋势自动显示“止损价”或者“抄底目标价”）。
Pine Script® indicator
by liuruochen5267a296d56d1da4272
1MF Buy The Dip - StrategyThis is the indicator "1MF Buy The Dip - Levels" but made a strategy so you can backtest the usage on each levels. There are 2 ways to enter: BY QUANTITY If Use Shares option is enabled, the amount of shares to open on each level will come from the values above. If it's disabled, then it will use whatever settings you did on the Properties Tab. The strategy works the following way: @10% discount - a position is open, targeting the previous high @25% discount - another position is open to price average, targeting the same highs. @50% discount & %70% discount, other positions will be opened, targeting the same highs. The volume of these positions will depend on the Shares Levels you defined (if Use Shares option is enabled), otherwise, on whatever settings you have setup on the Properties tab (percentage, amount, or shares itself). It's a Buy the Dip and hold, so there's no stop loss as its expected to be an investing strategy instead of a trading strategy. The look back bars amount is defaulted on 21, which represents 21 days on the daily timeframe (1-month = 30 days high), and from it will start calculating the discount down. You can play with those numbers to see which one is the best efficient for each stock historically. Any question, leave it below.
Pine Script® strategy
by jonathan_1mf
JT EARLY Predictive Regresion Signals🔴 Predictive SELL Trigger when: ✔ Regression slope becomes weaker before price collapse ✔ Regression slope change is negative ✔ RSI is below threshold ✔ Volume is strong This detects early weakening in structure, before price has a big drop. 🟢 Predictive BUY Trigger when: ✔ Regression slope starts turning upward before price rallies ✔ Regression slope acceleration positive ✔ RSI holds above threshold ✔ Volume strong This tries to spot early rotation BEFORE a rally, not after.
Pine Script® indicator
by SpaceMonkeyForOne