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Regressions

Higher High / Lower Low Probability IndicatorOverview The "Higher High / Lower Low Probability Indicator" is an original statistical tool designed to help traders assess the likelihood of trend continuation in price action. By analyzing historical candles, it calculates the probability that the next candle will form a higher high (HH) or lower low (LL) based whether the previous candle expanded higher or lower. This indicator uniquely incorporates handling for inside candles, where it falls back to the bias of the prior candle to maintain continuity in probability assessments. It's particularly useful for momentum traders, swing traders, or those incorporating probabilistic edges into their strategies, providing data-driven insights into potential bullish or bearish continuations without relying on complex oscillators or moving averages. Features Probability Calculations: Tracks occurrences and successes of higher highs and lower lows across the chart's history. For HH: If the previous candle had a higher high than the one before it, it computes the percentage chance the current candle will continue that pattern. The same logic applies to LL for downward trends. Inside Candle Handling: Detects inside bars (where the high is lower and low is higher than the previous candle) and intelligently uses the bias from the candle before the inside bar, ensuring the indicator doesn't skip potential signals. Visual Plotting: Displays the relevant probability (HH in green, LL in red) as a line plot only when the condition is met, helping users quickly identify active probabilities without clutter. Informative Table: A customizable table in the chart shows HH and LL occurrences alongside their respective probabilities, formatted for easy reading. User Inputs: Table Position: Choose from options like "Top Right" (default), "Bottom Left", etc., to place the table where it suits your chart layout. Text Size: Select from "Auto", "Tiny", "Small", "Normal" (default), or "Large" for optimal visibility. All calculations are performed in real-time using Pine Script's historical data access, ensuring efficiency without repainting. How to Use Add the indicator to your chart via TradingView's indicator search. Adjust the "Table Position" and "Text Size" inputs to fit your preferences. Monitor the plotted probability line: Green indicates a potential HH continuation with the displayed percentage; red signals LL probability. Refer to the table for cumulative stats—higher occurrences provide more reliable probabilities over time. Combine with other tools like support/resistance levels or volume for confirmation. For example, a high HH probability (>70%) in an uptrend might signal a buy opportunity. This indicator works on any timeframe and symbol but performs best on charts with sufficient historical data (e.g., daily or higher) to build meaningful statistics. Note that probabilities are historical and not predictive guarantees—always use risk management. Limitations Relies on available historical bars; on very short histories (e.g., new symbols), probabilities may start at 0% until patterns accumulate. Does not account for external factors like news events or volatility spikes. The table updates only on the last bar for performance reasons. This script is open-source for community review and customization.
Pine Script® インジケーター
Resonant_Traderの投稿
S/R Flip Detector [Alpha Confirmed]INDICATOR DOCUMENTATION S/R Flip Detector Horizontal support & resistance with alpha-scored resistance-to-support flip detection Pine Script v5 | Overlay Indicator | Based on Kakushadze (2016) quantitative alpha research Overview Most support and resistance indicators stop at identifying price levels. This one goes a step further: it scores each level against six quantitative alpha signals to determine whether a resistance zone has genuinely converted into support — or whether it is merely testing the level before rejecting again. The distinction matters enormously in practice. A stock returning to a prior resistance level after breaking above it can either be a high-conviction buy (the flip is confirmed, institutions are accumulating at the level) or a trap (the stock is failing to hold, distribution is present, and the level will reassert as resistance). Raw price structure alone cannot tell you which scenario is unfolding. Alpha confirmation can. The six confirmation signals are derived from 101 Formulaic Alphas by Kakushadze (2016), a widely cited quantitative finance paper that catalogues systematic alpha factors for equity trading. Each signal was selected specifically because it captures a dimension of market behavior that is meaningfully different from the others — together they form a multi-layered confirmation framework. How It Works Step 1 — Pivot Detection The indicator uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions to identify structurally significant price points. A pivot high at bar i means the high at that bar was the highest point within ±pivot_left bars on the left and ±pivot_right bars on the right. These are the swing highs and swing lows that form the skeleton of price structure. Step 2 — Zone Clustering Individual pivots that fall within atr_merge × ATR(14) of each other are merged into a single zone. This prevents the same price level from appearing as three separate zones at slightly different prices. The zone stores its representative price (running mean of all member pivots), upper and lower bounds, total touch count, and a breakdown of how many touches were pivot highs versus pivot lows. Step 3 — Classification Each zone is classified on every bar as one of four types: ★ FLIPPED Was resistance (≥2 pivot high touches), price held above it, and has returned from above with alpha score ≥ threshold ◎ FLIP? Price structure confirms a flip but alpha score is below the minimum threshold — watch closely SUP Zone is below current price with predominant pivot low touches RES Zone is above current price with predominant pivot high touches Step 4 — The Flip Condition A zone qualifies as FLIPPED when all four of the following structural conditions are simultaneously true: • Prior resistance: The zone has at least 2 pivot high touches, and the price approaching the zone historically came from below. • Breakout and hold: Price has closed above the zone's upper bound on at least 2 consecutive bars — confirming acceptance, not a wick through. • Return to zone: Price has subsequently come back to within 1 ATR of the zone from above — testing whether it now holds as support. • Alpha confirmation score: At least 2 of the 6 alpha signals are actively confirming the flip (configurable). Step 5 — Alpha Scoring When price is near a zone, six alpha signals are evaluated against the current bar. Each signal that passes its threshold contributes 1 point to the zone's confirmation score (maximum 6). The score is preserved at the highest value seen while price was near the zone. The Six Alpha Confirmation Signals Each signal was chosen because it captures a distinct dimension of what a genuine resistance-to-support flip looks like from an institutional and quantitative perspective. Alpha Signal Threshold Direction What It Confirms 43 high_vol_washout > 0.55 Bullish Volume surging at the zone on the retest. High percentile-ranked volume on a prior price decline — the hallmark of capitulation and institutional absorption. 101 candle_body_strength > 0.30 Bullish Price closing well above the open at the zone. A strong candle body means acceptance, not just a wick through. Buyers are in control at end-of-day. 34 calm_dip_reversion > 0.55 Bullish Short-term volatility compressing relative to medium-term volatility at the zone, combined with a recent close decline. The market is coiling quietly — a healthy retest pattern. 9 trend_regime_switch > 0.0 Bullish The 5-day price delta pattern is net positive. All recent daily moves agree directionally. The macro context supports the flip holding. 53 stochastic_decay > 0.0 Bullish The stochastic ratio (close position within the high-low range) has been deteriorating — meaning sellers have been progressively exhausted at this level. 3 discount_accumulation > 0.30 Bullish Opening prices and volume are negatively correlated over the past 10 bars — the signature of institutions buying at discounted opens. Smart money is present at the level. NOTE Alpha 43 and Alpha 3 are the highest-conviction individual signals. A zone with both firing simultaneously — high-volume washout combined with institutional discount accumulation — represents the strongest possible confirmation of a genuine flip. Reading the Chart Zone Boxes Each identified zone is drawn as a coloured box spanning its price range, extending to the right for a configurable number of bars. The box colour immediately communicates the zone type: • Bright green (solid border): Confirmed flip — resistance that has converted to support with alpha confirmation. Highest priority. • Dim green: Potential flip — price structure suggests a flip but alpha score is below the minimum threshold. Watch for score to rise. • Blue: Active support zone — price is above the zone with predominant pivot low touches. • Red: Active resistance zone — price is below the zone with predominant pivot high touches. Zone Labels Each box carries a label showing the zone type, representative price, touch count breakdown (H = pivot highs, L = pivot lows), and alpha score (e.g. ). Labels appear to the right of the most recent bar and update in real time. Green Background When the current bar is within proximity of a confirmed flip zone, the candle background turns a soft green. This is a real-time alert that price is at an actionable level — no need to scan visually for relevant zones. Alpha Signal Table A compact table in the bottom-right corner displays the live value of all six alpha signals with a ✓ or · pass indicator and the total score. This lets you verify at a glance what is driving (or preventing) a zone's confirmation score on the current bar. Settings Reference Zone Detection Setting Default Description Pivot lookback 10 Bars to the left that must be lower (for a pivot high) to qualify the point as a significant swing. Pivot lookforward 10 Bars to the right that must be lower to confirm the pivot. Note: this means pivots are confirmed 10 bars after they form. Min touches 2 Minimum number of pivot contacts required to form a meaningful zone. Increase to 3 for higher-conviction levels only. Zone merge width 0.5× Two pivots within this fraction of ATR(14) are merged into one zone. Increase if you see too many adjacent zones. Near-zone proximity 1.0× Price must be within this many ATRs of a zone to trigger alpha scoring and background highlighting. Max zones 10 Maximum number of zones tracked simultaneously. Oldest zones are dropped when this limit is reached. Flip Detection Setting Default Description Min alpha score 2 Minimum number of the 6 alpha signals required to classify a flip as confirmed. Raise to 3-4 for stricter confirmation. Lower to 1 for more sensitivity. Resistance lookback 60 How many bars back to examine when determining whether a zone was acting as resistance historically. Alpha Thresholds Setting Default Description 43_ vol washout 0.55 Percentile rank threshold for the volume-washout signal. Higher values require more extreme volume surges. 101_ candle body 0.30 Fraction of the high-low range that the close-open difference must exceed. 0.30 means the candle body is 30%+ of the full range. 34_ calm dip 0.55 Percentile rank threshold for the volatility compression signal. 3_ discount accum 0.30 Correlation threshold for the institutional accumulation signal. Display Setting Default Description Show Support zones On Toggle blue support zone boxes. Show Resistance zones On Toggle red resistance zone boxes. Show Flipped zones On Toggle confirmed flip zones. Show unconfirmed flips On Toggle potential flip zones (score below threshold). Show alpha scores On Display the score on zone labels. Extend zones right 40 How many bars to extend zone boxes to the right of the last bar. Highlight near-flip bars On Green background when price is near a confirmed flip zone. Alerts Two built-in alert conditions are included, configurable from the TradingView Alerts panel: ALERT 1 Near Confirmed Flip Zone — fires when the current bar is within proximity of a zone classified as a confirmed resistance-to-support flip. This is the primary trade signal alert. ALERT 2 Alpha Confirmation Score Met — fires when the overall alpha score for the current bar crosses the minimum threshold. Use this as a secondary confirmation that conditions are favourable even outside a specific zone. To set an alert: right-click the indicator name on the chart → Add Alert → select the condition from the dropdown. Suggested Usage Timeframes The indicator performs well on daily and 4-hour charts where pivots have structural significance. On daily charts, increase the pivot window to 12–15 bars to capture only major S/R levels. On intraday (1H and below), reduce the window to 5–7 and lower the min-touches requirement to 2. Entry Framework A confirmed flip zone provides a defined entry area, not a specific entry price. The suggested approach is: • Wait for the zone label: Price must return to within 1 ATR of the zone after breaking above it. • Check the alpha table: Ideally 3+ signals should be green when price is at the zone. • Entry trigger: Enter on a strong candle body (101_ > 0.40) closing at or above the zone's midpoint. • Stop placement: Below the zone's lower bound. If price closes below the zone, the flip has failed. • Target: Prior swing high or next resistance zone above. Filtering False Flips Not every confirmed flip leads to a continuation. The most common failure mode is when distribution signals (vol_amplified_dist) are present alongside the flip — this means institutions are selling into the recovery rather than buying the dip. If you see the zone confirm but the alpha table shows the stochastic and accumulation signals failing, treat the zone as lower conviction and size accordingly. Timeframe Alignment The most reliable setups occur when a flip zone on the daily chart aligns with a flip zone on the weekly chart — price is returning to a level that has multi-timeframe structural significance. Open the indicator on both timeframes and look for zones at similar price levels. Technical Notes Pine Script Constraints Because Pine Script processes bars sequentially from left to right, zone classification is built incrementally as pivots are detected. A pivot is only confirmed pivot_right bars after it forms — which means confirmed pivots appear with a lag. On a daily chart with the default setting of 10, a pivot from 10 days ago is classified today. This is inherent to Pine Script's architecture and cannot be avoided; it does not affect the quality of zones, only their discovery timing. Zone Memory Zones are stored in Pine Script var arrays that persist across bars. When the max_zones limit is reached, the oldest zone is dropped from the front of the array. If you need to track more historical levels, increase max_zones up to 30. Note that higher values may slow rendering on very long chart histories. Alpha Approximations The six alpha signals in this indicator are time-series implementations of cross-sectional factors from Kakushadze (2016). In the original paper, rank() refers to a cross-sectional percentile rank across all stocks in the universe on a given day. In a single-ticker Pine Script context, rank() is approximated using ta.percentrank() — the percentile position of the current value within its own recent history. This approximation is directionally consistent with the original formulation and effective in practice, but users should be aware it is not identical to a true cross-sectional computation. Academic Foundation The six alpha signals in this indicator are derived from "101 Formulaic Alphas" by Zura Kakushadze (2016), published in Wilmott Magazine. The paper provides a systematic catalogue of alpha factors used in quantitative equity trading, each expressed as a mathematical formula over price, volume, and VWAP series. The specific alphas used here were selected from that catalogue based on their interpretability in the context of price-level confirmation, their coverage of distinct market dimensions (volume, momentum, volatility, institutional flow), and their empirical behaviour at support/resistance zones in back-testing across multiple equity universes. This indicator does not replicate the full cross-sectional ranking methodology from the paper — it applies the factor formulas in a single-ticker time-series context as confirmation signals rather than return predictors. Users interested in the full methodology should refer to the original paper. S/R Flip Detector · Pine Script v5 · Kakushadze (2016) For educational purposes. Not financial advice.
Pine Script® インジケーター
thrilledFalcon14の投稿
CRR FRANKENSTEINCRR Magnet Micro Scalping is a multi-layer trading tool designed to help traders identify liquidity targets, market structure, institutional intent, and high-probability reaction zones in very short timeframes. The script combines several concepts commonly used in institutional price action analysis such as priority liquidity levels, structure shifts, accumulation breakouts, order blocks, and automatic Fibonacci retracements. Its purpose is not to generate automatic buy or sell signals, but to help the trader understand where price is most likely to move and where reactions may occur. The Priority Levels system plots the most important daily liquidity levels on the chart, including the current or previous Day High and Day Low, the previous Day High and Day Low, and the previous day Open and Close. These levels act as natural liquidity magnets and are used by the internal magnet engine to estimate the most probable price target. The Magnet Engine continuously evaluates distance, directional bias, freshness of the level, and market conditions to determine the most likely liquidity destination. The HUT panel displays three simple readings: the current primary magnet level (NOW), the expected directional movement toward that level (DIR), and the next likely liquidity level after the current one (NEXT). Market structure is analyzed through pivot detection to label Higher Highs, Higher Lows, Lower Highs, and Lower Lows. These labels help traders visually understand trend continuation or potential reversals. The script also detects accumulation ranges where price consolidates within a defined block of candles. When price breaks the range with sufficient momentum and volatility, the block changes state and signals a structural breakout (BOS). This helps identify moments where liquidity expansion may begin. An internal institutional confirmation engine operates using a 15-minute timeframe regardless of the chart timeframe. It evaluates liquidity sweeps of the previous day high or low, wick absorption behavior, displacement strength relative to ATR, market structure break confirmation, and optional Fibonacci retest confirmation. This engine produces internal states that help validate whether a move is likely to have real institutional participation rather than being a simple noise breakout. The script also identifies expansion-based Order Blocks on the 1-minute timeframe. These zones appear after strong displacement candles and mark the origin of potential institutional activity. Order Blocks can be used as reaction zones, especially when they align with liquidity levels or Fibonacci retracement zones. The automatic Fibonacci module dynamically detects swing pivots and draws the key institutional retracement levels including 0%, 25%, 50%, 61.8%, 78.6%, and 100%. The 50% level is highlighted because it often acts as the equilibrium level where price decides continuation or rejection. The script also draws extremely transparent buy and sell zones derived from these Fibonacci ranges to visually guide potential reaction areas without cluttering the chart. This indicator is primarily designed for micro scalping environments such as the 1-minute or 5-minute chart, while using higher timeframe information internally to filter noise. Traders typically use the tool by observing where the magnet engine indicates price is likely to move, monitoring market structure changes, and watching for confluence between liquidity levels, order blocks, and Fibonacci zones. The tool is intended to assist discretionary decision-making and should be used together with proper risk management and personal trading rules.
Pine Script® インジケーター
rivero8894の投稿
2
VWAP Rejection + CISD AlertVWAP Rejection + CISD Alert — Full Backtest Table + Entry Time Window This powerful intraday ICT-style indicator automatically detects high-probability VWAP Rejection + CISD setups and gives you everything you need to trade them with precise risk management. Strategy Rules (all must align): VWAP Rejection: Candle body fully above VWAP (bullish) or below VWAP (bearish) with a wick touching VWAP. CISD Confirmation: Strong reversal candle after minimum consecutive opposite candles (default 2), breaking the prior high/low, and occurring within max bars after rejection (default 2). Extra Filters: CISD candle must open above VWAP (longs) or below VWAP (shorts). CISD candle must close above/below your chosen Moving Average (SMA/EMA/WMA/VWMA – fully adjustable). Entry: At the open of the very next candle after CISD confirmation. Stop Loss: Choose between: Open of the CISD candle (original) Extreme wick of the VWAP rejection candle (low for longs / high for shorts) Take Profit: User-defined multiplier (default 2R) from entry. Visuals & Tools: Small REJ↑ / REJ↓ labels on rejection candles Large lime/fuchsia CISD↑ / CISD↓ triangles on confirmation Detailed ENTRY LONG/SHORT labels showing exact Open, SL, and TP prices Horizontal lines (Entry dashed blue, SL red, TP green) starting at the CISD candle and automatically stopping when price hits SL or TP Yellow TP and Blue SL hit triangles marking exact exit candles Live Performance Table (top-right) showing: Total Trades Wins / Losses Win Rate % Current TP Multiplier Key Inputs: CISD Settings: Min consecutive candles, Max bars after rejection Risk Management: TP Multiplier, SL Placement (2 options) Moving Average Filter: Length + Type (SMA/EMA/WMA/VWMA) Time Filter: Entry Time Window (default 8:00–11:00 AM EST) Visual toggles for labels, lines, and CISD shapes Alerts: Set alerts on “CISD Confirmed → LONG Setup” or “SHORT Setup”. Alerts fire the moment the CISD candle closes — perfect timing to enter at the next open. Ideal for 1m–15m charts on indices, forex, and futures. Combines classic VWAP rejection with ICT CISD concepts plus strict filters for cleaner, higher-probability trades.
Pine Script® インジケーター
Resonant_Traderの投稿
Z-score filter Daily/Weekly# Z-Score Filter — Daily / Weekly **Identifies statistically extreme price dislocations from a linear regression trend using a standardized residual z-score, firing high-precision mean-reversion entries at historically rare extremes.** --- ## What It Does Fits a linear regression to `close` over a configurable lookback and offset, then standardizes the residual of current price against that trend using a rolling standard deviation — producing a classical z-score of price deviation. Signals fire when the z-score crosses back through extreme upper or lower thresholds (default: ±5.1 / ±4.7), identifying price dislocations far enough into the tail distribution to represent genuine mean-reversion opportunity rather than noise. The offset parameter decouples the regression anchor from the current bar, eliminating the lookahead that plagues most regression-based overlays. --- ## Theoretical Foundations - **Ordinary Least Squares (linear regression):** Minimizes squared residuals to produce a best-fit price trend; `ta.linreg(close, length, offset)` with non-zero offset is non-repainting by design. - **Standardized residuals / z-scores:** Residual normalized by the rolling standard deviation of `close`; values beyond ±3σ are statistically rare under a normal distribution (~0.3% frequency), making the default thresholds (4.7–5.1σ) extremely selective. - **Mean-reversion in financial time series:** Grounded in error-correction dynamics — when price overshoots its equilibrium trend, restoring forces (liquidity, arbitrage, position unwinds) tend to pull it back. High σ thresholds act as a filter for only the most dislocated conditions. - **Signal polarity:** Crossover (z-score rising back through −lower) = **bullish** (price recovering from extreme negative dislocation). Crossunder (z-score falling back through +upper) = **bearish** (price rolling over from extreme positive dislocation). --- ## Signals | Signal | Condition | Interpretation | |---|---|---| | 🟢 **Deep Value (BUY)** | `zscore` crosses **above** `−lower` threshold | Price has been at extreme negative residual and is reverting toward trend — mean-reversion long entry | | 🔴 **Over Value (SELL)** | `zscore` crosses **below** `+upper` threshold | Price has been at extreme positive residual and is rolling back toward trend — mean-reversion short/exit entry | | ⬜ **No Signal** | `zscore` inside threshold band | Price within statistically normal range relative to trend; no actionable dislocation | --- ## Key Inputs | Input | Default | Type | Guidance | |---|---|---|---| | **Timeframe** | `D` | Dropdown (D / W) | `D` for swing entries; `W` for position-sizing filter or macro regime context. MTF security call pulls higher-TF data cleanly. | | **Linear Regression Length** | `21` | Integer | Controls the lookback window for trend fitting and σ estimation. Shorter (10–15) = more responsive, noisier. Longer (34–55) = slower, fewer signals but higher quality. | | **Linear Regression Offset** | `30` | Integer | Shifts the regression anchor back N bars, ensuring the fitted value at bar is based on historical data only — critical for anti-repainting. Do not set to 0. | | **Plot Linear Regression Line** | `true` | Boolean | Toggle the blue regression overlay. Disable to reduce chart clutter when stacking indicators. | | **Upper Threshold** | `5.1` | Float | Bearish trigger level (σ above trend). Increase to 5.5–6.0 on higher-volatility assets (altcoins, meme coins). | | **Lower Threshold** | `4.7` | Float | Bullish trigger level (σ below trend, stored as positive value, applied as negative). Slightly lower than upper to account for the well-documented negative skew in crypto. | **Threshold calibration guidance:** On BTC/ETH at daily resolution, 4.7–5.1σ yields 1–4 signals per year — true tail events. Reduce to 3.0–4.0 for higher-frequency assets or 4H charts with the understanding that signal quality degrades. --- ## Dashboard / Visual Elements | Visual Element | Description | |---|---| | **Blue line (Linear Regression)** | Best-fit OLS trend over `length` bars, anchored `offset` bars back. Toggleable. | | **Green cross + "BUY" label (below bar)** | Deep Value signal — z-score crossover through `−lower` | | **Red cross + "SELL" label (above bar)** | Over Value signal — z-score crossunder through `+upper` | *No dashboard table. This is an overlay-only signal indicator — no separate pane required.* --- ## Data Sources | Source | Ticker / Field | Usage | |---|---|---| | Chart symbol | `close`, `volume` | Primary price series and volume (built-in, no `request.security()` calls) | **`request.security()` budget:** **0 calls.** This indicator uses only the native chart series. The timeframe input switches chart context via the timeframe parameter on `ta.linreg` — note that standard Pine Script indicators do not auto-request the selected TF; for true MTF operation, a companion wrapper using `request.security()` is needed. --- ## Alerts | Alert Name | Trigger | Suggested Use | |---|---|---| | **Deep Value** | `zscore` crosses above `−lower` | Long entry watchlist — confirm with volume or funding rate context before execution | | **Over Value** | `zscore` crosses below `+upper` | Short entry / long exit watchlist — higher false-positive rate in strong trends; use regime filter | Both alerts use `alertcondition()` (static presets). Compatible with TradingView webhook delivery to execution systems. --- ## Important Notes **Anti-repainting:** The non-zero `offset` (default: 30) is the critical anti-repainting mechanism. The regression is evaluated at `bar_index - offset`, meaning it is computed entirely from historical bars at the time it fires. **Do not set offset to 0** — this creates lookahead bias where the regression re-fits to include the current bar, causing historical signals to shift position on replay. The signal shapes (`plotshape`) are plotted on confirmed close data. **Recommended timeframes:** Daily and Weekly. The default thresholds (4.7 / 5.1σ) are calibrated for daily BTC/ETH behavior. On intraday charts, reduce thresholds significantly or the indicator will rarely trigger. Can be used on any timeframe. **Asset scope:** Optimized for crypto majors (BTC, ETH, SOL, XRP). Apply cautiously to high-beta altcoins — the σ distribution has fatter tails, so fixed thresholds will be hit more frequently and signal quality degrades. Consider switching to adaptive percentile-based thresholds (97th/95th percentile of rolling |z|) for non-major assets. **Signal frequency expectation:** At default settings on BTCUSD daily, expect 1–5 signals per year. This is intentional — these are designed as high-conviction tail-event entries, not a frequent signal system. **Trend vs. mean-reversion regime:** This indicator performs best in ranging / oscillating markets. In strong directional trends, "Deep Value" signals may be sequentially triggered as price continues lower — always context-check against a trend/regime classifier before trading mechanically.
Pine Script® インジケーター
whitekidspazの投稿
VWAP slope (normalized)**Normalized VWAP Slope (Session-Based Regime Filter)** This indicator measures the slope of the session VWAP using a linear regression model and normalizes it by ATR. The goal is to identify whether the market is in a **balanced (range) state** or in a **directional (trend / discovery) state**. The script calculates the slope of the VWAP regression line over a configurable lookback period and divides it by the current ATR value. This normalization makes the slope comparable across different instruments and volatility environments. To avoid unstable readings at the start of a session, the indicator includes a **warm-up filter** that ignores the first N bars after the daily session reset. **How it works** 1. Session VWAP is calculated using TradingView's built-in VWAP function. 2. A linear regression is applied to the VWAP over the selected lookback length. 3. The difference between consecutive regression values produces the VWAP slope. 4. The slope is normalized by ATR to account for changing volatility. 5. During the warm-up period after the session reset, values are suppressed to prevent distortions caused by the VWAP initialization. **Interpretation** The normalized slope represents how steep the VWAP is relative to normal market volatility. Typical interpretation: * Values near **0** → VWAP is flat → market is likely in **balance / range** * Moderate positive or negative values → **developing directional bias** * Large absolute values → **strong directional move / information driven market** **Typical threshold usage** Many mean-reversion strategies use thresholds to determine when range trading is allowed. Example guideline: For Intraday Session * `|slope| < 0.01`and |slope| > -0.01 → Balanced market * `|slope| > 0.01`or |slope| < -0.01 → Directional market (range trading discouraged) These thresholds should be adjusted depending on the instrument and timeframe. **Inputs** * **LinReg Length** – Lookback period used for the VWAP regression slope. * **Warm-up Bars** – Number of bars ignored after a new session begins. * **ATR Length** – Period used for volatility normalization. * **Upper / Lower Threshold** – Reference levels used to identify balanced vs directional conditions. **Purpose** This tool is designed primarily as a **market regime filter**, especially useful for strategies that rely on mean reversion around VWAP. By detecting when the VWAP becomes steep relative to normal volatility, traders can avoid applying range strategies during strong directional moves.
Pine Script® インジケーター
pavliatiの投稿
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® インジケーター
karpychev_i_sの投稿
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® インジケーター
Resonant_Traderの投稿
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® インジケーター
UAlgoの投稿
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® インジケーター
WillyAlgoTraderの投稿
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® インジケーター
BINUT_BNTの投稿
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® インジケーター
ZakAlgoTradeの投稿
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® インジケーター
szymonsobkowiakの投稿
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® インジケーター
hasanaksoy199264の投稿
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® インジケーター
LuxAlgoの投稿
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® インジケーター
Tradenometryの投稿
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® インジケーター
CongTrader_の投稿
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® インジケーター
LuxAlgoの投稿
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® インジケーター
LuxAlgoの投稿
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® インジケーター
LuxAlgoの投稿
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