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Asia & London Session High/Low Description: This indicator plots the highest and lowest points of the Asian and London trading sessions based on Eastern Time (ET). Features: Draws horizontal rays for session highs and lows Automatically resets for each session Perfect for I CT-style liquidity analysis , range breaks , and session-based trading setups Clean chart : no labels or clutter, just the key session levels Use it to identify liquidity zones , plan entries , and anticipate potential session raids in your trading strategy.
Pine Script® インジケーター
ggeorgiev9pmの投稿
Liquidation Map [Alpha Extract]A sophisticated liquidity distribution visualization system that identifies potential liquidation zones through pivot-based detection and renders them as an interactive histogram with cumulative distance-to-liquidation curves. Utilizing multi-exchange volume aggregation and ATR-scaled pocket detection, this indicator delivers institutional-grade liquidity mapping with real-time histogram display showing relative concentration of long and short liquidation levels across configurable price ranges. The system's box-based rendering architecture combined with cumulative distribution overlays provides comprehensive visual assessment of asymmetric liquidity positioning for strategic trade planning. 🔶 Advanced Multi-Exchange Aggregation Framework Implements intelligent ticker detection and multi-source volume aggregation across major exchanges including Binance, Bybit, KuCoin, OKX, and MEXC for accurate liquidity weight calculations. The system automatically identifies base currency (BTC, ETH, SOL) from chart ticker, retrieves volume data from matching perpetual contracts across multiple venues, and aggregates into composite volume metric for enhanced pocket weighting accuracy. 🔶 Pivot-Based Liquidation Pocket Detection Features sophisticated swing point identification using configurable pivot width with ATR-scaled vertical zone construction for volatility-adaptive pocket sizing. The system detects pivot highs for short liquidation zones (placed above swing) and pivot lows for long liquidation zones (placed below swing), applying 200-period ATR with percentage multipliers to determine pocket heights that adjust to market volatility conditions. 🔶 Interactive Histogram Visualization Engine Provides real-time box-based histogram rendering in indicator pane with configurable bin counts (up to 400 columns) and adjustable height, displaying liquidity concentration across fixed percentage range above and below current price. The system calculates bin sizes from view range, accumulates pocket weights into price bins, and renders vertical bars with gradient color intensity reflecting relative liquidity concentration at each price level. 🔶 Cumulative Distance Overlay System Implements innovative cumulative distribution curves showing aggregate liquidity distance from current price for both long (left) and short (right) positions. The system calculates running totals of pocket weights from current price outward in both directions, normalizes against maximum span, and overlays line segments showing how much total liquidity exists at various distances, enabling instant assessment of liquidation cascade potential. 🔶 Dynamic Price Range Adaptation Features fixed percentage-based view window that maintains consistent price range visualization across all timeframes and instruments, automatically centering histogram on current price with configurable +/- percentage bounds. The system recalculates histogram bins and pocket distributions on each bar close, ensuring visualization adapts to price movement while maintaining interpretable scale regardless of volatility regime. 🔶 Touch Detection and Weight Adjustment Provides intelligent pocket state tracking that identifies when price trades through liquidation zones and applies configurable weight multipliers to touched pockets for historical context. The system monitors price interaction with pocket midpoints, marks pockets as "hit" when violated, and optionally increases their visual weight (default 5x) to emphasize historical liquidation levels while distinguishing from untouched future zones. 🔶 Gradient Intensity Color System Implements sophisticated color gradient engine that modulates bar opacity from transparent to opaque based on relative liquidity concentration within each bin. The system normalizes bin values against maximum liquidity, applies color interpolation from faded to vivid hues, and distinguishes long liquidation zones (cyan) from short liquidation zones (yellow/gold) with current price column highlighted in red for instant orientation. 🔶 Performance-Optimized Rendering Architecture Utilizes efficient box and line object management with dynamic allocation based on histogram configuration, implementing intelligent cleanup and reuse to maintain smooth performance. The system includes adaptive line budget calculations that adjust segment density for cumulative curves based on available object limits, ensuring consistent operation even with maximum histogram resolution settings. 🔶 Asymmetric Distribution Analysis Calculates separate cumulative distributions for long and short liquidation zones split at current price, enabling identification of imbalanced liquidity positioning. The system normalizes distributions against respective maximums and overlays both curves on single histogram, allowing traders to instantly assess whether more liquidation risk exists above (shorts vulnerable) or below (longs vulnerable) current price levels. 🔶 Configurable Label and Scale System Provides price axis labeling with adjustable frequency to reduce clutter while maintaining reference points, displaying price values at regular column intervals with configurable offset positioning. The system includes current price label showing exact value and percentile position within view range, offering both absolute price reference and relative positioning context for distribution interpretation. 🔶 Historical Pocket Persistence Framework Maintains rolling window of liquidation pockets up to 3000 bars with automatic expiration management and optional preservation of touched zones for historical analysis. The system tracks pocket creation time, monitors age against lookback limits, and manages array cleanup to prevent memory overflow while retaining relevant historical liquidation levels for pattern recognition and support/resistance validation. This indicator delivers sophisticated liquidity distribution analysis through histogram visualization and cumulative distance curves that reveal asymmetric positioning of potential liquidation levels. Unlike simple liquidation heatmaps that show absolute levels, the Liquidation Map's cumulative distribution overlays instantly communicate how much total liquidity exists at various distances from current price, enabling assessment of cascade potential. The system's multi-exchange volume aggregation, touch-weighted historical zones, and fixed-range visualization make it essential for traders seeking strategic positioning around institutional liquidity clusters in cryptocurrency futures markets. The histogram format enables instant identification of price levels where concentrated liquidations may trigger significant volatility or reversal events, while the asymmetric distribution curves reveal whether market structure favors upside or downside cascades.
Pine Script® インジケーター
AlphaExtractの投稿
2
Breakeven LECAPs BONCAPsEN Breakeven LECAPs & BONCAPs (ARS → USD) + Futures Curve This indicator plots the breakeven USD/ARS exchange rate for Argentine fixed-rate Treasury instruments LECAPs (S tickers) and BONCAPs (T tickers), showing the USD/ARS level at each maturity where holding the peso instrument would match the performance of holding dollars. What you get • Breakeven labels at (Maturity Date, Breakeven Dollar) • Automatic FX benchmarks: • Dólar MEP: BCBA:AL30 / BCBA:AL30D • Dólar Cable (CCL): BCBA:AL30 / BCBA:AL30C • Optional Custom Dollar input (1000–10000 ARS) • Optional MatbaRofex USD futures labels at their expiry dates • Optional polynomial regression curves for LECAPs, BONCAPs, and Futures (degree 1–4), with independent toggles, colors, and smoothness points Core calculations • Direct Return = (Maturity Price / Last Price) - 1 • TNA (Annualized Rate) = Direct Return × 365 / Days to Maturity • Breakeven Dollar = Current Dollar × (1 + Direct Return) Tooltip (hover labels) Ticker/type, maturity date, days to maturity, current price, maturity price (px_finish), direct return, TNA, and breakeven value. ⸻ ES Breakeven LECAPs & BONCAPs (ARS → USD) + Curva de Futuros Este indicador grafica el tipo de cambio USD/ARS de equilibrio (breakeven) para instrumentos de tasa fija del Tesoro argentino LECAPs (tickers S) y BONCAPs (tickers T). Te muestra a qué nivel de dólar, en cada vencimiento, una inversión en pesos igualaría el rendimiento de quedarse en dólares. Qué muestra • Etiquetas de breakeven en (Fecha de vencimiento, Dólar breakeven) • Referencias automáticas de tipo de cambio: • Dólar MEP: BCBA:AL30 / BCBA:AL30D • Dólar Cable (CCL): BCBA:AL30 / BCBA:AL30C • Opción de Dólar Custom (1000–10000 ARS) • Opción de mostrar futuros de USD MatbaRofex en sus vencimientos • Curvas de regresión polinómica opcionales para LECAPs, BONCAPs y Futuros (grado 1–4), con toggle, color y suavizado configurables por separado Cálculos principales • Retorno Directo = (Precio de vencimiento / Último precio) - 1 • TNA = Retorno Directo × 365 / Días al vencimiento • Dólar Breakeven = Dólar actual × (1 + Retorno Directo) Tooltip (pasar el mouse por las etiquetas) Ticker/tipo, fecha de vencimiento, días restantes, precio actual, precio de vencimiento (px_finish), retorno directo, TNA y valor de breakeven. ==================== DISCLAIMER / AVISO LEGAL ==================== This indicator is for informational and educational purposes only. Eco Valores S.A. does NOT provide investment advice or recommendations. Consult a qualified financial advisor before making investment decisions. Este indicador es solo para fines informativos y educativos. Eco Valores S.A. NO brinda asesoramiento ni recomendaciones de inversion. Consulte con un asesor financiero calificado antes de invertir. ===================================================================
Pine Script® インジケーター
Eco Valoresの投稿
2
LECAPS_BONCAP_LibraryLibrary "LECAPS_BONCAP_Library" getInstrumentCount() getTicker(index)   Parameters:      index (int) getTickerShort(index)   Parameters:      index (int) getMaturityPrice(index)   Parameters:      index (int) getMaturityTimestamp(index)   Parameters:      index (int) getMaturityYear(index)   Parameters:      index (int) getMaturityMonth(index)   Parameters:      index (int) getMaturityDay(index)   Parameters:      index (int) isBoncap(index)   Parameters:      index (int) isLecap(index)   Parameters:      index (int) getInstrumentType(index)   Parameters:      index (int) getDolarFuturesCount() getDolarFuturesTicker(index)   Parameters:      index (int) getDolarFuturesShort(index)   Parameters:      index (int) getDolarFuturesExpiry(index)   Parameters:      index (int) getDaysToMaturity(index)   Parameters:      index (int) getDataSummary(index)   Parameters:      index (int)
Pine Script® ライブラリ
Eco Valoresの投稿
YTD % / Visible Range % TableAUTHOR: Brandon Gum DATE: 2026-01-03 // PURPOSE: // Calculates price-range metrics based on the *currently visible* // portion of the chart. Intended for table-based UI display where // values must be stable and evaluated only on the last bar. // // Originally based on Jeff Sun's ADR price data table. // // METRICS RETURNED: // - Visible High // - Visible Low // - Visible % Range = (Visible High - Visible Low) / Visible Low // - Visible ATRs = (Visible High - Visible Low) / ATR // // IMPLEMENTATION NOTES: // - Logic executes ONLY on barstate.islast to avoid state corruption. // - Visible range is recomputed atomically using a backward loop // bounded by chart.left_visible_bar_time. // - Avoids var-based accumulation and bar-by-bar resets, which are // unreliable when visible window changes. // - ATR is evaluated at the current bar (not averaged over range). // // ASSUMPTIONS / LIMITATIONS: // - Uses chart-visible time boundaries supplied by TradingView. // - Loop upper bound must be sufficiently large to cover max // expected visible bars. // - Intended for display purposes, not signal generation. // // SIDE EFFECTS: // - None. No plots, no drawings, no state persistence.
Pine Script® インジケーター
gumbtgの投稿
Z-Score Momentum Dashboard Z-Score Momentum Dashboard: A Comprehensive Technical Analysis Framework Understanding the Z-Score Momentum Dashboard The Z-Score Momentum Dashboard represents a sophisticated evolution in technical analysis indicators, designed to synthesize multiple analytical frameworks into a singular, coherent probabilistic assessment of market conditions. At its core, this indicator is a multi-dimensional analytical engine that processes price action, volume dynamics, cyclical patterns, and statistical anomalies to generate standardized z-scores that measure how far current market behavior deviates from established norms. Unlike traditional single-metric indicators that examine price through one lens, this dashboard constructs a comprehensive probabilistic model by weighting and combining six distinct analytical domains: Ehlers bandpass filtering for cycle detection, momentum calculations across multiple timeframes, mean reversion tendencies, trend strength measurements, volatility regime analysis, and volume confirmation signals. The indicator operates by first calculating individual scores across each of these six domains, normalizing them into comparable z-score formats, then applying user-configurable weights to create a composite probability score that estimates the likelihood of upward price movement. This probability undergoes statistical transformation through hyperbolic tangent functions to ensure bounded outputs between zero and one, which are then compared against historical baselines to generate the final z-score reading. The z-score itself becomes the primary signal, indicating not just direction but the statistical significance of the current market state relative to recent history. When the z-score exceeds predefined thresholds, it suggests the market has entered a regime that statistically differs from the baseline, implying either strong momentum continuation or potential exhaustion depending on accompanying contextual indicators. The dashboard visualization provides traders with immediate access to critical information through a comprehensive table display that shows historical z-scores over the past five days, current probability assessments, trend classification, momentum measurements, acceleration metrics, and distance from moving averages. This multi-temporal perspective allows traders to observe not just the current state but the trajectory of change, identifying whether momentum is building, plateauing, or reversing. The indicator also generates regime classifications such as "PARABOLIC EXT," "OVERSOLD," "STRONG MOM," and "NEUTRAL," which combine z-score readings with price extension metrics to characterize the current market environment. These classifications directly inform suggested actions, ranging from "Ride trend w/ stops" during strong momentum periods to "Watch for reversal" during oversold conditions with increasing momentum, providing traders with contextually appropriate strategic guidance. The Special Nature of This Analytical Approach What distinguishes the Z-Score Momentum Dashboard from conventional technical indicators is its fundamental philosophical approach to market analysis, which embraces probabilistic thinking rather than deterministic prediction. Most traditional indicators generate binary signals or directional recommendations based on threshold crossovers or pattern recognition, implicitly suggesting certainty about future price movement. This dashboard, in contrast, explicitly models uncertainty by generating probability distributions and measuring statistical significance, acknowledging that markets are stochastic systems where edge comes from systematic bias rather than predictive certainty. By converting diverse technical signals into standardized z-scores, the indicator creates a common language for comparing fundamentally different types of market information, whether that information comes from price momentum, volume patterns, or cyclical oscillations. The pseudo-machine learning architecture embedded within the indicator represents another distinctive feature that elevates it beyond standard technical analysis tools. While Pine Script limitations prevent the implementation of actual neural networks or gradient-boosted decision trees, the indicator approximates ensemble learning principles by treating each analytical domain as a separate "model" whose outputs are weighted and combined. Users can adjust these weights based on their market beliefs or through backtesting optimization, effectively training the indicator to emphasize whichever analytical dimensions prove most predictive in their specific trading context. This flexibility means the same indicator can be configured for mean-reversion trading in range-bound markets by increasing mean reversion weights, or for momentum trading in trending markets by emphasizing trend and momentum components, making it adaptable across varying market regimes without requiring entirely different analytical tools. The integration of John Ehlers' digital signal processing concepts, particularly the bandpass filtering and super smoother functions, introduces engineering-grade analytical precision to financial market analysis. Ehlers' work translates aerospace and telecommunications signal processing mathematics into trading applications, allowing the indicator to isolate specific cyclical frequencies within price action while filtering out noise. This is fundamentally different from simple moving averages or oscillators that indiscriminately smooth price data; bandpass filters can extract the 10-day cycle component separately from the 20-day cycle component, identifying when multiple cycles align or diverge. The inclusion of these sophisticated filters alongside more conventional tools creates a hybrid analytical framework that combines the mathematical rigor of quantitative finance with the practical market wisdom embedded in traditional technical analysis. The dashboard's temporal analysis capabilities provide another layer of analytical depth rarely found in standalone indicators. By displaying five days of historical z-scores alongside current readings, the interface enables pattern recognition at the signal level rather than just the price level. Traders can observe whether z-scores are trending, oscillating, or demonstrating divergent behavior relative to price action. For instance, if price continues making new highs while z-scores decline, this suggests deteriorating statistical support for the advance despite superficial price strength, providing early warning of potential reversals. Similarly, rising z-scores during price consolidation indicate building statistical pressure that may soon manifest as directional movement. This meta-analytical capability transforms the indicator from a simple signal generator into a comprehensive framework for understanding the statistical character of market behavior. Algorithmic Superiority and Technical Advantages The algorithmic architecture of the Z-Score Momentum Dashboard demonstrates several technical advantages that contribute to its analytical power and practical utility. The normalization of disparate technical indicators into standardized z-scores solves a fundamental problem in multi-factor analysis: how to combine indicators with different scales and units into a coherent composite signal. A momentum reading measured in price points cannot be directly compared to an RSI reading measured on a 0-100 scale, nor to a volume ratio measured as a multiplier. By converting each measure into a z-score representing standard deviations from its respective mean, the indicator creates dimensional consistency, ensuring that each component contributes proportionally to the final composite score based on its statistical deviation rather than its nominal value. The use of adaptive baselines through rolling statistical windows provides robustness against regime changes and non-stationary market behavior. Rather than comparing current readings against fixed historical values or statically defined overbought/oversold levels, the indicator continuously recalculates mean and standard deviation estimates over the user-defined baseline period. This approach automatically adjusts to changing volatility regimes, market cycles, and structural shifts in price behavior. During high-volatility periods, the standard deviation increases, requiring larger absolute deviations to generate extreme z-scores, appropriately raising the bar for signal generation. Conversely, during low-volatility periods, smaller absolute movements can generate significant z-scores, maintaining signal sensitivity across diverse market conditions. The composite probability calculation employs mathematically sound transformation functions rather than arbitrary scaling. After weighting and combining individual z-scores into a composite score, the indicator applies hyperbolic tangent transformation to convert the unbounded composite score into a bounded probability estimate between zero and one. The tanh function was chosen specifically because its sigmoid-shaped curve smoothly compresses extreme values while maintaining sensitivity around the center, preventing outlier distortion while preserving information about moderate deviations. This is superior to linear scaling or simple threshold clamping, which can create artificial discontinuities or lose information about the magnitude of extreme readings. The subsequent z-score calculation on this probability distribution creates a second-order statistical metric that measures not just "is probability high?" but "is probability statistically significantly higher than typical?" This layered statistical approach provides more nuanced information than single-stage calculations. The incorporation of acceleration metrics alongside momentum measurements adds a crucial dimension to the analytical framework. While momentum measures the first derivative of the z-score (rate of change), acceleration measures the second derivative (rate of change of the rate of change), identifying inflection points where momentum itself shifts. Markets often reverse not when momentum reaches zero but when acceleration reverses, as this indicates the rate of momentum decay is accelerating even while momentum remains positive. By explicitly calculating and displaying acceleration, the indicator provides early warning of potential trend exhaustion before momentum fully dissipates. This mathematical sophistication mirrors concepts from physics and calculus, applying them to financial market dynamics in ways that enhance predictive capability. The multi-timeframe momentum analysis embedded within the indicator examines price changes over five, ten, and twenty periods, capturing different temporal scales of market behavior. Short-term momentum captures immediate price action and trading range dynamics, while longer-term momentum reflects sustained directional bias and major trend development. By combining these timeframes into a weighted average before calculating z-scores, the indicator synthesizes information across temporal scales, avoiding the myopia of single-timeframe analysis. This approach recognizes that market structure exists simultaneously at multiple frequencies, and robust signals often emerge when momentum aligns across timeframes, while divergences between timeframes can signal pending reversals or consolidations. Predictive Power Through Cyclical Analysis The integration of cyclical analysis into the Z-Score Momentum Dashboard represents one of its most powerful predictive capabilities, leveraging the empirical observation that financial markets exhibit periodic behavior driven by fundamental economic cycles, seasonal patterns, trader psychology, and technical feedback loops. The Ehlers bandpass filters implemented in the indicator specifically isolate cyclical components at 10, 15, and 20-day periods, frequencies that correspond to common trading cycles including bi-weekly, monthly, and quarterly rhythms in market activity. By extracting these specific frequency bands and measuring their slope, the indicator identifies when cycles are aligned in the same directional phase versus when they are diverging, with aligned cycles providing stronger predictive signals than single-frequency readings. Cyclical analysis offers predictive power because cycles, by definition, have characteristic wavelengths that enable forecasting of future turning points based on the current phase. If the indicator detects that the 10-day cycle is in a trough phase while the 20-day cycle is also declining, it can anticipate that the shorter cycle should begin turning upward before the longer cycle, potentially creating a bullish divergence or early reversal signal. Conversely, when a shorter cycle reaches a peak while longer cycles continue rising, this suggests the current rally may consolidate before the longer-cycle momentum can drive new highs. This phase relationship analysis transforms cyclical information from descriptive to predictive, allowing traders to position ahead of probable turning points rather than merely reacting to them. The bandpass filtering approach is particularly valuable because it separates signal from noise more effectively than conventional smoothing techniques. Traditional moving averages suppress both high-frequency noise and the actual signal being measured, creating lag and reducing responsiveness. Bandpass filters, in contrast, selectively attenuate frequencies outside the target band while preserving amplitude and phase information within the band, maintaining the timing and magnitude of the actual cyclical component. This means when the bandpass output changes, it reflects genuine change in the underlying cycle rather than random noise or smoothing artifacts. The z-score normalization of bandpass slopes then measures whether the current cyclical momentum is statistically unusual relative to recent history, identifying periods when cyclical forces are particularly strong or weak. The integration of Fisher Transform calculations further enhances cyclical predictive power by converting price oscillations into a nearly Gaussian probability distribution. Financial price data typically exhibits non-normal distributions with fat tails and skewness, which violate the assumptions underlying many statistical techniques. The Fisher Transform specifically addresses this by mapping the price data onto a normal distribution where standard statistical inference tools work more reliably. When applied to cyclical data, this transformation makes it possible to accurately assess the statistical significance of cycle phases and turning points, distinguishing between normal cyclical oscillation and statistically significant deviations that may precede major price movements. The Schaff Trend Cycle component adds another dimension to cyclical analysis by combining MACD calculations with stochastic smoothing to identify trending phases within broader cyclical structures. Markets often exhibit fractal behavior where trends exist within cycles which exist within larger trends. The Schaff indicator specifically addresses this nested structure by detecting when shorter-term trends are emerging within the dominant cycle, providing early identification of trend changes before they become apparent in price action. When the Schaff reading aligns with bandpass filter signals and overall z-score direction, it confirms that multiple analytical perspectives agree on current cyclical phase, increasing confidence in directional predictions. The Detrended Price Oscillator (DPO) calculation removes trend components to isolate pure cyclical behavior, addressing a common challenge in cyclical analysis where strong trends can mask underlying cycles. By comparing current price to a centered moving average, the DPO reveals cyclical patterns that persist regardless of trend direction, allowing the indicator to maintain cyclical awareness in both trending and ranging markets. This is particularly valuable because cycles often continue operating during trends but become invisible to trend-following indicators, yet these cycles can predict pullbacks, consolidations, and acceleration phases within the larger trend. The incorporation of DPO signals into the composite z-score calculation ensures that cyclical information contributes to the final reading even when dominated by strong directional momentum. Practical Trading Application and Strategic Implementation Implementing the Z-Score Momentum Dashboard in practical trading requires understanding both its signal generation logic and the appropriate strategic frameworks for acting on its outputs. The primary trading signal comes from the overall z-score reading relative to the trigger and extreme thresholds, which by default are set at 1.25 and 2.0 respectively. When the z-score exceeds the trigger threshold, it indicates that current market behavior is more than 1.25 standard deviations above the recent baseline, suggesting statistically significant bullish momentum. Traders can interpret this as a regime shift from neutral to bullish conditions, warranting either initiation of long positions or continuation of existing long exposure with trailing stops. The strength of this signal increases when the z-score crosses the extreme threshold, indicating the market has entered a parabolic phase that, while statistically unusual, may represent either climactic buying or unsustainable conditions prone to mean reversion. The regime classifications provide contextual interpretation that modifies how traders should approach z-score signals. A z-score above the trigger threshold combined with moderate price extension from the 20-period moving average generates a "STRONG MOM" regime classification with the recommended action "Ride trend w/ stops," suggesting that traders should maintain directional exposure while using trailing stop-loss orders to protect profits if momentum reverses. In contrast, a z-score above the trigger threshold but with extreme price extension generates a "PARABOLIC EXT" classification with the action "Mean rev UP expected," warning that despite strong statistical momentum, the price has deviated too far from its moving average and may soon consolidate or reverse toward the mean. This nuanced interpretation prevents traders from blindly chasing extended moves even when z-scores remain elevated. The trend classification system—identifying RISING, FALLING, BOTTOMING, and TOPPING patterns—provides crucial information about the trajectory of statistical momentum rather than just its current level. A RISING classification indicates that not only is the z-score positive, but it has been consistently increasing over recent periods, suggesting accelerating momentum and increasing statistical support for directional movement. Traders can use this to distinguish between stable momentum that may continue and deteriorating momentum that may reverse, informing position sizing and stop-loss placement decisions. BOTTOMING and TOPPING classifications specifically identify potential inflection points where the direction of z-score movement is changing, generating early reversal signals before z-scores cross back through neutral territory. For mean reversion traders, the indicator provides exceptional value when z-scores reach extreme negative levels (below -2.0) while showing BOTTOMING trend patterns and positive acceleration. This combination suggests that statistical momentum has reached an extreme oversold condition and is beginning to reverse, creating favorable risk-reward opportunities for counter-trend long positions. The extension metric provides additional confirmation, as extreme negative extension from the moving average creates mechanical pull toward the mean independent of momentum considerations. Traders can enter positions when these factors align, using the moving average as an initial profit target and the z-score returning to neutral as a signal for position closure or transition to trend-following mode. For trend-following traders, the indicator is most valuable when z-scores remain elevated above the trigger threshold for extended periods with RISING or stable trend patterns and positive momentum readings. This indicates persistent statistical support for the trend rather than a temporary spike, justifying larger position sizes and wider stop-loss placement. The momentum and acceleration metrics help trend followers distinguish between healthy trends with sustained momentum and exhausted trends where momentum is decelerating, allowing for timely exit before reversals occur. When momentum and acceleration both turn negative while z-scores remain positive, it signals that the statistical foundation of the trend is eroding even though the trend nominally persists, prompting trend followers to tighten stops or take partial profits. The component scores displayed in the dashboard enable advanced traders to perform qualitative analysis of what factors are driving the composite z-score reading. If the composite z-score is positive but the breakdown shows that bandpass and momentum scores are negative while mean reversion scores are strongly positive, this indicates that the bullish reading is driven primarily by oversold mean reversion potential rather than directional momentum. Traders can use this information to adjust their trading approach, perhaps favoring short-term reversal trades over longer-term trend follows. Conversely, if all components show aligned readings, it suggests broad-based agreement across analytical dimensions, increasing confidence in the signal and potentially warranting larger position sizes or longer holding periods. Integration with broader trading systems can enhance the indicator's effectiveness. Traders might use the z-score as a filter for other strategies, taking long signals from separate systems only when the z-score is positive or trading reversal patterns only when z-scores are extreme. Alternatively, the indicator can serve as a portfolio allocation tool, increasing equity exposure when z-scores are positive and reducing exposure or shifting to defensive positions when z-scores turn negative. The probability estimates can be directly incorporated into Kelly Criterion or other position sizing formulas, scaling position sizes proportionally to the estimated probability of upward movement adjusted for risk-reward ratios of specific trade setups. Alert conditions built into the indicator provide automated monitoring capabilities, notifying traders when z-scores cross critical thresholds or when trend patterns change from FALLING to BOTTOMING or RISING to TOPPING. These alerts enable traders to monitor multiple instruments without constant chart watching, maintaining awareness of regime changes across a diversified portfolio. The alerts for extreme z-scores specifically warn of potential climactic conditions that may require immediate attention, whether to take profits on existing positions or to prepare for reversal opportunities. The customization options allow traders to optimize the indicator for specific instruments and market conditions. The baseline period parameter controls the lookback window for calculating statistical norms, with shorter periods making the indicator more responsive to recent conditions at the cost of increased noise, while longer periods provide stability but slower adaptation to regime changes. The weight parameters enable traders to emphasize whichever analytical dimensions prove most predictive in their specific markets, potentially increasing trend weights for strongly trending instruments like technology stocks while increasing mean reversion weights for range-bound commodities or currencies. Through systematic backtesting and forward validation, traders can develop instrument-specific configurations that maximize the indicator's predictive accuracy. Ultimately, the Z-Score Momentum Dashboard functions most effectively as a comprehensive analytical framework rather than a standalone trading system, providing rich statistical context that enhances decision-making across diverse trading approaches. Whether used for discretionary trade timing, systematic signal generation, risk management, or portfolio allocation, the indicator's multi-dimensional analysis, cyclical awareness, and probabilistic framework offer traders a sophisticated tool for understanding and responding to statistical patterns in market behavior that persist across timeframes, instruments, and market regimes.
Pine Script® インジケーター
jaydesaiguの投稿
FX Rate Bias US vs EU 2YFX Rate Bias – US vs EU (2Y) This indicator implements a rate-differential based macro bias model using the 2-year government bond yield spread between the United States and Germany. The methodology focuses on the short end of the yield curve, which primarily reflects central bank expectations rather than long-term inflation or risk premiums. By applying light smoothing and a zero-line regime framework, the script classifies market conditions into USD rate advantage or EUR rate advantage states. Calculation logic: Retrieves daily 2Y sovereign yields for the US and Germany Computes the yield differential (US − DE) Applies optional smoothing to reduce noise Uses the zero line as a regime boundary to define relative monetary bias Practical use: This tool is designed to provide directional macro context for FX analysis, particularly for EURUSD. It helps traders align technical setups with prevailing interest rate expectations, and is not intended as a standalone signal or timing indicator.
Pine Script® インジケーター
emiurzの投稿
VSA Quantitative Framework [Research Grade]VSA Quantitative Framework – Objective Effort vs Result This indicator reformulates classical Volume Spread Analysis (VSA) into a fully quantitative, statistically grounded framework. Traditional VSA relies heavily on discretionary interpretation (e.g., “this volume looks high”). This script removes subjectivity by applying statistical normalization and modern market microstructure concepts, allowing effort–result relationships to be evaluated objectively and consistently. The core objective is to measure how efficiently the market converts Effort (Volume) into Result (Price Range / True Range). ⚙️ Methodology (Quantitative Foundation) Instead of using raw values, the indicator computes Z-Scores (standard deviations from a rolling mean) for: Log-normalized Volume (Effort) True Range (Result) This normalization makes volume and range comparable across regimes and volatility conditions. Additionally, an efficiency metric inspired by the Square Root Law of Market Impact is used, reflecting the empirical relationship between traded volume and price movement described in market microstructure literature (e.g., Kyle’s Lambda). Each bar is classified objectively into one of four VSA quadrants. 📊 VSA Quadrant Classification 🔴 The Squat – Inefficiency / Absorption Logic: High Effort (elevated Volume Z-Score) + Low Result (Range below average) Interpretation: Significant trading activity fails to produce proportional price movement, suggesting absorption by passive liquidity (e.g., iceberg or limit orders). Commonly observed near distribution/accumulation zones and potential reversal areas. Visualization: Red X marker on the bar. 💎 The Glide – High Efficiency / No Resistance Logic: Low Effort (low Volume Z-Score) + High Result (elevated Range Z-Score) Interpretation: Price moves with minimal volume, indicating a lack of opposing liquidity (liquidity vacuum). This is typically a high-quality continuation signal in directional markets. Visualization: Turquoise diamond marker. 🔵 The Drive – Trend Validation Logic: High Effort + High Result Interpretation: A healthy, well-supported directional move, often associated with institutional participation. This state is primarily contextual rather than a direct entry signal. 🕒 Session Filter – New York Focus To reduce noise and regime distortion from overnight trading, the indicator includes an integrated session filter. Default session: 10:00 – 16:00 New York Time Key design choice: The first 30 minutes of the NY open (09:30–10:00) are intentionally excluded due to frequent failed auctions, opening volatility spikes, and initial liquidity imbalances. Statistical calculations continue in the background across all bars to preserve correct rolling distributions, while signals and bar coloring are displayed only during the active NY session. The session filter can be disabled to display signals across all trading hours. 🚀 Practical Use Cases Reversal Context: Squat signals occurring near key levels (FVGs, order blocks, structural highs/lows) may indicate absorption and potential exhaustion. Continuation Context: Glide signals following a pullback often confirm low resistance and trend continuation. This indicator is designed as a contextual and confirmation tool, not as a standalone mechanical trading system. ⚠️ Disclaimer This script is provided for educational and research purposes only. Trading involves substantial risk and is not suitable for all participants.
Pine Script® インジケーター
messaoud_ramziの投稿
NQS Liquidation Map Institutional Suite by INVITiaINTRODUCTION The cryptocurrency market moves by hunting for liquidity. "Stop Hunts" and "liquidation wicks" are not accidents; they are calculated moves to capture retail trader liquidity. NQT Liquidation Map is not just a support and resistance indicator. It is a Market Intelligence tool that visualizes where liquidation orders are hidden (Stop Losses and Leveraged Liquidations), allowing you to trade aligned with Market Makers rather than against them. This is the Hybrid Version, merging two visualization philosophies into a single powerful suite. 💎 VISUALIZATION MODES (HYBRID ENGINE) The indicator features a dual engine selectable from the settings: 1. INSTITUTIONAL MODE (Heatmap & Pools) Visualization: Liquidity boxes ("Pools") that create a heat map on the chart. Behavior: The boxes extend through time until price touches them. When price captures that liquidity, the box automatically disappears, leaving the chart clean. Logic: Uses a "Smart Direction" algorithm that only projects logical liquidations based on volume inflow and the direction of Open Interest. 2. CLASSIC MODE (Lines & Bubbles) Visualization: Dotted lines with label bubbles at the end (25x, 50x, 100x). Style: Ideal for traders who prefer to see exact and discrete price levels instead of zonal areas. 🧠 ADVANCED FEATURES (SMART PROXIES) Unlike other scripts that require external paid data, NQT uses internal Algorithmic Proxies to simulate institutional data in real-time: 📊 Institutional Dashboard: A control panel (HUD) that shows in real-time how many Liquidity Pools are active (Above vs. Below), giving you an instant directional bias. 🌍 Macro Regime Filter: A smart trend filter. If the market is in a bearish structure (Bear Regime), the indicator will filter out weak bullish liquidation signals to prevent you from entering "traps." buzz Social Risk Proxy: Estimates "social heat" (FOMO or Extreme Fear) based on volatility and RSI. It warns you when the market is too extended to keep chasing price. ☠️ Flush Detector: Detects aggressive drops in Open Interest combined with high volume. When the Skull icon (☠️) appears, it indicates that a massive liquidation ("Flush") has already occurred, often marking a local bottom or top. 🛠️ HOW TO USE THIS INDICATOR "Liquidity Hunt" Strategy (Reversal): Identify a dense zone of Boxes/Pools (Institutional Mode) or 50x/100x lines (Classic Mode). Wait for price to make a quick move towards that zone. If price touches the zone and shows rejection (wick), it is a signal that liquidity has been taken. Entry: Trade in the opposite direction of the initial move (Reversal) once the liquidity grab is confirmed. "Breakout" Strategy: Observe the Dashboard. If there is massive liquidity accumulation on one side (e.g., many Shorts trapped above). If the "Macro Trend" supports the direction, that liquidity will act as a magnet (fuel) to push price higher. CONFIGURATION Visual Mode: Choose between "Institutional" (recommended) or "Classic". Data Feed: Select "OI+VOL" for greater precision. Sensitivity: Adjust according to asset volatility (1.0 is standard). ⚠️ Disclaimer: This indicator is a tool for technical analysis and visualization of derivative data. It does not constitute financial advice. Risk management is the trader's responsibility. Powered by INVITia Quantum Algorithms.
Pine Script® インジケーター
INVITia_の投稿
Swing Data [ATR Ext | RVol | ADR | Ticker/Sector RS]Disclaimer : This indicator is not financial advice and is strictly for educational and informational purposes only. The metrics and signals provided herein—including ATR extensions, volume projections, and rolling alpha for relative strength — are calculated based on historical market data and do not guarantee future performance. Trading stocks and commodities involves significant risk of loss. The user assumes full responsibility for all trading decisions and should always perform their own due diligence before executing trades. Hello there. I was inspired after reading this Twitter post by Steve Jacobs regarding the ATR Matrix. I followed Steve's recommendation to the interesting indicator built by @Fred6724 for @jfsrev but I couldn't match my manual calculations to their math. So, I threw together this TradingView indicator to match my own manual calculations for the ATR Extension Multiple. And then, I added more quality-of-life features that I found useful in my daily workflow such as table positioning, specific data streams, threshold customization, and conditional coloring. This became quite a snowball. Daily Chart : Please note that the design for this indicator was focused on the daily chart. Edge case testing has not been fully conducted for other charting periods, although the math should apply agnostically. The calculations of rolling alpha for Ticker RS and Sector RS fetch daily data instead of the displayed chart period, which may affect Ticker RS if you have turned on pre-market and after-market. Relative Strength Differential reveals rolling alpha: One way to read the Ticker RS and Sector RS is... this stock is beating SPY by +75% in the past 63 days and blue color means the stock's outperformance is accelerating but the sector of this stock is beating SPY by a sleepy 3% and orange color means the sector's performance against the broader market is shrinking... so at a glance, we can conclude this is a strong stock in a lagging sector. Status Line : The script outputs the raw ATR Extension value, ATR%, and a Boolean (0/1) for the ATR Extension alert dot directly to the Status Line. This allows you to hover your mouse over any historical candle to see exactly how extended price was on that specific candle, without needing to calculate it manually. These values are coded to display as text only. They provide the data you need without drawing distracting line plots across your price action. In the Style Tab of the indicator settings, you will see checkboxes for these values. Avoid toggling them off and on. Doing so can override the script’s default "invisible" setting and force TradingView to draw unnecessary lines on the chart. Data streams available for turning on/off: ATR Multiple above SMA (default SMA50, default alert on candle >6 multiple, the simple math is Price minus SMA50 and then divide by ATR) ATR Percent (default period length 14) ATR Value Percent Distance from SMA (default SMA50) Projected Relative Volume calculated against Average Volume (default 60 day avg vol) Projected Volume (estimates end of day volume based on current volume at elapsed time) Projected Dollar Volume (estimates end of day turnover based on projected volume x current price... it's a ballpark for gauging liquidity... time arrays for modestly more accurate turnover projection is compute heavy and low signal intel) Average Volume (default 60 day) Average Dollar Volume (default 60 day) ADR Percent (default period length 20 while TradingView prefers 14) ADX (default period length 14) Low of Day Price Dynamic Stop Loss (default Stop MA length 10 and Stop ATR multiple 0.5, adjust at your preference) Market Capitalization (calculates latest Fiscal Quarter's Shares Outstanding x Price) Ticker RS vs SPY (calculates the stock's 63-day rolling performance against the broader market to quantify raw outperformance percentage; the text color signals velocity, turning default blue if the relative strength is flying above the 21-day average of this relative strength or default orange if shrinking below) Sector RS vs SPY (calculates the sector's 63-day rolling performance against the broader market to quantify raw outperformance percentage; the text color signals velocity, turning default blue if the relative strength is flying above the 21-day average of this relative strength or default orange if shrinking below) Sector (basic exception handling such as metal/energy/crypto in ambiguous industries and GICS industry overrides, see code block below) Industry (pulls TradingView's syminfo, truncates when too long) Advanced mapping of the Sector string to a specific ETF, GICS Compliant. // 1. Get Sector and Industry Strings // 'str.lower' converts the description to lowercase to make keyword matching easier (case-insensitive). string sec_raw = syminfo.sector string ind_raw = syminfo.industry string desc_raw = str.lower(syminfo.description) // Default Fallback: If no match is found, we compare against SPY (Market Average). string sec_etf = "SPY" // 2. DEFINE CONDITIONAL GATES (The Safeguards) // CRITICAL: We only want to scan for keywords (like "Silver") if the stock is in a vague industry bucket. // This prevents "False Positives". For example, we don't want "Silvergate Bank" (Regional Banks) // to be accidentally reclassified as a Mining stock just because it has "Silver" in the name. bool is_ambiguous = ind_raw == "Investment Trusts/Mutual Funds" or ind_raw == "Miscellaneous" or ind_raw == "Financial Conglomerates" or ind_raw == "Other Metals/Minerals" or ind_raw == "Precious Metals" // 3. KEYWORD LOGIC (Only runs inside the Gate) // RULE A: COMMODITY TRUSTS (Metals -> XLB) // Fixes: PSLV, PHYS, SPPP, GLD, SLV which are legally "Financial Trusts" but trade like Commodities. // Logic: If it's a Trust AND mentions "Silver/Gold/Bullion", map to Materials ( AMEX:XLB ). bool has_metal = str.contains(desc_raw, "silver") or str.contains(desc_raw, "gold") or str.contains(desc_raw, "bullion") or str.contains(desc_raw, "platinum") or str.contains(desc_raw, "palladium") or str.contains(desc_raw, "precious") // RULE B: ENERGY TRUSTS (Oil/Uranium -> XLE) // Fixes: USO, UNG, SPUT (Uranium). // Logic: Uranium and Oil trusts correlate with Energy ( AMEX:XLE ), not Financials. bool has_energy = str.contains(desc_raw, "oil") or str.contains(desc_raw, "natural gas") or str.contains(desc_raw, "petroleum") or str.contains(desc_raw, "uranium") or str.contains(desc_raw, "crude") // RULE C: CRYPTO PROXIES (Bitcoin/Ether -> XLK) // Fixes: GBTC, IBIT, FBTC. // Logic: Crypto equities currently have the highest correlation with High-Beta Tech ( AMEX:XLK ). bool has_crypto = str.contains(desc_raw, "bitcoin") or str.contains(desc_raw, "ethereum") or str.contains(desc_raw, "crypto") or str.contains(desc_raw, "coin") // 4. EXECUTE KEYWORD MAPPING if is_ambiguous and has_metal sec_etf := "XLB" // Force Metals to Materials else if is_ambiguous and has_energy sec_etf := "XLE" // Force Energy Trusts to Energy else if is_ambiguous and has_crypto sec_etf := "XLK" // Force Crypto to Tech (Risk On) // 5. GICS INDUSTRY OVERRIDES (The "Standard" Fixes) // These rules fix known classification errors where TradingView data lags behind GICS reclassifications. // EXCEPTION: PAYMENT PROCESSORS (The "Visa" Rule - 2023 Update) // Visa ($V), Mastercard ( NYSE:MA ), and PayPal ( NASDAQ:PYPL ) are now Financials ( AMEX:XLF ), not Tech. else if ind_raw == "Data Processing Services" sec_etf := "XLF" // EXCEPTION: COMMUNICATIONS (The "Google/Meta" Rule - 2018 Update) // Separates "Internet" and "Media" stocks ( NASDAQ:GOOGL , NASDAQ:META , NASDAQ:NFLX ) from "Packaged Software" ( NASDAQ:MSFT ). // These belong in Communications ( AMEX:XLC ). else if ind_raw == "Internet Software/Services" or ind_raw == "Advertising/Marketing Services" or ind_raw == "Broadcasting" or ind_raw == "Cable/Satellite TV" or ind_raw == "Movies/Entertainment" sec_etf := "XLC" // EXCEPTION: REAL ESTATE (The "REIT" Rule) // Pulls REITs out of the Financials bucket ( AMEX:XLF ) and into their own sector ( AMEX:XLRE ). else if str.contains(ind_raw, "Real Estate") or str.contains(ind_raw, "REIT") sec_etf := "XLRE" // EXCEPTION: AUTO MANUFACTURERS (The "Tesla" Rule) // Tesla ( NASDAQ:TSLA ), Ford ($F), and GM are Consumer Discretionary ( AMEX:XLY ), not Tech or Industrials. else if ind_raw == "Motor Vehicles" sec_etf := "XLY" // EXCEPTION: INTERNET RETAIL (The "Amazon" Rule) // Amazon ( NASDAQ:AMZN ) and eBay are Consumer Discretionary ( AMEX:XLY ), distinct from generic "Retail Trade" ( AMEX:XRT ). else if ind_raw == "Internet Retail" sec_etf := "XLY" // EXCEPTION: TEXTILES & APPAREL // Nike ( NYSE:NKE ), Lululemon ( NASDAQ:LULU ), and Ralph Lauren are Consumer Discretionary ( AMEX:XLY ). else if ind_raw == "Apparel/Footwear" or ind_raw == "Textiles" sec_etf := "XLY" // EXCEPTION: AEROSPACE & DEFENSE (The "Lockheed" Rule) // Often mislabeled as Tech in some feeds, strictly belongs to Industrials ( AMEX:XLI ). else if ind_raw == "Aerospace & Defense" sec_etf := "XLI" // EXCEPTION: SEMICONDUCTORS // Explicit check to ensure Semis ( NASDAQ:NVDA , NASDAQ:AMD ) always stick to Tech ( AMEX:XLK ). else if ind_raw == "Semiconductors" sec_etf := "XLK" // 6. STANDARD FALLBACKS // If the stock didn't trigger any exception above, map based on the broad Sector name. else sec_etf := switch sec_raw "Technology Services" => "XLK" // Microsoft, Oracle, Adobe "Electronic Technology" => "XLK" // Apple, Hardware "Finance" => "XLF" // Banks, Insurance "Health Technology" => "XLV" // Pharma, Biotech "Health Services" => "XLV" // Managed Care (UNH) "Retail Trade" => "XRT" // Home Depot, Walmart (Retailers) "Consumer Non-Durables" => "XLP" // Coke, P&G (Staples) "Energy Minerals" => "XLE" // Exxon, Chevron (Oil) "Industrial Services" => "XLI" // Construction, Engineering "Consumer Services" => "XLY" // Restaurants, Hotels "Consumer Durables" => "XLY" // Homebuilders, Appliances "Utilities" => "XLU" // Power, Water "Transportation" => "XTN" // Airlines, Rail, Trucking "Non-Energy Minerals" => "XLB" // Steel, Copper, Chemicals "Commercial Services" => "XLC" // Remaining Media/Comms "Communications" => "XLC" // Legacy tag "Distribution Services" => "XLY" // Wholesalers => "SPY" // Final Catch-All
Pine Script® インジケーター
GoldenCosmosの投稿
3
Apex ICT: Proximity & Delivery FlowThis indicator is a specialized ICT execution tool that automates the identification of Order Blocks, Fair Value Gaps, and Changes in State of Delivery (CISD). Unlike standard indicators that clutter the screen, this script uses a Proximity Logic Engine to ensure you only see tradeable levels. It automatically purges old data (50-candle CISD limit) and deletes mitigated zones the moment they are breached, leaving you with a clean, institutional-grade chart.
Pine Script® インジケーター
garethsteadman47の投稿
ICT CISD+FVG+OBThis script is a high-performance ICT suite designed for traders who want a professional, "noise-free" chart. It identifies core institutional patterns—Order Blocks, Fair Value Gaps, and Changes in State of Delivery (CISD)—across multiple timeframes. The script features a proprietary Proximity Cleanup Engine that automatically deletes old or broken levels, keeping your workspace focused only on price action that is currently tradeable. It strictly follows directional delivery rules for CISD and includes a 50-candle "freshness" limit to ensure you never have to manually clear old data from your past bars. Core Features Intelligent CISD: Only triggers Bullish CISD on green candles and Bearish CISD on red candles. Proximity Filter: Automatically wipes away any levels that are "miles away" from the current price. Clean Workspace: Removes broken session highs/lows and mitigated zones instantly. Full Customization: Toggle visibility and colors for every component via the settings menu.
Pine Script® インジケーター
garethsteadman47の投稿
Session Standard Deviations [IbnHindi]Session Standard Deviation⁺ Introduction Session Standard Deviation⁺ is a comprehensive technical analysis tool designed to map key session-based price levels through Fibonacci deviation zones while simultaneously tracking real-time market regime conditions. Built for precision intraday analysis, this indicator combines structured session reference points with volatility-based regime filtering to provide traders with both tactical price zones and macro bias context across any liquid instrument. This indicator does not predict direction or generate trade signals. It operates on confirmed time-based session structures and produces logic-bound visuals designed for traders who understand ICT-based price delivery models and seek consistent visual frameworks for tracking displacement, deviation targeting, and regime-aware decision making. Key Terms and Definitions Session Reference Candle : A specific time-stamped candle that serves as the structural anchor for Fibonacci projections. The tool recognizes four distinct session markers: London Open (4:00 AM), Asia Range (8:00 PM–12:00 AM), New York 8:30 AM, and New York 9:30 AM. Each session's high and low become the baseline for calculating all subsequent deviation levels. Fibonacci Deviations : Price levels calculated as multiples of the session range, extending both above and beyond the reference high and low. Unlike traditional Fibonacci retracements, these deviations project targets at standard levels (0, 0.5, 0.618, 1, 1.618) as well as extended levels (2, 2.25, 2.5, 3, 3.25, 3.5, 4, 4.25, 4.5, 4.618), and their negative equivalents. These zones represent potential areas where institutional orders may cluster during expansion or retracement. Regime Analysis : A multi-factor assessment of current market conditions based on volatility (ATR), directional bias (EMA), and trend strength (ADX). The regime framework categorizes the market into three states: trending bullish, trending bearish, or consolidating. This classification helps traders contextualize whether session-based deviations are likely to act as continuation targets or reversal zones. ATR (Average True Range) : A volatility measurement comparing fast and slow periods to determine whether the market is expanding (regime-high volatility) or contracting (regime-low volatility). When fast ATR exceeds slow ATR, the market is considered to be in an elevated volatility state, which often accompanies displacement moves that respect deviation levels. Trend EMA : A directional filter using an exponential moving average to determine whether price is trading above or below a defined trend anchor. This binary condition helps classify whether the regime is structurally bullish or bearish. ADX (Average Directional Index) : A momentum oscillator measuring trend strength. When ADX is above 25, the market is considered to have sufficient momentum to support regime classification as trending. Below 25 suggests choppy or non-directional conditions (consolidation). Session Box (Asia Only) : A visual range overlay drawn for the Asia session (8:00 PM–12:00 AM), highlighting the consolidation zone that often precedes major market expansion. This box is rendered with customizable opacity and provides a structural reference for overnight price action. Fib Extension Mode : Determines how deviation lines project forward in time. Options include extending right indefinitely, extending a fixed number of bars, or stopping at the session reference point. This allows traders to declutter charts or maintain persistent levels based on their analytical preference. Description At its core, Session Standard Deviation⁺ operates on a two-layer framework: structural deviation mapping and dynamic regime classification. Each qualifying session creates a full matrix of Fibonacci-based price levels, calculated from the session's confirmed high and low. These levels remain active and extend forward until the next session triggers, providing persistent reference zones for intraday price delivery. The tool does not account for partial moves or wick-based touches. Deviation levels are drawn as horizontal lines and remain static once plotted. Labels are positioned to the left of each line by default, displaying the session prefix (LON, ASIA, PRE, NYAM) alongside the deviation multiplier. All labels use a minimal style with no background fill, ensuring clean visual hierarchy. The regime analysis operates independently and updates in real-time on each new bar. A table positioned in the top-right corner displays the current regime classification, live ATR value, and optional ADX strength. The table's background color shifts dynamically—green for bullish regimes, red for bearish regimes, and gray for consolidation—allowing traders to immediately assess whether session deviation zones should be interpreted as continuation targets or reversal areas. The model remains active until the next session reference candle is detected, at which point a new set of deviation levels is generated. Older session levels are automatically cleaned up after 300 objects to prevent performance degradation on lower-timeframe charts. Key Features Multi-Session Structure : Track up to four distinct session types simultaneously—London (4:00 AM 1H candle), Asia (8:00 PM–12:00 AM range), New York 8:30 AM (5m candle), and New York 9:30 AM (5m candle). Each session generates its own color-coded deviation matrix, allowing traders to differentiate between overnight, pre-market, and intraday structural levels. Extended Fibonacci Levels : The tool plots 26 unique deviation levels, including both standard and extended targets. Positive deviations (0 through 4.618) project above the session high, while negative deviations project below the session low. Each level can be toggled individually, enabling traders to focus only on the zones relevant to their strategy. Real-Time Regime Classification : A live regime panel evaluates market conditions using ATR comparison (fast vs. slow), trend EMA positioning, and ADX strength. The regime updates on every bar and displays one of three states: "Reversal to Bullish" (trending up with high volatility), "Bias: Bearish (Hi-Vol)" (trending down with high volatility), or "Consolidating" (low directional conviction). This dynamic classification allows traders to interpret session fibs contextually rather than mechanically. Customizable Color Coding : Each session type is assigned a unique color—purple for London, blue for Asia, and orange for New York pre-market candles. These colors carry through to both the deviation lines and their labels, maintaining visual consistency across timeframes and chart layouts. Flexible Extension Controls : Choose how deviation lines project into the future. "Right N Bars" extends lines a fixed number of bars forward (default 50), "Right" extends indefinitely, and "None" stops extension at the session reference point. This flexibility allows traders to maintain clean charts on busy intraday timeframes while preserving structural context. Minimal Label Design : Labels display session prefix and deviation multiplier (e.g., "LON 2.5" or "NYAM -0.618") with no background fill. Label placement can be toggled between left and right alignment, and padding is customizable to prevent overlap with price action. Session-Specific Box Overlay : The Asia session (8:00 PM–12:00 AM) is rendered as a semi-transparent box spanning its high and low range. This visual aid helps traders identify the overnight consolidation zone and anticipate expansion moves during London or New York open. Timezone Awareness : All session detections are timezone-aware and default to America/New_York. Traders can customize the timezone input to align with their broker's server time or preferred regional standard. Regime Panel Display : The top-right table shows the indicator name, current regime state, live ATR value, and optional ADX reading. The panel's background color shifts with regime changes, providing instant visual feedback without requiring interpretation of numeric values. Memory Management : The tool automatically deletes lines and labels after 300 objects are created, preventing performance issues on lower timeframes while maintaining enough historical context for multi-session analysis. How Traders Can Use the Indicator Effectively Session Standard Deviation⁺ is not a signal generator or automated trading system. It is best used as a visual reference framework for understanding where price may seek liquidity based on session expansion logic and how current volatility conditions contextualize those projections. The tool excels as a companion for: - Mapping session-based expansion targets and retracement zones for ICT-style price delivery analysis - Differentiating between low-probability and high-probability deviation zones based on regime classification - Journaling and reviewing which session structures produce the cleanest reactions across different market conditions - Identifying when price is respecting session fibs as continuation levels (trending regime) versus when deviation zones may act as exhaustion points (consolidation regime) Traders using the tool should be familiar with session-based analysis, Fibonacci extension logic, and the role of volatility in price delivery. The indicator is most effective when combined with narrative, higher-timeframe structure, and discretionary interpretation of regime shifts. Usage Guidance 1. Add Session Standard Deviation⁺ to any TradingView chart. This is a fractal tool and can be applied across any timeframe or liquid instrument. 2. Configure which sessions you want to track using the input toggles. Disable sessions that are not relevant to your trading hours or strategy. 3. Use the regime panel to assess whether the current market environment supports continuation into higher deviation levels (trending regime) or whether deviation zones are more likely to act as reversal points (consolidation regime). 4. Reference session deviation lines as structural zones for limit orders, stop placement, or target setting. Combine these levels with your own narrative and higher-timeframe bias to determine which zones carry the highest probability of reaction. 5. Adjust label placement, line width, and extension mode to match your visual preferences and chart timeframe. Lower timeframes (1m–5m) often benefit from shorter extension lengths, while higher timeframes (15m–1H) may prefer persistent lines. 6. Review how price interacts with session fibs across different regime classifications. Over time, you'll develop discretion for which deviation levels are most respected during specific market conditions. Session Standard Deviation⁺ provides the structural scaffolding and environmental context for informed intraday decision-making. Use it as a lens—not a crutch—for navigating session-based price delivery.
Pine Script® インジケーター
ibnhindiの投稿
[ElThibZ] - Futures Lot Size CalculatorI’m sharing a simple script to calculate position size for futures. You only need to enter: the risk in USD you’re willing to take the stop-loss distance in ticks The script will automatically calculate the correct position size (number of contracts) and display it in the table. This tool is designed to avoid sizing mistakes, especially on futures where contract multipliers and tick values can easily lead to incorrect risk calculations. I hope it will be as useful to you as it has been for me.
Pine Script® インジケーター
ElThibZの投稿
Opening Candle Continuation SamBerg_Opening Candle Continuation is a New York session–based trading indicator designed to structure the open and identify high-probability continuation moves. The script builds an Opening Window from the NY open (default 9:30–16:00, configurable) and plots: Opening High / Low levels Optional Midline (HL2) A real-time opening range box with directional context Clean breakout continuation signals above or below the opening range Key features Configurable opening window length (5–120 minutes) Optional close confirmation, minimum range filter, and ATR filter Directional bull / bear window shading Edgeful 30-minute follow-through statistics by weekday (optional) Compact info table with opening range metrics Optional NY Session VWAP Fully customizable colors and display controls Designed for intraday index futures and equities, this tool helps traders stay aligned with the session structure and avoid low-quality trades near the open. Educational and analytical tool only. Past performance does not guarantee future results.
Pine Script® インジケーター
lschazardの投稿