Empiece

Statistics

VWAP Slope (instantaneous and cumulative, includes percentiles)VWAP Slope shows how VWAP is moving right now and how that movement is building throughout the session. The indicator has two modes: Instantaneous: slope tracks short-term VWAP momentum using a smoothed, ATR-normalized slope, and only turns on once there’s enough data in the current session (no overnight weirdness). Cumulative: slope adds up valid VWAP slope over the day, resetting each session and normalizing for time-of-day behavior so you can see whether VWAP pressure is meaningfully building or fading. You can view both as raw values or as percentile strength levels, making it easy to spot when VWAP trends are unusually strong, weak, or just noise compared to recent days.
Indicador Pine Script®
por Self_Made_Man
Custom Time Highlighter (UK time adjusted)Overview This indicator is designed to visually isolate a specific custom time window on your chart. It automatically adjusts for British Summer Time (BST) and Greenwich Mean Time (GMT) transitions, ensuring your session start and end times remain accurate throughout the year. Customizable Window: While the default is set to 9:15 AM - 5:15 PM, users can easily modify the session hours via the input settings.
Indicador Pine Script®
por ManWithDPlan
Position Size Dashboard (Gold / Forex / Indices)A clean, MT5-accurate position sizing tool that instantly calculates lot size based on risk and stop-loss range. Designed for discretionary and prop-firm traders who want fast, no-nonsense sizing without manual math. Supports Gold (XAUUSD), Forex pairs, and Indices, with clear on-chart dashboard output. How to Use (Step-by-Step) Add the indicator to your chart Open Settings → Inputs Enter your Risk ($) (e.g., 100) Enter SL Range Forex → pips Gold / Indices → price points Enable or disable Gold / Forex / Indices rows as needed Choose dashboard position, colors, and text size Click OK → Lot size is calculated instantly and shown on chart
Indicador Pine Script®
por notpranesh
Market Regime AnalyzerStatistical regime detection with forward-looking transition probabilities. Combines drift testing, variance ratios, and volume delta to classify markets into 5 regimes and quantify transition probabilities. What Regime Are We In, and What's Likely Next? That's the question this indicator answers with statistical rigor and forward-looking probabilities. The Problem: Most traders classify regimes arbitrarily: "Bull if price > 200 MA" or "Bear if RSI < 30." These rules ignore statistical significance, volume confirmation, and mean reversion patterns. The result? Late entries, false signals, and confusion when markets transition. The Solution: Market Regime Analyzer combines drift detection, variance ratio testing, and volume delta analysis to classify markets into 5 distinct regimes. Then it calculates the probability of transitioning to each regime based on historical patterns. The Benefit: Know not just where you are, but where you're likely going - with probabilities, not guesses. The Five Market Regimes 🟢 Strong Bull (Regime 1) - Statistically significant upward drift (t-stat > 1.96) - Strong buying pressure (volume delta > 0.3) - No mean reversion detected - **Trade:** Trend-following strategies, ride the momentum 🟢 Weak Bull (Regime 2) - Upward drift present - BUT weak volume OR mean reversion detected - **Trade:** Reduce position size, tighten stops, prepare for consolidation ⚪ Consolidation (Regime 3) - No statistically significant drift - Mixed volume signals - Mean reversion likely present - **Trade:** Range-trading, avoid trend-following systems 🔴 Weak Bear (Regime 4) - Downward drift present - BUT weak volume pressure - **Trade:** Cautious shorts, reduce exposure, prepare for bounce 🔴 Strong Bear (Regime 5) - Statistically significant downward drift (t-stat < -1.96) - Strong selling pressure (volume delta < -0.3) - No mean reversion detected - **Trade:** Trend-following shorts, protective puts The Statistical Framework 1. Drift Detection with T-Statistics Instead of guessing if there's a trend, we test it statistically. How it works: - Calculates mean return over lookback period - Standardizes by volatility - Compares to significance threshold (default 1.96 = 95% confidence) What it tells you: - T-stat > 1.96: Statistically significant uptrend - T-stat < -1.96: Statistically significant downtrend - In between: No significant trend (consolidation) Why it matters: Only trades trends that are statistically validated, not just visually apparent. 2. Mean Reversion Testing (Variance Ratio) Based on Lo & MacKinlay (1988) research, this detects when markets are range-bound. How it works: - Compares variance at different time scales - Variance Ratio < 0.8 indicates mean reversion What it tells you: - Mean reversion = NO: Trends can continue - Mean reversion = YES: Expect price to return to mean, not breakout Why it matters: Prevents chasing breakouts in range-bound markets. 3. Volume Delta Analysis Total volume tells you HOW MUCH traded. Volume delta tells you WHO won. How it works: - Buying pressure - Selling pressure = Volume Delta - Normalized to show relative strength What it tells you: - Strong positive delta (>0.3): Buyers in control - Strong negative delta (<-0.3): Sellers in control - Weak delta: No clear winner Why it matters: Price can move up on weak buying or down on weak selling. Volume delta reveals the truth. 4. Transition Probability Matrix Historical regime changes predict future regime changes. How it works: - Tracks every regime transition over last 100 bars (configurable) - Builds probability distribution for next regime - Updates continuously Example: Current: Strong Bull Historical transitions from Strong Bull: - Stayed Strong Bull: 45% - Became Weak Bull: 30% - Became Consolidation: 20% - Became Weak Bear: 4% - Became Strong Bear: 1% What it tells you: Strong Bull has 75% chance of staying bullish (45% + 30%), only 5% chance of bearish turn. Why it matters: Adapts to your specific market's behavior patterns. How to Use This Indicator Strategy Adaptation In Strong Bull/Bear Regimes: - Use trend-following strategies - Wider stops, let winners run - Add to positions on pullbacks - High confidence in directional trades In Weak Bull/Bear Regimes: - Reduce position sizes by 50% - Tighter stops - Take profits earlier - Prepare for regime change In Consolidation: - Switch to range-trading strategies - Avoid trend-following systems - Sell resistance, buy support - Wait for regime change before trend trades Risk Management Position Sizing: - Strong regime + high continuation probability (>60%) = Normal size - Weak regime OR high transition probability = Half size - Consolidation = Quarter size or skip Stop Loss Placement: - Strong regime: Use wider stops (2x ATR) - Weak regime: Tighter stops (1x ATR) - Consolidation: Very tight stops (0.5x ATR) Entry Timing Best entries: - Regime just changed to Strong Bull/Bear - High probability (>50%) of staying in current regime - No divergence signals present - Drift and volume delta aligned Avoid entries: - High probability of regime change - Divergence signals appearing - Mean reversion detected in trending regime - Weak volume despite price movement Reading the Dashboard Current Regime Color-coded for instant recognition: - Dark Green = Strong Bull - Light Green = Weak Bull - Gray = Consolidation - Light Red = Weak Bear - Dark Red = Strong Bear Annualized Drift Expected annual return based on recent trend. - Positive = Upward bias - Negative = Downward bias - Near zero = No directional edge T-Statistic Measures statistical significance of drift. - > 1.96 = 95% confident in uptrend - < -1.96 = 95% confident in downtrend - Between = Not statistically significant Mean Reversion - Yes = Expect price to return to mean (range-bound) - No = Trends can continue (trending market) Volume Pressure Normalized volume delta strength. - > 0.3 = Strong buying - < -0.3 = Strong selling - Near 0 = Balanced Transition Probabilities Shows most likely next regime. - Highest probability = Most likely outcome - Evenly distributed = High uncertainty - Concentrated = High confidence in direction Practical Examples Example 1: Strong Bull with High Continuation Dashboard shows: Current Regime: Strong Bull Drift: +22% annualized T-Stat: 3.2 Mean Reversion: No Volume Pressure: +0.45 Probabilities: → Strong Bull: 50% → Weak Bull: 25% → Consolidation: 20% → Bears: 5% Interpretation: - Strong uptrend (t-stat 3.2 >> 1.96) - No mean reversion = trends can continue - Strong buying pressure (0.45 > 0.3) - 75% chance stays bullish (50% + 25%) Action: - Full position size on long setups - Use trend-following entries - Wider stops (2x ATR) - High conviction trades Example 2: Weak Bull Before Consolidation Dashboard shows: Current Regime: Weak Bull Drift: +8% annualized T-Stat: 1.2 Mean Reversion: Yes Volume Pressure: +0.15 Probabilities: → Strong Bull: 10% → Weak Bull: 30% → Consolidation: 50% → Weak Bear: 10% Interpretation: - Weak drift (t-stat 1.2 < 1.96) - Mean reversion detected = range-bound likely - Weak volume (0.15 < 0.3) - 50% chance of consolidation Action: - Reduce long positions - Tighten stops - Prepare for range-bound trading - Avoid new trend trades Example 3: Regime Transition Alert Previous: Weak Bull Current: Consolidation Volume divergence signal appeared: Price made new high, volume delta weakened Interpretation: - Trend exhausted - Buyers losing control - Regime confirmed the transition Action: - Exit trend-following longs - Switch to range-trading approach - Wait for new regime before new directional trades Settings Guide ### Regime Detection Period (50) Number of bars for statistical calculations. - **30-40:** More responsive, catches changes faster, more regime switches - **50 (default):** Balanced for daily/4H charts - **75-100:** More stable, fewer false regime changes, slower to adapt Transition History Depth (100) How much history to use for probabilities. - **50-75:** Adapts quickly to recent behavior - **100 (default):** Balanced robustness - **150-200:** More stable probabilities, slower to adapt Volume Delta Period (14) Period for volume calculations. - **7-10:** More sensitive to volume shifts - **14 (default):** Standard period - **20-30:** Smoother, less noise Significance Threshold (1.96) T-statistic required for trend classification. - **1.64:** 90% confidence, more trend regimes detected - **1.96 (default):** 95% confidence, balanced - **2.58:** 99% confidence, very conservative, mostly consolidation Best Practices Do: - Wait for regime confirmation (at least 3-5 bars in new regime) - Use probabilities to size positions appropriately - Combine with support/resistance for entries - Respect mean reversion signals - Adapt strategy to current regime Don't: - Trade every regime change immediately - Ignore high transition probabilities - Use trend strategies in consolidation - Override statistical signals with gut feel - Trade against Strong regimes without clear setup Timeframe Recommendations Daily Charts: - Default settings work well - Most reliable regime detection - Best for swing trading 4H Charts: - Use default or slightly higher lookback (60-75) - Good for active swing trading - More regime changes than daily 1H Charts: - Reduce lookback to 30-40 - More noise, use with caution - Better for intraday position trading 15M and below: - Not recommended - Too much noise for statistical validity - Regimes change too frequently Combining with Other Indicators Works Well With: Moving Averages - Use regime for directional bias - MAs for specific entry/exit points Support/Resistance - Regime shows context - S/R shows specific levels - High probability at confluence Volume Profile - Regime shows regime - Profile shows where volume is - Target high-volume nodes RSI/MACD - Regime provides context - Momentum shows entry timing - Combine for higher probability Example Combined Setup Regime: Strong Bull Price: Above 200 MA Level: Pullback to support RSI: Oversold (30) Volume Delta: Still positive Setup: Long entry Reason: Trend intact, healthy pullback, buyers still present Divergence Signals The indicator shows volume divergence warnings: Bearish Divergence (Red Triangle Down) - Price makes new high - Volume delta makes lower high - Warning: Buyers weakening, potential reversal Bullish Divergence (Green Triangle Up) - Price makes new low - Volume delta makes higher low - Warning: Sellers weakening, potential reversal How to use: - Divergence in Strong regime = early warning of regime change - Confirms when regime actually transitions - Don't trade divergence alone, wait for regime confirmation Limitations This Indicator Cannot: **Predict black swan events** - Unexpected news overrides all technical regimes **Work in all markets** - Needs liquid markets with reliable volume data **Guarantee profits** - Probabilities are not certainties **Replace fundamental analysis** - Technical regimes can diverge from fundamentals Works Best: - Liquid markets (major indices, forex, crypto, large-cap stocks) - Daily and 4H timeframes - Combined with other analysis - With proper risk management - In normal market conditions Common Questions "Why did the regime stay consolidation despite strong price move?" The indicator detected mean reversion (variance ratio < 0.8), indicating the move will likely reverse. Or the move wasn't statistically significant (t-stat < 1.96). Trust the statistics over visual appearance. "Probabilities show 30% for each regime. What does that mean?" High uncertainty. The market is at an inflection point. Reduce position sizes and wait for clearer regime formation. "Can I use this for day trading?" Not recommended on timeframes below 1H. Statistical tests need sufficient data. Better suited for swing trading. "Why does this show Strong Bull when my momentum indicators show weakness?" Momentum can weaken while the trend remains statistically significant. The indicator focuses on drift and volume, not momentum. Consider it a different perspective. Technical Notes Volume Delta Approximation Uses OHLCV data to approximate order flow: - Buy volume ≈ Volume on up-closes - Sell volume ≈ Volume on down-closes - Delta = Buy - Sell **Note:** Real order flow (from futures or Level 2) is more precise. This approximation works well on liquid markets. Statistical Tests Drift T-Test: - Null hypothesis: No drift (mean return = 0) - Reject if |t-stat| > threshold - Based on standard hypothesis testing Variance Ratio: - Compares 2-period variance to 1-period variance - Ratio = 1 for random walk - Ratio < 1 for mean reversion - Threshold of 0.8 based on empirical testing Transition Probability Implementation Due to Pine Script v5 limitations (no native 2D arrays), the 5×5 transition matrix is stored as a flat 1D array of 25 elements: - Position maps to index: `row × 5 + col` - Example: Transition from Regime 2 to Regime 4 is at index `1 × 5 + 3 = 8` - Laplace smoothing (0.1) prevents zero probabilities - Row sums normalized to calculate probabilities This approach is computationally efficient and maintains statistical accuracy. No Repainting All calculations confirmed on bar close. Regime changes appear when the bar closes, not during formation. Historical analysis is accurate. Alert Conditions Regime Change - Triggers when regime transitions to any new state - Message shows new regime number (1-5) Bearish Divergence - Triggers when price makes new high but volume delta doesn't confirm Bullish Divergence - Triggers when price makes new low but volume delta doesn't confirm Disclaimer FOR EDUCATIONAL PURPOSES ONLY This indicator uses statistical methods to analyze market regimes. It does not predict the future or guarantee trading success. Markets are probabilistic, not deterministic. A 70% probability of staying bullish means 30% chance of regime change. Always use proper risk management. Past regime transitions do not guarantee future transitions. Market structure can change. Statistical relationships can break down. Never risk more than you can afford to lose. Use stop losses on every trade. Test thoroughly before live trading. Consult a qualified financial advisor. © 2026 | Open Source Statistical rigor meets practical application
Indicador Pine Script®
por DavidEH
Smart Trend Sniper [Noise Filter]"See the Trend, Ignore the Noise." This is a specialized Trend Indicator designed to filter out market noise and visualize market momentum. It is a variation of the traditional Heikin Ashi calculation, displayed in a separate pane to help you make clearer decisions without cluttering your main chart. Why use this indicator? Traditional K-lines often have too many "fake moves" (long wicks). This indicator smoothes price action into "Bricks," making it easier to hold winning trades and spot reversals instantly. Key Features: Noise Reduction: Turns messy price action into smooth color blocks. Reversal Alert (Split Color): Unlike standard indicators, this script detects the exact moment of a trend shift. It splits the candle into two colors (e.g., Red Top / White Bottom) to signal a "Tug of War" between buyers and sellers. Harmonious Trading: It works perfectly with Trendlines and Fibonacci levels. When price hits a Fibo level AND this indicator changes color, it is a high-probability entry signal. How to Read Signals: 🔴 Solid Red: Bullish Trend. Strong momentum. Hold your long position. ⚪ Solid White: Bearish Trend. Strong selling pressure. Hold short or stay out. 🌗 Split Color (Half Red/Half White): Reversal Warning! The trend is changing. Be ready to exit or enter. Configuration: Up Color: Default Red (Bullish). Down Color: Default White (Bearish). Tip: Use this in the bottom pane to confirm your main chart analysis. “看清趋势，过滤噪音。” 这是一个专为捕捉波段趋势设计的副图指标。它是传统 Heikin Ashi（平均K线）的变种优化版，旨在通过视觉化的颜色变化，帮你过滤掉市场中的“假动作”和噪音。 核心功能与优势： 极致去噪：将原本杂乱的K线平滑为整齐的“资金砖块”，让你在持仓时心态更稳，不会被细小的回调震出局。 变盘预警（独家分层技术）： 当趋势发生反转的瞬间（例如由涨转跌），指标会将柱子分裂为双色（上红下白）。 这是一个极佳的**“变盘信号”**，提示你多空力量正在发生逆转。 技术共振：该指标非常适合配合 趋势线 和 斐波那契 (Fibo) 使用。当价格回踩 Fibo 支撑位，且本指标出现变色信号时，往往是胜率极高的进场点。 小白使用指南（看颜色）： 🔴 纯红色连排：多头趋势。资金强势，建议持股/做多，不要轻易下车。 ⚪ 纯白色连排：空头趋势。抛压沉重，建议空仓或做空。 🌗 双色柱 (红白分层)：反转信号！ 趋势即将改变（例如：上红下白 = 涨势结束，准备下跌）。 设置建议： 建议放在副图使用。 只看红白转换，操作简单明了。 Disclaimer: Past performance is not indicative of future results. This tool is for educational purposes only. 免责声明：过往表现不代表未来收益，本指标仅供学习参考，不构成投资建议。
Indicador Pine Script®
por jack5391
MT Trading Deep Value Accumalation ZoneMT Trading – Deep Value Accumalation Zone is a long-term market indicator designed to show price areas where buying becomes statistically reasonable during market drawdowns. It does not give buy or sell signals and is not meant for short-term trading. The indicator focuses on identifying value zones rather than predicting exact market bottoms. The model works in logarithmic price space and builds a fixed-width zone below the market price. This zone represents areas where long-term demand has historically appeared during periods of stress, panic, or forced selling. The width of the zone never changes. Only its position moves over time. The zone is predictive, not reactive. It adjusts slowly during normal market conditions, stays stable during consolidation, and adapts faster during strong sell-offs or extreme volatility. This allows the zone to remain realistic and reachable without following price impulsively. Price may move below the zone during extreme events, but such situations are expected to be temporary. The indicator is designed to highlight areas where risk-to-reward improves, not to mark exact turning points. MT Trading – Predictive Value Zone is best used on daily or higher timeframes for crypto markets such as BTC, ETH, and major altcoins. It is intended for investors and swing traders who focus on accumulation during drawdowns and long-term market structure rather than short-term signals.
Indicador Pine Script®
por whoisoneontop
Hedge Fund Statistical Aggregate Index | QuantLapseHedge Fund Statistical Aggregate Index A Multi-Domain Regime Classification Model for Technical Structure, Higher-Timeframe Bias, and Global Liquidity Dynamics Overview The Hedge Fund Statistical Aggregate Index is a closed-source, multi-domain statistical model designed to classify market regimes by merging three independent forms of analysis: Short- to medium-term technical structure Higher-timeframe trend and persistence Macro-liquidity and systemic environment Each domain uses its own transformations, including RTI, VIDYA, Fourier smoothing, Gann-based geometry, Mastermind Trend scoring, Kijun Sen equilibrium baselines, and custom statistical aggregation loops. The final system value is therefore derived from cross-domain coherence , not from the behavior of any single indicator. This is a long-horizon regime model , not a scalping, intraday, or leverage-based system. Its logic assumes a baseline of 100% spot exposure —similar to a trend-filtered buy-and-hold framework—because risk assets tend to drift upward over long horizons under monetary expansion. This model attempts only to identify when long-term structural conditions deteriorate enough to reduce or avoid exposure . It is not designed for futures, margin, or active position flipping. Core Analytical Domains 1. Technical Layer (Short–Medium Term) This domain evaluates immediate market behavior using: volatility-adjusted trend extraction rate-of-change normalization adaptive momentum scoring deviation from dynamic equilibrium baselines This produces a normalized short-term sentiment between –1 and +1. 2. Higher-Timeframe Structural Layer A slower, structural evaluation designed to reduce noise. It evaluates: multi-timeframe trend alignment momentum persistence across cycles strength of directional bias The purpose of this domain is to identify whether local behavior aligns with broader structural pressure. 3. Macroeconomic Liquidity Layer This domain uses TradingView’s macroeconomic datasets to evaluate liquidity expansion or contraction. Inputs include: Global M2 aggregates Net Liquidity (Fed + Treasury + RRP adjustments) Global sovereign yield trends Credit-spread and funding conditions Currency-strength composites This domain approximates global liquidity cycles that frequently precede regime transitions. Aggregation & Signal Architecture A weighted statistical aggregator merges all three domains using: cross-domain agreement vs. divergence baseline distance and z-normalization rate-of-change synchronization rolling-window statistical coherence The model outputs: System Value (−1 to +1 normalized regime score) Composite Rate-of-Change Directional Regime Classification This is a regime classifier , not a traditional trade-entry generator. How to Use Designed for swing, macro, and position investing (weeks → years). Positive values = improving regime / upward structural environment. Negative values = deteriorating regime / contraction environment. Candle coloring displays market mode for clarity. When paired with a reference baseline BTCUSD the model reveals divergences between asset-specific and system-wide liquidity conditions. Domain Contribution Table The companion table shows individual contributions from each domain. Values below 0 → structural weakness Values above 0 → structural strength Values near ±1 → strong alignment (up or down) Strong Downward Regime Strong Upward Regime Additional Metrics Table These metrics help contextualize performance in long-horizon tests. Color Guide Green/Teal – favorable regime alignment Pink/Red – unfavorable regime alignment Why 100% Spot Allocation (Buy-and-Hold Logic) This model is explicitly designed around: unleveraged spot exposure macro-driven trend filtering avoiding high-risk sizing Reasoning: Long-term risk assets tend to appreciate under expanding liquidity (M2, global credit growth). A 100% spot baseline reflects realistic investor behavior, not leveraged systems. The model does not attempt to scalp, flip, or actively rotate positions. Exposure adjustments occur only during structural deterioration—not short-term volatility. It is therefore fundamentally a trend-filtered buy-and-hold overlay, not a futures or scalping tool. Charting Notes Use with a clean chart for clarity. Colors indicate regime shifts—not entry signals. No other indicators are required. Why the System Produces a Low Number of Trades Because this model is designed as a regime-classification and long-horizon investment framework , it intentionally generates a very low number of trades compared to typical trading strategies. This behavior is expected and intentional. 1. Long-Term Regimes Do Not Change Frequently The three domains—Technical, Higher-Timeframe Structure, and Macro Liquidity—are built around slow-moving structural conditions. Liquidity expansion and contraction cycles often last months or years. Higher-timeframe directional biases do not flip often. Macro persistence means structural signals remain unchanged for extended periods. Because of these slow dynamics, the system avoids high-frequency rotation and issues trades only when major structural transitions occur. This aligns with the script’s purpose: a trend-filtered buy-and-hold overlay rather than an active trading engine . 2. The Strategy Uses Spot Investment Logic (Not Trading-Centric Logic) This model assumes a baseline of 100% spot exposure , mimicking the behavior of long-term investors who remain fully invested unless the system detects a strong structural deterioration. Thus: “Trades” simply represent large regime transitions, not tactical entries. The model spends extended periods in a single position—typically long. Flat periods occur only in extreme structural divergence. This explains why the trade count seen in backtests remains low, even over multi-year datasets. 3. Why Performance May Appear Large on Assets Like Bitcoin Bitcoin and other crypto assets historically undergo: extreme long-term appreciation high volatility extended trending behavior driven by liquidity cycles In combination with a strategy that stays invested during expansion regimes, this produces: large absolute net-profit values steeper equity curves significant compounding during multi-year uptrends This is not due to leverage or aggressive trading. It is simply the result of a long-term investment model applied to a historically high-growth asset. 4. Low Trade Count Does Not Violate Strategy Guidelines TradingView’s guidelines recommend at least 100 trades only for systems claiming to be active trading strategies . However, this system is explicitly described as: not a scalping system not an intraday or short-term strategy not built for leverage not constructed around trade frequency Its purpose is regime identification for investment allocation , which justifies the lower number of trades. This is fully compliant as long as the description clearly states: “This is an investment framework, not a high-frequency strategy, and therefore the number of trades will naturally be low. Results reflect long-horizon spot exposure, not rapid trade execution.” 5. BTC’s Price Behavior Magnifies the Visual Movement of Trades On the chart you are provided: 📈 Price appreciation from 2018 → 2024 causes the equity curve to appear extremely steep. 📉 During bear cycles, the model remains flat or minimally exposed. This asymmetry creates: High net profit values High Sharpe / Sortino ratios High profit factor Low max-drawdown relative to buy-and-hold In other words: “Large-looking returns are a function of staying invested during large structural expansions, not because the system makes many trades.” Summary of This Section Low number of trades is expected. The system behaves like a trend-filtered buy-and-hold model. Spot exposure + BTC’s historical growth explains strong results. Macro trends change slowly → few trades. This aligns with TradingView publishing rules for long-horizon systems. Originality, Why the combination This script is not a mashup of public-domain TradingView indicators. It is a composite system built from independently derived, proprietary sub-models, each operating in a distinct analytical domain.The theoretical foundation of this architecture is the Law of Large Numbers, which states: As the number of independent trials increases, the average outcome converges toward the expected value. Rather than relying on a single indicator or regime assumption, this system aggregates multiple statistically independent signal sources. Each component contributes a partial, noisy estimate of market state. Through structured aggregation, these inputs converge into a stable composite signal whose expectancy is materially more reliable than any individual input in isolation. In this context, the “mashup” is deliberate: it is a statistical averaging engine, not an indicator stack. Aggregation Domains The composite signal is formed through controlled statistical aggregation of the following independent domains: RTI transformations VIDYA adaptive trend systems For-loop statistical aggregation Gann-style geometric filters Fourier-based cyclic components Mastermind trend scoring Multi-timeframe structural tracking Custom macro-liquidity composites Incorporates external liquidity conditions (M2, Global Liquidity, Net Liquidity) as slow-moving regime anchors. Why This Mashup Creates Edge The edge does not come from any single indicator or predictive claim. It emerges from: Statistical independence across domains Variance reduction through aggregation Convergence toward a stable expected value Suppression of false positives common in single-signal systems By merging signals derived from orthogonal market properties (trend, cycle, geometry, liquidity, structure), the system behaves analogously to a casino’s game portfolio or an insurance risk pool: individual outcomes vary, but the composite converges. The result is a high-signal-to-noise regime classifier designed for consistency, robustness, and long-horizon allocation decisions — not short-term prediction. Summary The Hedge Fund Statistical Aggregate Index combines multi-timeframe technical structure with global liquidity cycles to produce a normalized market regime model. It is intended for long-term analysts and allocators looking to contextualize market structure rather than trade frequently. The system is built for spot allocation frameworks and can help identify major regime transitions—especially in liquidity-sensitive assets like cryptocurrencies and global risk assets. Note: Past performance does not equal future results. This strategy is intended for research and educational purposes within TradingView.
Indicador Pine Script®
por QuantLapse
SPX SPY 5Min Lock🔹 DESCRIPTION (Public Library) This indicator overlays SPX price levels directly onto the SPY chart by converting SPX levels into SPY prices using a session-locked SPY/SPX ratio. Instead of mentally translating SPX levels, you see them mapped precisely on SPY, where you actually trade. How it works • Calculates the SPY-to-SPX price ratio • Locks the ratio at the first 5-minute RTH candle close (9:35am ET) • Uses that fixed ratio for the entire session • Converts SPX levels into accurate SPY-equivalent prices • Draws clean labels (and optional short stubs) directly on SPY Why the 5-minute lock SPY and SPX can drift slightly during the day. Locking the ratio at 9:35am creates stable, non-moving levels that stay consistent throughout RTH, making them far more usable for intraday trading. Best use cases • SPY / SPX options traders • Index-based level traders • GEX, gamma, and macro level mapping • Traders who think in SPX but execute in SPY Customization • Adjustable SPX level spacing (5 / 10 / 25) • Number of levels above and below price • Label size and offset • Live or Locked ratio mode • Optional short line stubs • Info table with ratio and lock status
Indicador Pine Script®
por GEOC1
TSX Sector ETF Overlay// --- Plot Data with Standard Colors --- plot(xiu, title="TSX 60", color=color.white, linewidth=2) plot(xfn, title="Financials", color=color.blue, linewidth=2) plot(xeg, title="Energy", color=color.orange, linewidth=2) plot(xma, title="Materials", color=color.yellow, linewidth=2) plot(xgd, title="Gold Miners", color=color.yellow, linewidth=1) plot(xit, title="Tech", color=color.purple, linewidth=2) plot(xre, title="REITs", color=color.red, linewidth=2) plot(xut, title="Utilities", color=color.green, linewidth=2) plot(xst, title="Staples", color=color.teal, linewidth=2)
Indicador Pine Script®
por alexchongkee
Asia London NY Probability Map [ES/NQ] Session StatisticsA data-driven probability overlay built on 2,800+ days of NQ and ES session data (2015–2025). This indicator classifies the current day into one of 72 unique market contexts based on Asia range, London open location, London sweep behavior, and NY open position — then displays the historical probabilities for that exact setup. Unlike typical session indicators that only draw boxes, this tool answers the question every NY session trader actually asks: "Given what Asia and London have already done today — what is statistically likely to happen next?" ═══════════════════════════════════════════════════════════════════ █ HOW IT WORKS The indicator operates in three phases: 1 — Session Detection Automatically detects Asia (20:00–02:00 ET), London (02:00–08:00 ET), and NY (08:00–16:00 ET) sessions. Session boxes are drawn on the chart with customizable colors and transparency. 2 — Context Classification At NY open, the indicator classifies the day across 4 axes: Asia Range — Below or Above average (rolling 14-session average, adapts to current volatility) London Open vs Asia — Below, Near, or Above Asia midpoint (±15% threshold) London Sweep — No sweep, Swept High only, Swept Low only, or Both NY Open vs London — Below, Near, or Above London midpoint (±15% threshold) This produces 2 × 3 × 4 × 3 = 72 distinct contexts. Each context maps to a pre-calculated set of statistics drawn from the full dataset. 3 — Probability Display Once the context is identified, the indicator displays the relevant statistics through a comprehensive panel and chart overlay. ═══════════════════════════════════════════════════════════════════ █ PANEL SECTIONS The information panel contains 6 toggleable sections: SETUP Shows the current context classification, sample size, and a confidence grade (A+ through D) based on directional clarity, sample reliability, hit rate confirmation, and sweep-both risk. PREDICTION Hit High First / Hit Low First — directional probability Sweep Both — probability that price hits both London High and Low Median Time — median minutes to first level touch Fail H→L / Fail L→H — reversal failure rates HIT RATES Independent probabilities of price reaching each key level during the NY window: London High / London Low Asia High / Asia Low PENETRATION TARGETS After a level break, how far does price typically travel beyond? Shows Median and 75th percentile penetration distances in points for both upside and downside. RANGE INFO Today's Asia and London ranges with their historical percentile ranking (e.g., "95th" means today's range is larger than 95% of historical days). LIVE STATUS Real-time tracking of: first sweep direction, sweep-both status, and actual penetration distances. Updates as NY session progresses. ═══════════════════════════════════════════════════════════════════ █ CHART OVERLAY Session Boxes Subtle outline boxes for Asia (orange), London (blue), and NY (green) with centered labels. Non-intrusive design that doesn't obscure price action. Key Levels London High / Low — solid lines with context-specific hit rate percentages London Mid — dotted reference line Asia High / Low — dashed lines with hit rate percentages Checkmarks (✓) appear next to each level as price reaches it during the NY session Penetration Targets Dynamic dotted lines that appear only after a level break, showing the Median and P75 expected penetration distances above London High or below London Low. Bias Arrow A directional indicator (▲ or ▼) showing the dominant probability with percentage. Positioned near the relevant London level for quick visual reference. ═══════════════════════════════════════════════════════════════════ █ CONFIDENCE GRADING Each context receives a score (0–100) and letter grade based on: Directional Clarity (30 pts) — How skewed is the Hit High First / Hit Low First split Sample Size (25 pts) — Larger samples = more reliable statistics Hit Rate Confirmation (25 pts) — Do the level hit rates align with the directional bias Sweep-Both Risk (20 pts) — Lower sweep-both probability = cleaner setups Grades: A+ (80+), A (65+), B (50+), C (35+), D (below 35) ═══════════════════════════════════════════════════════════════════ █ INSTRUMENTS & WINDOWS Symbols: NQ (Nasdaq futures) and ES (S&P 500 futures) Windows: AM (8:00–12:00), PM (12:00–16:00), or Full (8:00–16:00) Select your instrument and time window via the dropdown inputs. All statistics update automatically — each of the 6 configurations has its own embedded dataset. Sample sizes: NQ AM: 2,839 days | NQ PM: 982 days | NQ Full: 2,839 days ES AM: 2,692 days | ES PM: 1,036 days | ES Full: 2,692 days ═══════════════════════════════════════════════════════════════════ █ SETTINGS All visual elements are independently toggleable: Show/hide Statistics Panel, Key Levels, Session Boxes, Penetration Targets, Bias Arrow Customize colors for all session boxes and level lines Adjust label sizes (tiny / small / normal) ═══════════════════════════════════════════════════════════════════ █ ALERTS Three built-in alerts: Broke London High — price exceeds London session high Broke London Low — price breaks below London session low Sweep Both Sides — price has now touched both London High and Low ═══════════════════════════════════════════════════════════════════ █ METHODOLOGY & DATA All statistics are pre-calculated from historical tick-level session data and embedded directly in the Pine Script as arrays. No external data feeds or API calls — everything runs natively on TradingView. The context classification methodology uses fixed thresholds (±15% of range for open location) applied consistently across the entire dataset. The Asia Range classification uses a rolling 14-session average rather than a fixed historical median — this adapts to current market volatility, making the "Below/Above Average" determination relevant to recent conditions rather than a decade-old baseline. Hit rates use inclusive operators (≥ / ≤) for level touches. Note that some contexts have smaller sample sizes (under 40 days). The confidence grading system accounts for this — lower-sample contexts receive lower grades. Always consider the sample size when interpreting probabilities. ═══════════════════════════════════════════════════════════════════ █ LIMITATIONS Designed specifically for NQ and ES futures — other instruments are not supported Best used on 1–5 minute timeframes during active session hours Historical probabilities are not guarantees of future outcomes Context windows with small sample sizes (shown in panel) should be interpreted with caution Data covers 2015–2025; market regime changes may affect relevance of older data ═══════════════════════════════════════════════════════════════════ █ DISCLAIMER This indicator is a statistical research tool, not a trading signal generator. It provides historical context to support your own analysis and decision-making. Past performance does not guarantee future results. Always use proper risk management.
Indicador Pine Script®
por btcLeft
[YUTAS] Market Session Boxesゆうたす作 『市場時間表示』インジケーター Market Session Boxes （MSB） 概要 主要市場（東京・ロンドン・ニューヨーク）の時間帯レンジをチャート上にボックス表示するインジケーターです。 各セッションの開始〜終了までの高値・安値を囲み、どの市場で動いたか／どの市場のレンジをブレイクしたかを一目で把握できます。 主な機能 東京／ロンドン／ニューヨークのセッションボックス表示（ON/OFF可） セッション開始バーにアイコン表示（サイズ調整可） セッションごとの色、枠線、透明度を設定可能 DST（サマータイム）スイッチ（ロンドン／NY） ボックス保持数（過去N個まで）で軽量化 時間の扱い 基準タイムゾーン（UTCオフセット）を指定（例：Tokyo +9 / London 0 / New York -5） セッション時間は「HH:MM-HH:MM」形式で入力 DSTオン時はセッションを1時間早めて表示 -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*- Yutas' Indicator “Market Session Display” Market Session Boxes （MSB） Overview This indicator draws session range boxes for the major markets (Tokyo, London, New York). It highlights each session’s high–low range so you can quickly see where price moved and which session’s range was broken or reclaimed. Main Features Session boxes for Tokyo / London / New York (ON/OFF) Icon displayed at the session start bar (adjustable size) Custom colors, border width, and transparency for each session DST (Daylight Saving Time) switch for London / New York Limit the number of past boxes to keep the chart light Time Handling Set a base timezone (UTC offset), e.g., Tokyo +9 / London 0 / New York -5 Session time input in “HH:MM-HH:MM” format When DST is ON, sessions shift one hour earlier
Indicador Pine Script®
por yutas
Day/Month Returns Analysis [theUltimator5]This indicator calculates the average returns for day of the week, months of the year, and each Friday of the month, then gives a visualization of the average returns in green/red bars as well as the average percentage move. You can select from (3) options. 1) Day of the week. This shows the average returns for each day of the week calculated back as far as your chart history goes. For crypto, it calculates all 7 days of the week. If not crypto, it does Monday through Friday 2) Month of the year. This shows the average returns for each month. Self explanatory 3) Friday of the month. This is a niche setting that lets you see the average returns of each Friday of the month, to track if there is any OPEX related consistency. You can also set the start date for the indicator to start calculating from in the options. If there is a certain date that a symbol starts acting differently and you want to only calculate from that point forwards, you can. The visuals appear as a table which can be repositioned to whichever section of your screen you would like. This indicator works best on the daily timeframe since lower timeframes may not have enough bars back in history to calculate enough to make an average.
Indicador Pine Script®
por TheUltimator5
3
Volatility & Probability by Hour/DayVolatility & Probability by Hour/Day Analyzes historical candle data to find statistically significant time-based patterns. Tracks green candle probability, volatility, and average returns broken down by hour (UTC), day of week, and their combinations. What It Shows: Hourly Table: P(Green), edge, volatility, and average return for each hour (00:00-23:00 UTC) Day of Week Table: Same metrics aggregated by day (Sun-Sat) Top Combinations: The 5 best bullish and 5 best bearish day+hour slots ranked by edge Key Metrics: P(Grn): Historical probability the candle closes green Edge: Deviation from 50% (how tradeable the bias is) Vol%: Average candle range as percentage of price N: Sample size Use Cases: Identify optimal entry windows with statistical edge Avoid low-edge, high-volatility periods (noise) Find specific day+hour combinations with compounding edges Time trades around recurring market patterns Notes: All times in UTC Current period highlighted with ► Best results on liquid assets with sufficient history Edges are historical and not guaranteed to persist
Indicador Pine Script®
por LEEFO
NQ Statistical MapperNQ Statistical Mapper CRITICAL DISCLAIMER - READ FIRST WARNING: THIS INDICATOR IS EXCLUSIVELY FOR NQ (NASDAQ-100 E-MINI FUTURES) ONLY All statistics displayed in this indicator are HARD-CODED values derived from a comprehensive analysis of 12 years (2013-2025) of 1-minute NQ futures data. These statistics are calculated offline using Python and embedded directly into the indicator code. These probabilities DO NOT apply to any instrument other than NQ What This Indicator Does The NQ Statistical Mapper is a data-driven trading tool that displays historical probability statistics for intraday NQ price behavior based on overnight session structure and opening positioning. Rather than generating signals, it provides context by showing: Three trading sessions with visual boxes: Asia (8PM-2AM), London (2AM-8AM), and New York (8AM-4PM) Eastern Time Key price levels with historical hit rate percentages showing the probability these levels are touched during the NY cash session (8AM-4PM) Context-aware statistics that change based on current market conditions Session range analysis showing whether Asia and London ranges are unusually large or small compared to recent history Core Methodology and Statistical Foundation Pattern Detection System The indicator automatically detects one of four overnight session patterns based on how the London session (2AM-8AM) interacts with the Asia session (8PM-2AM): London Engulfs Asia: London high is greater than Asia high AND London low is less than Asia low Asia Engulfs London: Asia high is greater than or equal to London high AND Asia low is less than or equal to London low London Partial Up: London high is greater than Asia high BUT London low is greater than or equal to Asia low (took out Asia high only) London Partial Down: London low is less than Asia low BUT London high is less than or equal to Asia high (took out Asia low only) Each pattern has distinct statistical characteristics that influence NY session behavior. Conditional Probability Framework The indicator uses a conditional probability approach where statistics adapt based on: Primary Condition: Where does NY open (8:00 AM) relative to the London session midpoint? "NY opens above London midpoint" "NY opens below London midpoint" This single condition dramatically changes the probabilities. For example: When NY opens above London midpoint: 76.68% chance NY hits the London high before the London low during 8AM-4PM When NY opens below London midpoint: 73.32% chance NY hits the London low before the London high during 8AM-4PM Secondary Condition: The overnight pattern further refines these probabilities. Each combination of "NY position vs London midpoint" plus "overnight pattern" has unique hit rate statistics calculated from the 12-year dataset. "Hit First" Statistics Explained The table displays "Hit High First" and "Hit Low First" percentages. These answer the question: "During the NY cash session (8AM-4PM), if price eventually touches both the London high AND London low, which one does it touch FIRST?" Example interpretation: Hit High First: 76.68% means that in 76.68% of historical days with this setup, price touched the London high before touching the London low Hit Low First: 22.48% means London low was touched first The remaining approximately 1% represents days where neither level was hit during the NY session This is fundamentally different from asking "will price go up or down" - it is about the sequence of range expansion during the NY session. Displayed Levels and Their Meanings Session Highs/Lows (Solid Lines) These appear when each session completes and extend through the NY session: Asia High/Low (Orange): The highest and lowest prices during 8PM-2AM EST London High/Low (Blue): The highest and lowest prices during 2AM-8AM EST Each level shows its hit rate percentage - the probability that NY session price (8AM-4PM) will touch that level, based on the current pattern and NY opening position. Hourly Midpoint Levels (Dashed Gray Lines) Three specific hourly levels with remarkably high hit rates: 7-8 AM Midpoint: Average of high and low during the 7-8 AM hour. Hit rates consistently above 93-94%, essentially sitting at the 8 AM open price (mean distance: -0.001%) Midnight Open: The opening price at midnight EST. Hit rates vary from 62-87% depending on pattern and setup 2-3 AM Midpoint: Average of high and low during the 2-3 AM hour. Hit rates range from 67-92% These levels are derived from mean-reversion behavior - price tends to revisit certain overnight reference points during the NY session. Session Midpoints (Dotted Lines) Optional display of Asia and London session midpoints. These lines terminate when their respective sessions end, providing additional reference levels for session positioning. Statistics Table Breakdown The table displays five sections of information: 1. SETUP Section Shows whether "NY opens above/below London midpoint" Displays the detected overnight pattern (1 of 4 types) Sample size: Number of historical days matching this exact setup Hit High First / Hit Low First: Directional bias percentages 2. HIT RATES (8AM-4PM) Section Shows probability that each level gets touched at any point during the NY cash session: 7-8 AM Midpoint: Almost always touched (93-97% depending on pattern) Midnight Open: Varies significantly (62-87%) based on whether the overnight pattern is aligned or contrary to NY's opening position 2-3 AM Midpoint: Strong hit rates (67-92%) These are independent probabilities - they do not predict which is hit first, just whether each level gets visited. 3. ASIA RANGE Section Real-time comparison of today's Asia session range versus recent history: Sessions Captured: Shows how many sessions are in the rolling calculation (e.g., "18 / 50" = 18 sessions captured out of 50 requested). This alerts users if their chart history is insufficient Current Range: Today's Asia high minus Asia low in points Mean Range: Average range over the captured sessions Percentile Rank: Where today's range falls in the distribution 80th percentile (red background): Unusually large range - top 20% of days 60-80th percentile (light gray): Above average 20-60th percentile (white): Normal range Less than 20th percentile (light blue): Unusually small range - bottom 20% of days 4. LONDON RANGE Section Identical structure to Asia Range section, analyzing the London session's range characteristics. Why Percentile Rank Instead of Standard Deviation? Intraday ranges exhibit right-skewed distributions with fat tails (volatility spikes create extreme outliers). Percentile rank is distribution-free and robust to these characteristics, providing more reliable identification of unusual ranges than z-scores or standard deviations. How To Use This Indicator For Context and Confluence This is not a standalone trading system. The indicator provides statistical context to support other analysis: Understanding Session Bias: If the table shows 76% probability of hitting the session high first, you know there is a statistical lean toward upside range expansion Target Setting: If trading a breakout above the overnight high, knowing that Asia high gets hit 75% of the time helps assess target viability Entry Timing: The 7-8 AM midpoint's 94% hit rate makes it an excellent re-entry or scaling level Range Expansion Assessment: Percentile rankings help identify whether overnight sessions showed abnormal volatility, which may influence NY session behavior Pattern-Specific Insights London Partial Up plus NY Opens Below London Midpoint: Midnight open hit rate jumps to 87.82% (strong mean reversion) Suggests counter-trend reversal back toward overnight lows is likely London Partial Down plus NY Opens Above London Midpoint: Midnight open hit rate is 86.30% Mirror pattern - reversion toward overnight highs Asia Engulfs London Pattern: Very high hit rates (85-98%) across all levels Suggests consolidation/mean reversion during NY session rather than directional expansion Typical Workflow 8:00 AM: Review the statistics table - which pattern occurred? Where did NY open relative to London midpoint? Check Hit Rates: Note which levels have the highest probabilities of being touched Assess Range Percentiles: Are Asia/London ranges unusually large or small? High percentiles may indicate already-extended ranges Combine With Your Strategy: Use the statistics as confluence with your technical analysis, support/resistance, or order flow Customization Options Trading Sessions Settings Session Visualization: Toggle each session on/off independently Customize colors for each session (New York, London, Asia) Adjust background transparency using "Range Area Transparency" slider (0-100, default 90) Show/hide session outlines with "Range Outline" checkbox Each session has three customizable parameters on the same line: Checkbox to enable/disable the session Text field to rename the session label if desired Color picker to select the session's display color Hit Rate Levels Settings Master Controls: "Show Hit Rate Levels" - Master toggle to show or hide all level lines and labels Individual Level Toggles: "7-8 AM Midpoint" - Toggle the 7-8 AM hour midpoint level "Midnight Open" - Toggle the midnight opening price level "2-3 AM Midpoint" - Toggle the 2-3 AM hour midpoint level Hourly Level Styling (applies to 7-8 AM Mid, Midnight, and 2-3 AM Mid): "Hourly Level Color" - Color picker for all three hourly levels "Hourly Level Line Width" - Thickness of hourly level lines (1-5, default 1) "Hourly Level Line Style" - Choose between Solid, Dashed, or Dotted lines (default Dashed) Session High/Low Styling (applies to Asia High/Low and London High/Low): "Session High/Low Line Width" - Thickness of session extreme lines (1-5, default 1) "Session High/Low Line Style" - Choose between Solid, Dashed, or Dotted lines (default Solid) Additional Options: "Show Session Midpoints" - Toggle display of Asia and London midpoint reference lines (dotted lines that end when each session completes) "Label Text Size" - Size of percentage labels on all levels (tiny, small, normal, large, default small) Table Settings Statistics Table Controls: "Show Statistics Table" - Master toggle to display or hide the entire statistics table "Stats Table Position" - Choose from 9 positions on the chart: Top: Top Left, Top Center, Top Right Middle: Middle Left, Middle Center, Middle Right Bottom: Bottom Left, Bottom Center, Bottom Right "Stats Table Size" - Text size within the table (Auto, Tiny, Small, Normal, Large, Huge, default Small) "Sessions for Stats Calculation" - Number of historical sessions to use for percentile calculations (5-100, default 50) Lower values (20-30): More responsive to recent market conditions Higher values (50-100): More stable baseline, requires more chart history The table displays "Sessions Captured" to show how many sessions were actually available Important Limitations and Considerations 1. This Is Historical Data, Not Prediction The statistics show what happened in the past given similar setups. Markets evolve, regimes change, and past probability does not guarantee future outcomes. A 75% hit rate means that in 25% of historical cases, the level was NOT hit. 2. Chart History Requirements TradingView imposes data limits: 5-minute chart: Approximately 10 days of history (enough for minimal statistics) 1-minute chart: Approximately 2-3 days of history (insufficient for percentile calculations) Use 5-minute or higher timeframes to ensure adequate session capture The table displays "Sessions Captured" (e.g., 18/50) to alert you when your chart history is limited. 3. Session Timing Is Fixed (EST) All sessions use America/New_York timezone: Asia: 8PM-2AM London: 2AM-8AM NY: 8AM-4PM These times do not adjust for daylight saving changes in other regions. The definitions match CME NQ futures trading hours. 4. The Statistics Are From 2013-2025 Data The 12-year analysis period includes: Multiple market regimes (bull/bear/sideways) Various volatility environments QE, taper tantrums, COVID, 2022 bear market, 2023-2024 rally However, it is still a limited sample. Future market structure changes (algorithmic trading evolution, regulatory changes, etc.) may alter these probabilities over time. 5. No Real-Time Calculation This indicator does not recalculate statistics based on your chart's data. It displays pre-calculated probabilities. The only real-time calculations are: Which pattern occurred today Where NY opened relative to London midpoint Current session ranges and their percentile ranks (based on your chart's recent history) Statistical Methodology Details Data Source Instrument: NQ (Nasdaq-100 E-mini Futures) continuous contract Timeframe: 1-minute bars Period: January 2013 - January 2025 (12 years) Sample Size: 3,132 trading days analyzed Analysis Approach Each trading day was classified by overnight pattern (4 types). NY opening position vs London midpoint was determined. For each combination (4 patterns times 2 positions equals 8 scenarios), the following was measured: How often each level (session highs/lows, hourly midpoints) was touched during 8AM-4PM Which session extreme (high or low) was hit first Mean distance from 8 AM open to each level Session ranges were measured for percentile analysis. All percentages were rounded to two decimal places for display. Why These Specific Levels? The levels were not chosen arbitrarily: Session highs/lows: Natural support/resistance from overnight price discovery 7-8 AM midpoint: The final hour before NY open often establishes the opening range balance point Midnight open: Represents the "true" start of the trading day (6PM-5PM structure) 2-3 AM midpoint: Captures early London price action balance Testing showed these levels had the highest and most consistent hit rates across different patterns and setups. Technical Implementation Notes Language: Pine Script v5 Drawing Objects: Uses boxes for session visualization, lines for levels, labels for percentages, table for statistics Performance: Optimized for real-time use with max limits set (500 boxes, 500 lines, 500 labels) Calculations Per Bar: Session detection (3 sessions) Hourly detection (3 hourly periods) Pattern classification Conditional probability lookup Percentile rank calculation (for session ranges) All heavy statistical analysis was performed offline. The indicator only performs simple lookups and real-time range tracking. Educational Value Beyond trading application, this indicator demonstrates: Conditional Probability: How market context (opening position, overnight structure) dramatically changes probabilities Mean Reversion Dynamics: Why certain levels (7-8 AM midpoint, midnight) have such high revisit rates Pattern Recognition: How overnight session relationships create different NY session behaviors Distribution Analysis: Using percentile ranks instead of parametric statistics for skewed data Understanding these concepts helps traders develop more sophisticated market models beyond simple "support and resistance." Final Notes This indicator is a tool for informed decision-making, not a crystal ball. It answers questions like: "What typically happens in this setup?" "How often does price revisit these levels?" "Is this overnight range unusual?" It does NOT answer: "Should I buy or sell right now?" "Where will price be at 4 PM?" "What will happen tomorrow?" Combine these statistics with proper risk management, sound trading strategy, and awareness that any individual day can deviate significantly from historical norms. The power of this indicator lies in providing objective, data-driven context to complement your analysis - not in replacing your judgment.
Indicador Pine Script®
por lucymatos
5
Universal Valuation Predator | QuantLapseUniversal Valuation Predator A statistically normalized valuation and mean-reversion engine for all markets and timeframes. Overview Universal Valuation Predator is a statistically normalized valuation framework designed to identify relative overbought and oversold conditions across any asset class , any timeframe , and any market regime . Rather than relying on fixed oscillator levels or asset-specific assumptions, this script expresses price behavior through Z-scores , allowing all signals to be evaluated as deviations from their own historical norms. This approach enables consistent valuation analysis across: Cryptocurrencies Equities Indices Forex Commodities Core Philosophy Market behavior varies significantly between instruments and regimes. Absolute indicator thresholds (e.g., RSI = 70) are not inherently comparable across assets or volatility environments. This script addresses that limitation by: Calculating each component independently Normalizing each component using its own rolling mean and standard deviation Expressing all outputs as dimensionless Z-scores The result is a universal valuation model that adapts automatically to changing volatility and structure. Multi-Factor Z-Score Engine The primary valuation signal is derived from the average Z-score of multiple independent analytical components, including: Relative Strength Index (RSI) Chande Momentum Oscillator (CMO) Price Gravity Oscillator (PGO) Regression Oscillator (ROSC) Bollinger Band Percent (%B) True Strength Index (TSI) Kairi Relative Index (KRI) Each component is normalized before aggregation, reducing single-indicator bias and increasing signal robustness. Overbought & Oversold Classification Valuation regimes are expressed in standard deviations from equilibrium : +2σ to +3σ → Overbought +3σ to +4σ → Strongly Overbought > +4σ → Extremely Overvalued −2σ to −3σ → Oversold −3σ to −4σ → Strongly Oversold < −4σ → Extremely Undervalued Optional labels highlight the first transition into each valuation regime, focusing attention on statistically significant extremes rather than repeated conditions. Rapid Valuation Mode (Fast Engine) An optional Rapid Valuation Engine is included for faster market conditions and lower timeframes. This engine blends Z-score–normalized versions of: Rapid RSI (RRSI) Relative Momentum Oscillator (RMO) Intraday Momentum Oscillator (IMI) Coppock Curve–based momentum All components are standardized and averaged, producing a responsive valuation signal while maintaining statistical consistency. Visual Design & Interpretation Gradient color mapping reflects valuation intensity Background shading reinforces regime context Candle coloring mirrors valuation state directly on price Neutral zones represent statistical equilibrium, not trade signals This indicator does not predict price direction. It provides context for where price resides relative to its historical behavior. Intended Use This script is designed as a valuation and contextual analysis tool , not a standalone trading system. It is best used alongside: Market structure analysis Trend identification Volume or liquidity tools Risk management frameworks Z-score extremes indicate statistical rarity , not certainty. Important Notes No future performance is implied or guaranteed This script does not constitute financial advice All calculations are based solely on historical price data Users are responsible for validating settings and interpretations Summary Universal Valuation Predator delivers a statistically grounded, asset-agnostic framework for identifying relative market extremes using normalized Z-scores. By combining multiple independent indicators into a unified valuation model, it provides a consistent and adaptive method for analyzing overextension and mean-reversion potential across all markets.
Indicador Pine Script®
por QuantLapse