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HaP RSIComprehensive Guide to HaP RSI Indicator Introduction The HaP RSI indicator is a custom technical analysis tool designed to replicate the logic and structure of the HaP MACD indicator but applied to the Relative Strength Index (RSI). This indicator combines traditional RSI concepts with advanced smoothing techniques, dynamic signal generation, and visual cues to help traders identify potential entry and exit points, trend strength, and momentum shifts. This document provides an exhaustive explanation of the indicator's logic, its components, and practical strategies for trading with it. Logic and Structure of HaP RSI The HaP RSI indicator is built on the foundation of the RSI oscillator, which measures the speed and change of price movements to identify overbought and oversold conditions. The indicator enhances RSI by incorporating the following elements: RSI Calculation: Uses a customizable length (default 10) and allows selection of smoothing type (EMA or SMA) for flexibility. Signal Line: A moving average of the RSI (default length 9) that acts as a reference for crossovers and trend confirmation. DEMA Logic: Double Exponential Moving Average applied to RSI and its signal line to generate dynamic dot signals for entries and exits. Visual Elements: Midline at 50, Overbought/Oversold levels at 70 and 30, color-coded dots (Blue, Green, Orange, Red) for intuitive interpretation. Conditions and Signal Generation The indicator uses a sophisticated set of conditions to determine market states and generate actionable signals: Buy Condition: Triggered when the DEMA of RSI is above the DEMA of its signal line AND the DEMA signal line is rising. This indicates strengthening bullish momentum. First Signal Dot: Appears as a Blue dot when the buy condition becomes true for the first time after being false. This marks the start of a potential bullish phase. Ongoing Signal Dot: Appears as Green if RSI is rising or Orange if RSI is falling while the buy condition remains true. This provides real-time feedback on momentum strength. Exit Dot: Appears as Red when the buy condition turns false after being true, signaling a potential end to the bullish phase. Crossovers: RSI crossing above its signal line (bullish) or below (bearish) are calculated but hidden by default, offering additional confirmation if enabled. Trading Strategies Using HaP RSI The HaP RSI indicator can be used in multiple ways to enhance trading decisions. Below are detailed strategies and best practices: 1. Entry Strategies Enter long positions when a Blue dot appears, confirming the start of bullish momentum. Ideally, combine this with RSI above the midline (50) and price action breaking resistance. Add to positions or scale in when Green dots appear, indicating continued bullish strength. 2. Exit Strategies Exit or tighten stops when a Red dot appears, signaling weakening momentum. Consider partial exits on Orange dots if momentum slows but the trend remains intact. 3. Trend Confirmation Use the midline (50) as a regime filter: RSI above 50 generally favors long trades, while below 50 favors shorts. Overbought/Oversold levels (70/30) can help identify exhaustion points for reversals or caution zones. 4. Risk Management Always combine HaP RSI signals with stop-loss placement based on recent swing lows/highs. Avoid chasing signals in low-volatility environments; confirm with volume or higher timeframe trend. Advanced Usage and Best Practices Combine HaP RSI with other indicators like moving averages or price action patterns for confluence. Use alerts for Blue and Red dots to automate monitoring and reduce missed opportunities. Backtest the indicator on multiple timeframes (H1 recommended) to optimize settings for your trading style. Summary HaP RSI is a powerful tool that blends RSI's simplicity with advanced signal logic, making it suitable for trend-following, momentum trading, and swing strategies. Its visual clarity and dynamic alerts allow traders to act decisively while managing risk effectively.
Pine Script® indicator
by DayTraderz365
SMI + Trend Whale Tracker//@version=6 // Fixed Line 1: Explicitly naming the title and shorttitle indicator(title="SMI + Trend Whale Tracker", shorttitle="SMI_Whale", overlay=true) // --- Inputs --- lenK = input.int(10, "%K Length", group="SMI Settings") lenD = input.int(3, "%D Length", group="SMI Settings") lenEMA = input.int(3, "EMA Length", group="SMI Settings") volMult = input.float(3.0, "Whale Volume Multiplier (x Avg)", group="Whale Settings") trendLen = input.int(200, "Global Trend SMA Length", group="Trend Settings") // --- Calculations: SMI --- emaEma(src, len) => ta.ema(ta.ema(src, len), len) hi = ta.highest(lenK), lo = ta.lowest(lenK) relRange = close - (hi + lo) / 2 smi = (hi - lo) != 0 ? 200 * (emaEma(relRange, lenD) / emaEma(hi - lo, lenD)) : 0 // --- Calculations: Global Trend --- sma200 = ta.sma(close, trendLen) isBullishTrend = close > sma200 plot(sma200, "200 SMA", color=color.new(color.blue, 50), linewidth=2) // --- Calculations: Whale Tracker with Filter --- avgVol = ta.sma(volume, 20) isWhaleVol = volume > (avgVol * volMult) // Filter: Whale must buy while price is above the 200 SMA isWhaleBuy = isWhaleVol and close > open and isBullishTrend isWhaleSell = isWhaleVol and close < open // --- Visuals --- plotshape(isWhaleBuy, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Whale Buy") plotshape(isWhaleSell, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Whale Sell") // --- Dashboard --- var table dash = table.new(position.top_right, 2, 3, bgcolor=color.new(color.black, 0), border_width=1) if barstate.islast smiColor = smi > 40 ? color.green : (smi < -40 ? color.red : color.gray) trendColor = isBullishTrend ? color.green : color.red table.cell(dash, 0, 0, text="SMI", text_color=color.white) table.cell(dash, 1, 0, text=str.tostring(smi, "#.#"), bgcolor=smiColor, text_color=color.white) table.cell(dash, 0, 1, text="Trend", text_color=color.white) table.cell(dash, 1, 1, text=isBullishTrend ? "BULLISH" : "BEARISH", bgcolor=trendColor, text_color=color.white) table.cell(dash, 0, 2, text="Whale", text_color=color.white) table.cell(dash, 1, 2, text=isWhaleVol ? "ACTIVE" : "None", bgcolor=isWhaleVol ? color.purple : color.gray, text_color=color.white) // --- Alerts --- if isWhaleBuy alert("Whale Buy + Trend Aligned: " + syminfo.ticker, alert.freq_once_per_bar_close)
Pine Script® indicator
by azharshamim72726
TradeCraftly - Previous OHLC Levels📌 TradeCraftly – Previous OHLC Levels TradeCraftly OHLC plots the most important higher-timeframe price levels directly on your chart, helping you identify key support, resistance, and reference zones with clarity. 🔹 What this indicator shows Previous Day OHLC (High, Low, Open, Close) Previous Week OHLC Previous Month OHLC Today’s Open (no historical clutter) All levels are drawn as clean horizontal rays and extend only into the current session, keeping the chart focused and readable. 🔹 Key Features Individual enable / disable controls for Day, Week, and Month levels No historical clutter – only the most relevant levels are shown Labels aligned to today’s first candle for quick level identification Custom line width, color, and style (solid / dashed / dotted) Works seamlessly on all intraday and higher timeframes 🔹 Why use Previous OHLC levels? Previous period OHLC levels are widely used by: Intraday traders Swing traders Index & futures traders They often act as: Strong support & resistance Liquidity zones Breakout / rejection levels 🔹 Best Use Cases Market open bias using Today’s Open Intraday trades around PDH / PDL Weekly range reactions near PWH / PWL Higher-timeframe context using Monthly levels ⚠️ Disclaimer This indicator is for educational purposes only and does not provide trading signals or financial advice. Always manage risk and confirm with your own analysis.
Pine Script® indicator
by amolsmagar
Fair Value Gaps w Signals fair value gaps for resistance and support. It is important to understand ranges with this. An open bearish fair value gaps can indicate a bearish range. A bullish fair value gaps in premium can indicate retracement into the bearish range. A fair value gaps on a high time frame in discount of the range can be a indicator to go long. one can play the fair value gaps in discount or a range back into it for longs. negation of the fair value gaps candle bearish or bullish is stop loss. One would want to see a small time frame turn around story within the fair value gaps you are trading. FVG are support and resistance until the market is balanced. A bearish fair value gaps untouched can indicate the end of a range. The candle before the 1st bullsih fair value gaps could be the beginning of the range. all time frames
Pine Script® indicator
by soulvibeslive
3
Volume-Weighted Price Z-Score [QuantAlgo]🟢 Overview The Volume-Weighted Price Z-Score indicator quantifies price deviations from volume-weighted equilibrium using statistical standardization. It combines volume-weighted moving average analysis with logarithmic deviation measurement and volatility normalization to identify when prices have moved to statistically extreme levels relative to their volume-weighted baseline, helping traders and investors spot potential mean reversion opportunities across multiple timeframes and asset classes. 🟢 How It Works The indicator's core methodology lies in its volume-weighted statistical approach, where price displacement is measured through normalized deviations from volume-weighted price levels: volumeWeightedAverage = ta.vwma(priceSource, lookbackPeriod) logDeviation = math.log(priceSource / volumeWeightedAverage) volatilityMeasure = ta.stdev(logDeviation, lookbackPeriod) The script uses logarithmic transformation to capture proportional price changes rather than absolute differences, ensuring equal treatment of percentage moves regardless of price level: rawZScore = logDeviation / volatilityMeasure zScore = ta.ema(rawZScore, smoothingPeriod) First, it establishes the volume-weighted baseline which gives greater weight to price levels where significant trading occurred, creating a more representative equilibrium point than simple moving averages. Then, the logarithmic deviation measurement converts the price-to-average ratio into a normalized scale: logDeviation = math.log(priceSource / volumeWeightedAverage) Next, statistical normalization is achieved by dividing the deviation by its own historical volatility, creating a standardized z-score that measures how many standard deviations the current price sits from the volume-weighted mean. Finally, EMA smoothing filters noise while preserving the signal's responsiveness to genuine market extremes: rawZScore = logDeviation / volatilityMeasure zScore = ta.ema(rawZScore, smoothingPeriod) This creates a volume-anchored statistical oscillator that combines price-volume relationship analysis with volatility-adjusted normalization, providing traders with probabilistic insights into market extremes and mean reversion potential based on standard deviation thresholds. 🟢 Signal Interpretation ▶ Positive Values (Above Zero): Price trading above volume-weighted average indicating potential overvaluation relative to volume-weighted equilibrium = Caution on longs, potential mean reversion downward = Short/sell opportunities ▶ Negative Values (Below Zero): Price trading below volume-weighted average indicating potential undervaluation relative to volume-weighted equilibrium = Caution on shorts, potential mean reversion upward = Long/buy opportunities ▶ Zero Line Crosses: Mean reversion transitions where price crosses back through volume-weighted equilibrium, indicating shift from overvalued to undervalued (or vice versa) territory ▶ Extreme Positive Zone (Above +2.5σ default): Statistically rare overvaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bullish conditions with high mean reversion probability = Strong correction warning/short signal ▶ Extreme Negative Zone (Below -2.5σ default): Statistically rare undervaluation representing 98.8%+ confidence level deviation, indicating extremely stretched bearish conditions with high mean reversion probability = Strong buying opportunity signal ▶ ±1σ Reference Levels: Moderate deviation zones (±1 standard deviation) marking common price fluctuation boundaries where approximately 68% of price action occurs under normal distribution ▶ ±2σ Reference Levels: Significant deviation zones (±2 standard deviations) marking unusual price extremes where approximately 95% of price action should be contained under normal conditions 🟢 Features ▶ Preconfigured Presets: Three optimized parameter sets accommodate different analytical approaches, instruments and timeframes. "Default" provides balanced statistical measurement suitable for swing trading and daily/4-hour analysis, offering deviation detection with moderate responsiveness to price dislocations. "Fast Response" delivers heightened sensitivity optimized for intraday trading and scalping on 15-minute to 1-hour charts, using shorter statistical windows and minimal smoothing to capture rapid mean reversion opportunities as they develop. "Smooth Trend" offers conservative extreme identification ideal for position trading on daily to weekly charts, employing extended statistical periods and heavy noise filtering to isolate only the most significant market extremes. ▶ Built-in Alerts: Seven alert conditions enable comprehensive automated monitoring of statistical extremes and mean reversion events. Extreme Overbought triggers when z-score crosses above the extreme threshold (default +2.5σ) signaling rare overvaluation, Extreme Oversold activates when z-score crosses below the negative extreme threshold (default -2.5σ) signaling rare undervaluation. Exit Extreme Overbought and Exit Extreme Oversold alert when prices begin reverting from these statistical extremes back toward the mean. Bullish Mean Reversion notifies when z-score crosses above zero indicating shift to overvalued territory, while Bearish Mean Reversion triggers on crosses below zero indicating shift to undervalued territory. Any Extreme Level provides a combined alert for any extreme threshold breach regardless of direction. These notifications allow you to capitalize on statistically significant price dislocations without continuous chart monitoring. ▶ Color Customization: Six visual themes (Classic, Aqua, Cosmic, Ember, Neon, plus Custom) accommodate different chart backgrounds and visual preferences, ensuring optimal contrast for identifying positive versus negative deviations across trading environments. The adjustable fill transparency control (0-100%) allows fine-tuning of the gradient area prominence between the z-score line and zero baseline, with higher opacity values creating subtle background context while lower values produce bold deviation emphasis. Optional bar coloring extends the z-score gradient directly to the indicator pane bars, providing immediate visual reinforcement of current deviation magnitude and direction without requiring reference to the plotted line itself. *Note: This indicator requires volume data to function correctly, as it calculates deviations from a volume-weighted price average. Tickers with no volume data or extremely limited volume will not produce meaningful results, i.e., the indicator may display flat lines, erratic values, or fail to calculate properly. Using this indicator on assets without volume data (certain forex pairs, synthetic indices, or instruments with unreported/unavailable volume) will produce unreliable or no results at all. Additionally, ensure your chart has sufficient historical data to cover the selected lookback period, e.g., using a 100-bar lookback on a chart with only 50 bars of history will yield incomplete or inaccurate calculations. Always verify your chosen ticker has consistent, accurate volume information and adequate price history before applying this indicator.
Pine Script® indicator
by QuantAlgo
11
Spot Futures Divergence & Auction ContextSpot–Futures Divergence & Auction Context Spot–Futures Divergence & Auction Context is a contextual market analysis indicator designed to help traders understand where the market is positioned and when structural divergence is meaningful. This tool compares spot and futures price structure using confirmed swing pivots and overlays that information with VWAP location, auction regime, and higher-timeframe (HTF) trend context. ⚠️ This indicator is NOT a buy/sell signal generator. It is intended for discretionary decision support and market context only. 🔍 What This Indicator Shows 1️⃣ Spot–Futures Structural Divergence Identifies divergence between spot and futures swing structure Highlights where derivatives are leading or lagging cash markets Uses confirmed pivots only (non-repainting) 2️⃣ Divergence Quality (DIV-A / DIV-B) DIV-A: Divergence aligned with HTF trend DIV-B: Divergence against or without HTF alignment Helps distinguish high-quality context from early warnings 3️⃣ VWAP Context & Deviation Bands Session VWAP plotted on futures Optional VWAP deviation bands (±1σ / ±2σ / ±3σ) for auction stretch context Bands are visual only, not signals 4️⃣ Auction Regime Detection Classifies market as BALANCED or IMBALANCED Helps avoid divergence during strong trend / directional auctions 5️⃣ Options Bias Panel (Context Only) Provides a high-level directional or volatility bias, such as: CALL BIAS PUT BIAS SELL PREMIUM WAIT This bias is informational, not an instruction to trade. ⚙️ Key Settings Explained Futures / Execution Symbol Select the futures or derivative symbol you are trading (e.g., NIFTY1!, BANKNIFTY1!, ES1!, BTCUSDT.P). Spot / Cash Reference Symbol Select the corresponding spot or cash index used for structural comparison. Divergence Display Mode Show All → Displays all divergences Hide in Imbalanced → Suppresses divergences during strong directional auctions DIV-A only in Imbalanced → Shows only HTF-aligned divergences on trend days This is a discipline and visibility control, not a signal filter. VWAP Deviation Bands Optional visual bands to assess how far price is trading from fair value. Best used for context, not entries. 🧭 How to Use (1-Page User Guide) Recommended Workflow Start with auction regime Balanced → mean-reversion context Imbalanced → trend / momentum context Observe VWAP location Near VWAP → fair value Extended → stretched auction Note Spot–Futures divergence DIV-A → higher contextual importance DIV-B → early warning or risk signal Use Options Bias panel As a guideline, not a trigger Especially useful for options and volatility strategies 🚫 When to Ignore Divergence Strong imbalanced trend with steep VWAP slope News-driven or event-driven sessions Very early session before structure forms ⚠️ Important Disclaimers This indicator does not generate buy/sell signals. No profitability or performance claims are made. Past behavior does not guarantee future results. Trading futures, options, and leveraged products involves significant risk. Use this tool for analysis and education only. 📊 Best Use Cases Index futures & options Spot vs derivative structure analysis Intraday auction and VWAP-based context Risk awareness and trade selection support
Pine Script® indicator
by Market_Logic_India
2
Infinity Signal Momentum ConsensusMulti-Timeframe Momentum Fusion & Projection Infinity Signal — Momentum Consensus is a multi-timeframe momentum oscillator designed to identify early turning points, directional bias, and momentum structure by blending momentum data across multiple timeframes into a single, unified signal. Instead of relying on a traditional single-timeframe Stochastic RSI, this indicator creates a consensus momentum curve that reflects how short-, medium-, and long-term momentum align in real time. The result is a smoother, more stable oscillator that often turns before price and before standard momentum indicators react. This approach reduces noise while preserving the geometric structure required for forward projection and swing analysis. 🔍 How It Works The indicator computes Stochastic RSI momentum across multiple timeframes (1H, 4H, 1D, 1W, 1M), normalizes those values, and combines them into a single composite curve. Each timeframe contributes differently: Higher timeframes shape overall curvature and bias Mid timeframes influence impulse strength Lower timeframes refine timing When averaged together, these form a momentum consensus that highlights genuine shifts in market behavior. The indicator also includes: A forward momentum projection based on prior curvature A multi-timeframe alignment table with weighted bias and grading Visual context for overbought, oversold, and transitional states 🧭 How to Use 1️⃣ Identify Directional Bias Use the Composite Momentum Curve to determine the dominant market bias. Rising curve → bullish momentum pressure Falling curve → bearish momentum pressure Flattening or compressing curve → consolidation or transition Because the curve blends multiple timeframes, its direction is often more reliable than single-TF oscillators. 2️⃣ Watch for Early Turning Points Key signals occur when the composite curve bends, flattens, or crosses. Momentum turns frequently appear before price reversals Signals near overbought or oversold zones carry greater significance The smoother curve helps reduce whipsaw These inflection points are particularly useful for swing and position traders. 3️⃣ Use the Multi-Timeframe Table for Confirmation The table summarizes momentum alignment across all tracked timeframes. Bull / Bear / Mixed shows agreement or divergence Weighted scores reveal which timeframes dominate Signal grades (A+ → F) reflect alignment quality The strongest setups occur when table bias and momentum direction agree. 4️⃣ Interpret Projections as Context Projected momentum paths visualize how momentum may evolve based on prior structure. Use projections as guidance, not guarantees Look for symmetry, slope changes, and recurring curvature Combine projections with structure or support/resistance Projections are most effective in stable momentum regimes. 5️⃣ Combine with Price Action & Risk Management Infinity Signal — Momentum Consensus is designed as a decision-support tool. Confirm signals with market structure and price behavior Use clear invalidation levels and risk controls Reduce exposure during mixed or low-alignment conditions No indicator replaces proper risk management. 🎯 Ideal Use Cases Swing trading & position trading Momentum-based trend analysis Early reversal and pivot detection Multi-timeframe confirmation ⚠️ Disclaimer This indicator is for educational and analytical purposes only and does not constitute financial advice. Always manage risk appropriately.
Pine Script® indicator
by Dinjin
VWAP Institutional Trading Engine INDICATORVWAP Institutional Trading Engine Adaptive Market Regime & Trading Model Indicator 🔍 Overview The VWAP Institutional Trading Engine is an advanced, rule-based market analysis indicator designed to replicate institutional decision-making logic using VWAP, volatility, and session-based market behavior. This indicator does not predict price. Instead, it answers a more important question: “What type of trading is appropriate right now – if any?” The engine continuously evaluates: Market regime (trend, range, dead market) Volatility conditions VWAP acceptance and deviation Trading session (Asia / London / New York) Based on this, it dynamically activates one of three trading models: TREND MEAN REVERSION OFF (no trading) This makes it ideal for: Discretionary traders Systematic traders Risk-focused trading Educational / portfolio-style trading approaches 🧠 Core Philosophy Professional trading is not about finding more signals. It is about knowing when not to trade. This indicator is built around three institutional principles: VWAP defines fair value Volatility defines opportunity or danger Different sessions require different behavior ⚙️ Indicator Components 1️⃣ VWAP & Statistical Deviation Bands VWAP represents institutional fair price ±1σ bands indicate acceptance zones ±2σ bands represent statistical extremes Used for: Mean reversion zones Trend acceptance confirmation Go Score calculation 2️⃣ Volatility Engine Volatility is measured using ATR relative to price Compared against its own moving average Classifications: Low volatility → dead / untradable market Normal volatility → structured behavior High volatility → trend or liquidation events 3️⃣ Market Regime Detection The engine classifies each moment into one regime: Regime Meaning TREND Price accepts above or below VWAP with volatility RANGE Price rotates near VWAP DEAD Low volatility, no opportunity MIXED Unclear structure 4️⃣ Active Trading Model (Most Important) Displayed in the dashboard as Model: Model Interpretation TREND Trade with momentum and continuation MEAN_REVERT Trade extremes back to VWAP OFF Do not trade The Model tells you HOW you are allowed to trade right now. 5️⃣ Session Awareness (UTC) The indicator adapts behavior based on session logic: Session Preferred Behavior Asia Mean Reversion London Trend New York Selective / adaptive Trades are only allowed when model + session are aligned. 6️⃣ Go Score – Trade Quality Filter Each potential setup receives a Go Score (0–100), based on: Distance from VWAP Market regime quality Volatility penalties Go Score Interpretation ≥ 80 High-quality (A+) 65–79 Acceptable < 65 No trade 7️⃣ Risk Guidance (Informational) The indicator outputs a Risk % suggestion, based on: Go Score Simulated drawdown logic ⚠️ This is guidance only, not position sizing. 📈 Visual Signals The indicator plots contextual signals, not blind entries: Mean Reversion Signals ▲ Long below −2σ ▼ Short above +2σ Trend Signals ↑ Long after acceptance above +1σ ↓ Short after acceptance below −1σ Signals appear only when trading is allowed by: Model Session Go Score 🧩 Dashboard Explanation The top-right dashboard displays real-time engine state: Field Description Session Current UTC session Regime Detected market condition Go Score Trade quality score Risk % Suggested relative risk Drawdown % Virtual defensive metric Model Active trading model If Model = OFF → do nothing. 🧭 Practical Trading Manual (Step-by-Step) Step 1 – Check the Model TREND → look for continuation MEAN_REVERT → look for extremes OFF → do not trade Step 2 – Confirm Session Alignment Asia + Mean Reversion ✔ London + Trend ✔ Misalignment = caution Step 3 – Check Go Score Below 65 → skip 65+ → proceed Step 4 – Use Chart Structure VWAP = anchor σ bands = context Signal = permission, not obligation Step 5 – Manage Risk Manually Use your own SL/TP rules Follow the Risk % as guidance, not law ❌ What This Indicator Is NOT Not a signal spam tool Not a prediction system Not a “holy grail” It is a decision framework. ✅ Best Use Cases Futures Indices Forex Crypto Intraday & swing trading Recommended timeframes: 5m – 1H (intraday) 4H (contextual swing) 🏁 Final Notes This indicator is intentionally transparent and rule-based. It is designed to help traders: Think in regimes Trade with structure Avoid overtrading Protect capital If you trade with the Model, not against it, you will already be ahead of most market participants.
Pine Script® indicator
by ypkiss12
Candle Statistics | by beidou_123Script Description Candle Statistics is a quantitative market analysis indicator that provides a structured statistical overview of recent price behavior using candlestick classification. The script analyzes historical candles over four user-defined lookback periods and classifies each candle into one of three categories: Bullish candles (close > open) Bearish candles (close < open) Doji candles , defined as candles whose real body is less than or equal to 10% of the total candle range Key Features Fully customizable lookback periods Users can define four independent candle windows (e.g., 15, 60, 240, 480 bars). Standardized Doji definition A Doji is identified when the candle body is small relative to total price range, ensuring consistency across instruments and timeframes. Directional dominance calculation For each lookback period, the script computes the Bullish Percentage, defined as: Bullish % = Bullish Candles ÷ (Bullish + Bearish Candles) Doji candles are intentionally excluded from this calculation to avoid diluting directional bias. Visual dominance highlighting If Bullish % > 50%, the value is displayed using a user-defined bullish dominance color If Bullish % ≤ 50%, the value is displayed using a user-defined bearish dominance color On-chart statistics table All results are presented in a compact, non-intrusive table displayed directly on the main chart. Table position is fully configurable. Intended Use This indicator is designed for: Market structure analysis Trend bias evaluation Volatility and indecision studies Systematic filtering in discretionary or rule-based trading systems It is not a signal generator, but a statistical context tool that helps traders assess whether recent price action is dominated by bullish pressure, bearish pressure, or indecision. Disclaimer This indicator is provided for educational and analytical purposes only and does not constitute financial or investment advice.
Pine Script® indicator
by beidou_123
libSchedulerTLDR: This is a lightweight, easy-to-use way to throttle sections of Pinescript v6 scripts, the same as you'd use barstate.isconfirmed or barstate.islast. You can use this for enormous efficiency gains, provided you design your script to handle updates on differing intervals rather than computing everything on each cycle. Usage is easy: ``` import showmethegrail/libScheduler/1 as libScheduler i_tf_fetch = input.enum(libScheduler.Timeframes.C, "Fetch Interval", tooltip="Do things just once every interval, default=once per chart timeframe.") var scheduler = libScheduler.Scheduler.new().init() if scheduler.every(i_tf_fetch) // Do stuff ``` That's it. If you need to know more, the code is well-commented. Combine this with sensible caching, and you can right-size the compute-heavy sections of your script, for better stability and managed use of Pinescript compute quotas. You'll need to know the proper use of var and varip to make the most of this, but I found this effectively replaced a lot of boilerplate in throttling my own scripts. Sound software engineering, made Pinescript-level easy. That's all.
Pine Script® library
by showmethegrail
1
DeeptestDeeptest: Quantitative Backtesting Library for Pine Script ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ OVERVIEW Deeptest is a Pine Script library that provides quantitative analysis tools for strategy backtesting. It calculates over 100 statistical metrics including risk-adjusted return ratios (Sharpe, Sortino, Calmar), drawdown analysis, Value at Risk (VaR), Conditional VaR, and performs Monte Carlo simulation and Walk-Forward Analysis. █ WHY THIS LIBRARY MATTERS Pine Script is a simple yet effective coding language for algorithmic and quantitative trading. Its accessibility enables traders to quickly prototype and test ideas directly within TradingView. However, the built-in strategy tester provides only basic metrics (net profit, win rate, drawdown), which is often insufficient for serious strategy evaluation. Due to this limitation, many traders migrate to alternative backtesting platforms that offer comprehensive analytics. These platforms require other language programming knowledge, environment setup, and significant time investment—often just to test a simple trading idea. Deeptest bridges this gap by bringing institutional-level quantitative analytics directly to Pine Script. Traders can now perform sophisticated analysis without leaving TradingView or learning complex external platforms. All calculations are derived from strategy.closedtrades.* , ensuring compatibility with any existing Pine Script strategy. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ ORIGINALITY AND USEFULNESS This library is original work that adds value to the TradingView community in the following ways: 1. Comprehensive Metric Suite: Implements 112+ statistical calculations in a single library, including advanced metrics not available in TradingView's built-in tester (p-value, Z-score, Skewness, Kurtosis, Risk of Ruin). 2. Monte Carlo Simulation: Implements trade-sequence randomization to stress-test strategy robustness by simulating 1000+ alternative equity curves. 3. Walk-Forward Analysis: Divides historical data into rolling in-sample and out-of-sample windows to detect overfitting by comparing training vs. testing performance. 4. Rolling Window Statistics: Calculates time-varying Sharpe, Sortino, and Expectancy to analyze metric consistency throughout the backtest period. 5. Interactive Table Display: Renders professional-grade tables with color-coded thresholds, tooltips explaining each metric, and period analysis cards for drawdowns/trades. 6. Benchmark Comparison: Automatically fetches S&P 500 data to calculate Alpha, Beta, and R-squared, enabling objective assessment of strategy skill vs. passive investing. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ KEY FEATURES Performance Metrics Net Profit, CAGR, Monthly Return, Expectancy Profit Factor, Payoff Ratio, Sample Size Compounding Effect Analysis Risk Metrics Sharpe Ratio, Sortino Ratio, Calmar Ratio (MAR) Martin Ratio, Ulcer Index Max Drawdown, Average Drawdown, Drawdown Duration Risk of Ruin, R-squared (equity curve linearity) Statistical Distribution Value at Risk (VaR 95%), Conditional VaR Skewness (return asymmetry) Kurtosis (tail fatness) Z-Score, p-value (statistical significance testing) Trade Analysis Win Rate, Breakeven Rate, Loss Rate Average Trade Duration, Time in Market Consecutive Win/Loss Streaks with Expected values Top/Worst Trades with R-multiple tracking Advanced Analytics Monte Carlo Simulation (1000+ iterations) Walk-Forward Analysis (rolling windows) Rolling Statistics (time-varying metrics) Out-of-Sample Testing Benchmark Comparison Alpha (excess return vs. benchmark) Beta (systematic risk correlation) Buy & Hold comparison R-squared vs. benchmark ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ QUICK START Basic Usage //@version=6 strategy("My Strategy", overlay=true) // Import the library import Fractalyst/Deeptest/1 as * // Your strategy logic fastMA = ta.sma(close, 10) slowMA = ta.sma(close, 30) if ta.crossover(fastMA, slowMA) strategy.entry("Long", strategy.long) if ta.crossunder(fastMA, slowMA) strategy.close("Long") // Run the analysis DT.runDeeptest() ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ METRIC EXPLANATIONS The Deeptest table displays 23 metrics across the main row, with 23 additional metrics in the complementary row. Each metric includes detailed tooltips accessible by hovering over the value. Main Row — Performance Metrics (Columns 0-6) Net Profit — (Final Equity - Initial Capital) / Initial Capital × 100 — >20%: Excellent, >0%: Profitable, <0%: Loss — Total return percentage over entire backtest period Payoff Ratio — Average Win / Average Loss — >1.5: Excellent, >1.0: Good, <1.0: Losses exceed wins — Average winning trade size relative to average losing trade. Breakeven win rate = 100% / (1 + Payoff) Sample Size — Count of closed trades — >=30: Statistically valid, <30: Insufficient data — Number of completed trades. Includes 95% confidence interval for win rate in tooltip Profit Factor — Gross Profit / Gross Loss — >=1.5: Excellent, >1.0: Profitable, <1.0: Losing — Ratio of total winnings to total losses. Uses absolute values unlike payoff ratio CAGR — (Final / Initial)^(365.25 / Days) - 1 — >=10%: Excellent, >0%: Positive growth — Compound Annual Growth Rate - annualized return accounting for compounding Expectancy — Sum of all returns / Trade count — >0.20%: Excellent, >0%: Positive edge — Average return per trade as percentage. Positive expectancy indicates profitable edge Monthly Return — Net Profit / (Months in test) — >0%: Profitable month average — Average monthly return. Geometric monthly also shown in tooltip Main Row — Trade Statistics (Columns 7-14) Avg Duration — Average time in position per trade — Mean holding period from entry to exit. Influenced by timeframe and trading style Max CW — Longest consecutive winning streak — Maximum consecutive wins. Expected value = ln(trades) / ln(1/winRate) Max CL — Longest consecutive losing streak — Maximum consecutive losses. Important for psychological risk tolerance Win Rate — Wins / Total Trades — Higher is better — Percentage of profitable trades. Breakeven win rate shown in tooltip BE Rate — Breakeven Trades / Total Trades — Lower is better — Percentage of trades that broke even (neither profit nor loss) Loss Rate — Losses / Total Trades — Lower is better — Percentage of unprofitable trades. Together with win rate and BE rate, sums to 100% Frequency — Trades per month — Trading activity level. Displays intelligently (e.g., "12/mo", "1.5/wk", "3/day") Exposure — Time in market / Total time × 100 — Lower = less risk — Percentage of time the strategy had open positions Main Row — Risk Metrics (Columns 15-22) Sharpe Ratio — (Return - Rf) / StdDev × sqrt(Periods) — >=3: Excellent, >=2: Good, >=1: Fair, <1: Poor — Measures risk-adjusted return using total volatility. Annualized using sqrt(252) for daily Sortino Ratio — (Return - Rf) / DownsideDev × sqrt(Periods) — >=2: Excellent, >=1: Good, <1: Needs improvement — Similar to Sharpe but only penalizes downside volatility. Can be higher than Sharpe Max DD — (Peak - Trough) / Peak × 100 — <5%: Excellent, 5-15%: Moderate, 15-30%: High, >30%: Severe — Largest peak-to-trough decline in equity. Critical for risk tolerance and position sizing RoR — Risk of Ruin probability — <1%: Excellent, 1-5%: Acceptable, 5-10%: Elevated, >10%: Dangerous — Probability of losing entire trading account based on win rate and payoff ratio R² — R-squared of equity curve vs. time — >=0.95: Excellent, 0.90-0.95: Good, 0.80-0.90: Moderate, <0.80: Erratic — Coefficient of determination measuring linearity of equity growth MAR — CAGR / |Max Drawdown| — Higher is better, negative = bad — Calmar Ratio. Reward relative to worst-case loss. Negative if max DD exceeds CAGR CVaR — Average of returns below VaR threshold — Lower absolute is better — Conditional Value at Risk (Expected Shortfall). Average loss in worst 5% of outcomes p-value — Binomial test probability — <0.05: Significant, 0.05-0.10: Marginal, >0.10: Likely random — Probability that observed results are due to chance. Low p-value means statistically significant edge Complementary Row — Extended Metrics Compounding — (Compounded Return / Total Return) × 100 — Percentage of total profit attributable to compounding (position sizing) Avg Win — Sum of wins / Win count — Average profitable trade return in percentage Avg Trade — Sum of all returns / Total trades — Same as Expectancy (Column 5). Displayed here for convenience Avg Loss — Sum of losses / Loss count — Average unprofitable trade return in percentage (negative value) Martin Ratio — CAGR / Ulcer Index — Similar to Calmar but uses Ulcer Index instead of Max DD Rolling Expectancy — Mean of rolling window expectancies — Average expectancy calculated across rolling windows. Shows consistency of edge Avg W Dur — Avg duration of winning trades — Average time from entry to exit for winning trades only Max Eq — Highest equity value reached — Peak equity achieved during backtest Min Eq — Lowest equity value reached — Trough equity point. Important for understanding worst-case absolute loss Buy & Hold — (Close_last / Close_first - 1) × 100 — >0%: Passive profit — Return of simply buying and holding the asset from backtest start to end Alpha — Strategy CAGR - Benchmark CAGR — >0: Has skill (beats benchmark) — Excess return above passive benchmark. Positive alpha indicates genuine value-added skill Beta — Covariance(Strategy, Benchmark) / Variance(Benchmark) — <1: Less volatile than market, >1: More volatile — Systematic risk correlation with benchmark Avg L Dur — Avg duration of losing trades — Average time from entry to exit for losing trades only Rolling Sharpe/Sortino — Dynamic based on win rate — >2: Good consistency — Rolling metric across sliding windows. Shows Sharpe if win rate >50%, Sortino if <=50% Curr DD — Current drawdown from peak — Lower is better — Present drawdown percentage. Zero means at new equity high DAR — CAGR adjusted for target DD — Higher is better — Drawdown-Adjusted Return. DAR^5 = CAGR if max DD = 5% Kurtosis — Fourth moment / StdDev^4 - 3 — ~0: Normal, >0: Fat tails, <0: Thin tails — Measures "tailedness" of return distribution (excess kurtosis) Skewness — Third moment / StdDev^3 — >0: Positive skew (big wins), <0: Negative skew (big losses) — Return distribution asymmetry VaR — 5th percentile of returns — Lower absolute is better — Value at Risk at 95% confidence. Maximum expected loss in worst 5% of outcomes Ulcer — sqrt(mean(drawdown^2)) — Lower is better — Ulcer Index - root mean square of drawdowns. Penalizes both depth AND duration ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ MONTE CARLO SIMULATION Purpose Monte Carlo simulation tests strategy robustness by randomizing the order of trades while keeping trade returns unchanged. This simulates alternative equity curves to assess outcome variability. Method Extract all historical trade returns Randomly shuffle the sequence (1000+ iterations) Calculate cumulative equity for each shuffle Build distribution of final outcomes Output The stress test table shows: Median Outcome: 50th percentile result 5th Percentile: Worst 5% of outcomes 95th Percentile: Best 95% of outcomes Success Rate: Percentage of simulations that were profitable Interpretation If 95% of simulations are profitable: Strategy is robust If median is far from actual result: High variance/unreliability If 5th percentile shows large loss: High tail risk ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ WALK-FORWARD ANALYSIS Purpose Walk-Forward Analysis (WFA) is the gold standard for detecting strategy overfitting. It simulates real-world trading by dividing historical data into rolling "training" (in-sample) and "validation" (out-of-sample) periods. A strategy that performs well on unseen data is more likely to succeed in live trading. Method The implementation uses a non-overlapping window approach following AmiBroker's gold standard methodology: Segment Calculation: Total trades divided into N windows (default: 12), IS = ~75%, OOS = ~25%, Step = OOS length Window Structure: Each window has IS (training) followed by OOS (validation). Each OOS becomes the next window's IS (rolling forward) Metrics Calculated: CAGR, Sharpe, Sortino, MaxDD, Win Rate, Expectancy, Profit Factor, Payoff Aggregation: IS metrics averaged across all IS periods, OOS metrics averaged across all OOS periods Output IS CAGR: In-sample annualized return OOS CAGR: Out-of-sample annualized return ( THE key metric ) IS/OOS Sharpe: In/out-of-sample risk-adjusted return Success Rate: % of OOS windows that were profitable Interpretation Robust: IS/OOS CAGR gap <20%, OOS Success Rate >80% Some Overfitting: CAGR gap 20-50%, Success Rate 50-80% Severe Overfitting: CAGR gap >50%, Success Rate <50% Key Principles: OOS is what matters — Only OOS predicts live performance Consistency > Magnitude — 10% IS / 9% OOS beats 30% IS / 5% OOS Window count — More windows = more reliable validation Non-overlapping OOS — Prevents data leakage ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ TABLE DISPLAY Main Table — Organized into three sections: Performance Metrics (Cols 0-6): Net Profit, Payoff, Sample Size, Profit Factor, CAGR, Expectancy, Monthly Trade Statistics (Cols 7-14): Avg Duration, Max CW, Max CL, Win, BE, Loss, Frequency, Exposure Risk Metrics (Cols 15-22): Sharpe, Sortino, Max DD, RoR, R², MAR, CVaR, p-value Color Coding 🟢 Green: Excellent performance 🟠 Orange: Acceptable performance ⚪ Gray: Neutral / Fair 🔴 Red: Poor performance ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ IMPLEMENTATION NOTES Data Source: All metrics calculated from strategy.closedtrades , ensuring compatibility with any Pine Script strategy Calculation Timing: All calculations occur on barstate.islastconfirmedhistory to optimize performance Limitations: Requires at least 1 closed trade for basic metrics, 30+ trades for reliable statistical analysis ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ QUICK NOTES ➙ This library has been developed and refined over two years of real-world strategy testing. Every calculation has been validated against industry-standard quantitative finance references. ➙ The entire codebase is thoroughly documented inline. If you are curious about how a metric is calculated or want to understand the implementation details, dive into the source code -- it is written to be read and learned from. ➙ This description focuses on usage and concepts rather than exhaustively listing every exported type and function. The library source code is thoroughly documented inline -- explore it to understand implementation details and internal logic. ➙ All calculations execute on barstate.islastconfirmedhistory to minimize runtime overhead. The library is designed for efficiency without sacrificing accuracy. ➙ Beyond analysis, this library serves as a learning resource. Study the source code to understand quantitative finance concepts, Pine Script advanced techniques, and proper statistical methodology. ➙ Metrics are their own not binary good/bad indicators. A high Sharpe ratio with low sample size is misleading. A deep drawdown during a market crash may be acceptable. Study each function and metric individually -- evaluate your strategy contextually, not by threshold alone. ➙ All strategies face alpha decay over time. Instead of over-optimizing a single strategy on one timeframe and market, build a diversified portfolio across multiple markets and timeframes. Deeptest helps you validate each component so you can combine robust strategies into a trading portfolio. ➙ Screenshots shown in the documentation are solely for visual representation to demonstrate how the tables and metrics will be displayed. Please do not compare your strategy's performance with the metrics shown in these screenshots -- they are illustrative examples only, not performance targets or benchmarks. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ HOW-TO Using Deeptest is intentionally straightforward. Just import the library and call DT.runDeeptest() at the end of your strategy code in main scope. . //@version=6 strategy("My Strategy", overlay=true) // Import the library import Fractalyst/Deeptest/1 as DT // Your strategy logic fastMA = ta.sma(close, 10) slowMA = ta.sma(close, 30) if ta.crossover(fastMA, slowMA) strategy.entry("Long", strategy.long) if ta.crossunder(fastMA, slowMA) strategy.close("Long") // Run the analysis DT.runDeeptest() And yes... it's compatible with any TradingView Strategy! 🪄 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ CREDITS Author: @Fractalyst Font Library: by @fikira - @kaigouthro - @Duyck Community: Inspired by the @PineCoders community initiative, encouraging developers to contribute open-source libraries and continuously enhance the Pine Script ecosystem for all traders. if you find Deeptest valuable in your trading journey, feel free to use it in your strategies and give a shoutout to @Fractalyst -- Your recognition directly supports ongoing development and open-source contributions to Pine Script. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ █ DISCLAIMER This library is provided for educational and research purposes. Past performance does not guarantee future results. Always test thoroughly and use proper risk management. The author is not responsible for any trading losses incurred through the use of this code.
Pine Script® library
by Fractalyst
4
CVD Flow Labels for Sessions Ranges [AMT Edition]CVD Flow Labels for Session Ranges Description: This script provides a session-aware Cumulative Volume Delta (CVD) analysis designed to enhance the “Session Ranges ” framework by combining price extremes with detailed volume flow dynamics. Unlike generic trend or scalping indicators, this tool focuses on identifying aggressive buying and selling pressure, distinguishing between absorption (failed auctions where aggressive flows are rejected) and acceptance (confirmed continuation of flows). How it works: CVD Calculation: The script calculates delta for each bar using a choice of Total, Periodic, or EMA-based cumulative methods. Delta represents the net difference between estimated buying and selling volume per bar. Normalization: By normalizing delta relative to recent volatility, it highlights extreme flows that are statistically significant, making large shifts in market sentiment easier to spot. Session-Specific Analysis: The indicator separates Asia, London, and New York sessions to allow context-sensitive interpretation of price and volume interactions. Each session’s extremes are monitored, and flow labels are plotted relative to these extremes. Flow Labels: Bullish and bearish absorption (“ABS”) and acceptance (“ACC WEAK/STRONG”) labels provide immediate visual cues about whether aggressive flows are being absorbed or accepted at key price levels. Alerts: Configurable alerts trigger when absorption or acceptance occurs, supporting active trading or strategy automation. Originality & Usefulness: This script is original because it integrates volume-based auction theory with session-specific market structure, rather than simply showing trend or scalping signals. By combining CVD dynamics with session extreme levels from the “Session Ranges ” script, traders can: Identify where price is likely to be accepted or rejected. Confirm aggressive buying or selling flows before entering trades. Time entries near session extremes with higher probability setups. How to use: Apply the “Session Ranges ” to see session highs, lows, and interaction lines. Use this CVD Flow Labels script to visualize absorption and acceptance at these session levels. Enter trades based on alignment of session extremes and flow signals: Absorption at a session extreme may indicate a potential reversal. Acceptance suggests continuation in the direction of the flow. Alerts can help manage trades without constant screen monitoring. This tool is designed to give traders a structured, session-based view of market auctions, providing actionable insights that go beyond typical trend-following or scalping methods. It emphasizes flow analysis and statistical extremes, enabling traders to make more informed decisions grounded in market microstructure.
Pine Script® indicator
by samb817
3
Cosmic Volume Analyzer [JOAT] Cosmic Volume Analyzer - Astrophysics Edition Overview Cosmic Volume Analyzer is an open-source oscillator indicator that applies astrophysics-inspired concepts to volume analysis. It classifies volume into buy/sell categories, calculates volume flow, detects accumulation/distribution phases, identifies climax volume events, and uses gravitational and stellar mass analogies to visualize volume dynamics. What This Indicator Does The indicator calculates and displays: Volume Classification - Categorizes each bar as CLIMAX_BUY, CLIMAX_SELL, HIGH_BUY, HIGH_SELL, NORMAL_BUY, or NORMAL_SELL Volume Flow - Percentage showing buy vs sell pressure over a lookback period Buy/Sell Volume - Separated volume based on candle direction Accumulation/Distribution - Phase detection using Money Flow Multiplier Volume Oscillator - Fast vs slow volume EMA comparison Gravitational Pull - Volume-weighted price attraction metric Stellar Mass Index - Volume ratio combined with price momentum Black Hole Detection - Identifies extremely low volume periods (liquidity voids) Supernova Events - Detects extreme volume with extreme price movement Orbital Cycles - Sine-wave based cyclical visualization How It Works Volume classification uses volume ratio and candle direction: classifyVolume(series float vol, series float close, series float open) => float avgVol = ta.sma(vol, 20) float volRatio = avgVol > 0 ? vol / avgVol : 1.0 if volRatio > 1.5 if close > open classification := "CLIMAX_BUY" else classification := "CLIMAX_SELL" else if volRatio > 1.2 // HIGH_BUY or HIGH_SELL else // NORMAL_BUY or NORMAL_SELL Volume flow separates buy and sell volume over a period: calculateVolumeFlow(series float vol, series float close, simple int period) => float currentBuyVol = close > open ? vol : 0.0 float currentSellVol = close < open ? vol : 0.0 // Accumulate in buffers float flow = (buyVolume - sellVolume) / totalVol * 100 Accumulation/Distribution uses the Money Flow Multiplier: float mfm = ((close - low) - (high - close)) / (high - low) float mfv = mfm * vol float adLine = ta.cum(mfv) if adLine > adEMA and ta.rising(adLine, 3) phase := "ACCUMULATION" else if adLine < adEMA and ta.falling(adLine, 3) phase := "DISTRIBUTION" Gravitational pull uses volume-weighted price distance: gravitationalPull(series float vol, series float price, simple int period) => float massCenter = ta.vwma(price, period) float distance = math.abs(price - massCenter) float mass = vol / ta.sma(vol, period) float gravity = distance > 0 ? mass / (distance * distance) : 0.0 Signal Generation Signals are generated based on volume conditions: Buy Climax: Volume exceeds 2 standard deviations above average on bullish candle Sell Climax: Volume exceeds 2 standard deviations above average on bearish candle Strong Buy Flow: Volume flow exceeds positive threshold (default 45%) Strong Sell Flow: Volume flow exceeds negative threshold (default -45%) Supernova: Volume 3x average AND price change 3x average Black Hole: Volume 2 standard deviations below average Dashboard Panel (Top-Right) Volume Class - Current volume classification Volume Flow - Buy/sell flow percentage Buy Volume - Accumulated buy volume Sell Volume - Accumulated sell volume A/D Phase - ACCUMULATION/DISTRIBUTION/NEUTRAL Volume Strength - Normalized volume strength Gravity Pull - Current gravitational metric Stellar Mass - Current stellar mass index Cosmic Field - Combined cosmic field strength Black Hole - Detection status and void strength Signal - Current actionable status Visual Elements Volume Ratio Columns - Colored bars showing normalized volume Volume Flow Line - Main oscillator showing flow direction Flow EMA - Smoothed flow for trend reference Volume Oscillator - Area plot showing fast/slow comparison Gravity Field - Area plot showing gravitational pull Orbital Cycle - Circle plots showing cyclical pattern Stellar Mass Line - Line showing mass index Climax Markers - Fire emoji for buy climax, snowflake for sell climax Supernova Markers - Diamond shapes for extreme events Black Hole Markers - X-cross for liquidity voids A/D Phase Background - Subtle background color based on phase Input Parameters Volume Period (default: 20) - Period for volume calculations Distribution Levels (default: 5) - Granularity of distribution analysis Flow Threshold (default: 1.5) - Multiplier for flow significance Accumulation Period (default: 14) - Period for A/D calculation Gravitational Analysis (default: true) - Enable gravity metrics Black Hole Detection (default: true) - Enable void detection Stellar Mass Calculation (default: true) - Enable mass index Orbital Cycles (default: true) - Enable cyclical visualization Supernova Detection (default: true) - Enable extreme event detection Suggested Use Cases Identify accumulation phases for potential long entries Watch for distribution phases as potential exit signals Use climax volume as potential exhaustion indicators Monitor volume flow for directional bias Avoid trading during black hole (low liquidity) periods Watch for supernova events as potential trend acceleration Timeframe Recommendations Best on 15m to Daily charts. Volume analysis requires sufficient trading activity for meaningful readings. Limitations Volume data quality varies by exchange and instrument Buy/sell separation is based on candle direction, not actual order flow Astrophysics concepts are analogies, not literal physics A/D phase detection may lag during rapid transitions Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management. - Made with passion by officialjackofalltrades
Pine Script® indicator
by officialjackofalltrades
Session Anchored OIWAP [Arjo]The Session Anchored OIWAP (Open Interest Weighted Average Price) indicator shows you a weighted average price that uses Open Interest (OI) changes during different trading sessions . It divides the day into four clear sessions: Opening Hour , Morning Session , Mid-Day Session , and Closing Session . For each session , it calculates a weighted average price using both market price and open interest data from futures . This line updates as the session progresses and resets when a new session starts . You can also see optional deviation bands that you visually compare to how far the market price is moving away from the session’s weighted average. This indicator also helps you watch how Open Interest changes connect with price movements during specific market hours. Concepts This tool works on a few simple ideas: Session anchoring Each session starts fresh. The indicator resets and begins a new calculation when a new time block begins. This allows users to visually study each session independently. Open-interest weighting Instead of treating all price moves equally, price changes linked to higher open-interest activity have more influence on the OIWAP. This gives a weighted reflection of where the market has been trading during the session. Averaging and smoothing The OIWAP line blends many price data points into one smooth curve, making it easier to follow than raw price movement. Volatility display with bands The upper and lower bands are placed at ±0.5 standard deviation from the OIWAP line. These bands simply help you see when price stretches further away than usual from the session average. Features Four Independent Session Calculations: Shows separate OIWAP lines for Opening Hour (default: 09:15-10:15), Morning (10:15-11:30), Mid-Day (11:30-14:00), and Closing (14:00-15:30) sessions Open Interest Weighting: Uses absolute OI change as the weight instead of traditional volume Customizable Session Times: You can change the time ranges for each session to match your market or what you need Optional Deviation Bands: You can turn ±0.5 standard deviation bands on or off around each OIWAP line Color-Coded Sessions: Each session has its own color so you can tell them apart easily Selective Display: You can turn individual sessions and bands on or off Data Availability Check: Shows you a notification when Open Interest data isn't available for your symbol Adjustable Position Timeframe: You can calculate OI changes on different timeframes (Chart, Daily, 15min, 30min, 60min, 120min) How to use Add this indicator to a chart of any symbol that has Open Interest data ( from futures or derivatives contracts). Once you add it, you'll see colored lines showing the OIWAP for each session you enable, along with optional deviation bands. Adjusting Settings: Turn individual sessions on or off using the checkboxes in the " Sessions " section Change session colors to match your chart or what looks good to you Turn deviation bands on or off using the " Show Bands " option in the Display settings Change session time ranges in the " Session Times " section to match your market hours or what you want to analyze Change the Position Timeframe if you want to see OI changes calculated on a different time period Visual Interpretation: Each OIWAP line shows you the OI-weighted average price for that session The deviation bands show you how much prices spread out, weighted by OI changes You can watch how price interacts with these levels to see where significant OI activity happened Different sessions may show different OIWAP levels, showing you how the OI-price relationship changes throughout the trading day Note: This indicator needs Open Interest data to work. If OI data isn't available for your symbol, you'll see a message in the center of your chart. This indicator works only with derivatives markets like futures and options in the Indian Market where OI data is publicly available. Conclusion The Session Anchored OIWAP indicator is designed to support structured market observation by combining price, open interest, and session anchoring into a clear visual format. It helps users study market behavior during different parts of the day without generating trading instructions or outcomes. Disclaimer This indicator is for educational and visual-analysis purposes only. It does not provide trading signals , financial advice, or guaranteed outcomes . You should perform your own research and consult a licensed financial professional when needed. All trading decisions are solely the responsibility of the user. Happy Trading
Pine Script® indicator
by ARJO_2019
Zero Lag Moving Average Convergence Divergence (ZLMACD) [EVAI]Zero Lag Moving Average Convergence Divergence (ZLMACD) ZLMACD is a MACD-style momentum oscillator that keeps the standard MACD structure while adding a practical “zero-lag” option through ZLEMA. It is intended for traders who like the familiar MACD workflow but want an oscillator that can respond earlier during transitions without turning into an overly noisy trigger. The indicator plots the MACD line, the signal line, and the histogram around a zero baseline. If you already understand MACD, you already understand how to read this. The difference is that you can choose whether the oscillator and signal are driven by EMA, SMA, or ZLEMA, which changes the responsiveness and smoothness of the indicator. Default behavior This script defaults to the preset mode “ZLEMA osc + EMA signal.” In this configuration, the fast and slow oscillator averages are computed using ZLEMA, while the signal line remains an EMA of the MACD line. The reason for this mix is simple: ZLEMA tends to reduce lag in the oscillator, while EMA on the signal line helps keep crossovers readable and avoids excessive micro-signals. In practice, this default preset often behaves like a “faster MACD” that still feels like MACD. It can highlight momentum turns earlier than a traditional EMA MACD while keeping the signal line stable enough to use for timing and confirmation. Custom mode and MA selection If you switch Mode to “Custom,” the indicator will use your selected moving average types for both the oscillator and the signal line. In Custom mode, the oscillator type applies to both fast and slow averages, and the signal type applies to the smoothing of the MACD line. If you are in the default preset mode, the custom MA dropdowns will not change the calculations. This is intentional: the preset locks the MA types so the default behavior remains consistent and reproducible across charts and users. Reading the indicator The histogram reflects the distance between the MACD line and the signal line. When the histogram is above zero, the MACD line is above the signal line and momentum is biased upward; when it is below zero, the MACD line is below the signal line and momentum is biased downward. Changes in histogram height help visualize strengthening versus weakening momentum, while the zero baseline provides regime context by indicating whether the fast average is above or below the slow average. Crossovers between MACD and signal behave exactly as they do in standard MACD, but the timing and “feel” will vary depending on the MA choices. ZLEMA on the oscillator typically makes turns appear earlier; SMA typically smooths more but can be slower; EMA tends to be the balanced baseline. Alerts Two alert conditions are included to detect histogram polarity shifts. One triggers when the histogram switches from non-negative to negative, and the other triggers when it switches from non-positive to positive. These are useful if you want simple notifications for momentum regime flips without staring at the chart continuously. Notes This indicator is provided for informational and educational purposes only and is not financial advice. Always test settings per instrument and timeframe and use risk management.
Pine Script® indicator
by evaiinvesting
Power Hour Trendlines [LuxAlgo]The Power Hour Trendlines indicator is based on Power Hours detection, and includes up to three displayed trendlines derived from the closing prices of all the bars within the last user-selected Power Hours. Users can edit the time of Power Hours, choose how many sessions to take into account, enable or disable any trendlines, and change their colors. 🔶 USAGE The Power Hour is defined as the last hour of the trading session and is set by default from 3:00 p.m. to 4:00 p.m. New York time. During this period, volume and volatility enter the market. Traders using higher timeframes may use this period to enter or exit positions by placing MOC (Market on Close) orders. This tool works under the hypothesis that prices made during power hours (periods with high trading activity) are more relevant when used for the construction of trendlines. An initial trendline is fit using linear regression; prices from power hours located above this initial fit are used for the upper trendline, while the ones below the fit are used for the lower one. As with any trendline, traders can analyze the slope to determine the market's direction: Positive slope: The market is trending up. Negative slope: The market is trending down. No slope: The market is trending sideways. As we can see in the image, Nasdaq and Bitcoin are clearly in downtrends, gold is clearly in an uptrend, and the euro/U.S. dollar is in a sideways market over the last visible sessions. As you can see, the trend lines may or may not be parallel to each other. The wider the area, the more volatile the data. The narrower the area, the less volatile the data. Let's look at an example. In the image, the Dow30 and the euro/U.S. dollar have opposite behaviors. The volatility above the middle trendline is growing in the first case but shrinking in the second. In both cases, the volatility in the bottom area seems steady, so there are no big surprises there. Traders can adjust the number of sessions for calculations, making the tool ideal for analyzing price behavior over different time frames. As the image shows, we can clearly see how the market behaves over different time periods. XLY has been moving down over the last 10, 20, and 40 sessions, with a steeper decline over shorter periods. However, it has been moving sideways over the last 70 sessions. One of the main uses of trendlines is to provide key support and resistance. In the image, SPY is shown with trendlines over the last 20 sessions. These lines provide excellent reference points for trading and observing price behavior in those areas, such as whether prices are accepted or rejected, which may trigger a response from other traders. 🔹 Not Allowed Timeframes For obvious reasons, timeframes larger than 1H are not allowed. The Power Hour is defined as the last hour of the trading session. The tool will display a warning message if the timeframe is longer than 60 minutes. 🔶 SETTINGS Power Hour (NY Time): Choose a custom Power Hour in New York time Sessions Memory: Select how many Power Hours to take into account for calculations. 🔹 Style Top: Enable or disable the top line and choose the line and background colors. Middle: Enable or disable the middle line and choose the line color. Bottom: Enable or disable the bottom line and choose the line and background colors. Background: Enable or disable the background color for top and bottom lines.
Pine Script® indicator
by LuxAlgo
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