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Cumulative Returns by Session [BackQuant]Cumulative Returns by Session What this is This tool breaks the trading day into three user-defined sessions and tracks how much each session contributes to return, volatility, and volume. It then aggregates results over a rolling window so you can see which session has been pulling its weight, how streaky each session has been, and how sessions relate to one another through a compact correlation heatmap. We’ve also given the functionality for the user to use a simplified table, just by switching off all settings they are not interested in. How it works 1) Session segmentation You define APAC, EU, and US sessions with explicit hours and time zones. The script detects when each session starts and ends on every intraday bar and records its open, intraday high and low, close, and summed volume. 2) Per-session math At each session end the script computes: Return — either Percent: (Close−Open)÷Open×100(Close − Open) ÷ Open × 100(Close−Open)÷Open×100 or Points: (Close−Open)(Close − Open)(Close−Open), based on your selection. Volatility — either Range: (High−Low)÷Open×100(High − Low) ÷ Open × 100(High−Low)÷Open×100 or ATR scaled by price: ATR÷Open×100ATR ÷ Open × 100ATR÷Open×100. Volume — total volume transacted during that session. 3) Storage and lookback Each day’s three session stats are stored as a row. You choose how many recent sessions to keep in memory. The script then: Builds cumulative returns for APAC, EU, US across the lookback. Computes averages, win rates, and a Sharpe-like ratio avgreturn÷avgvolatilityavg return ÷ avg volatilityavgreturn÷avgvolatility per session. Tracks streaks of positive or negative sessions to show momentum. Tracks drawdowns on cumulative returns to show worst runs from peak. Computes rolling means over a short window for short-term drift. 4) Correlation heatmap Using the stored arrays of session returns, the script calculates Pearson correlations between APAC–EU, APAC–US, and EU–US, and colors the matrix by strength and sign so you can spot coupling or decoupling at a glance. What it plots Three lines: cumulative return for APAC, EU, US over the chosen lookback. Zero reference line for orientation. A statistics table with cumulative %, average %, positive session rate, and optional columns for volatility, average volume, max drawdown, current streak, return-to-vol ratio, and rolling average. A small correlation heatmap table showing APAC, EU, US cross-session correlations. How to use it Pick the asset — leave Custom Instrument empty to use the chart symbol, or point to another symbol for cross-asset studies. Set your sessions and time zones — defaults approximate APAC, EU, and US hours, but you can align them to exchange times or your workflow. Choose calculation modes — Percent vs Points for return, Range vs ATR for volatility. Points are convenient for futures and fixed-tick assets, Percent is comparable across symbols. Decide the lookback — more sessions smooths lines and stats; fewer sessions makes the tool more reactive. Toggle analytics — add volatility, volume, drawdown, streaks, Sharpe-like ratio, rolling averages, and the correlation table as needed. Why session attribution helps Different sessions are driven by different flows. Asia often sets the overnight tone, Europe adds liquidity and direction changes, and the US session can dominate range expansion. Separating contributions by session helps you: Identify which session has been the main driver of net trend. Measure whether volatility or volume is concentrated in a specific window. See if one session’s gains are consistently given back in another. Adapt tactics: fade during a mean-reverting session, press during a trending session. Reading the tables Cumulative % — sum of session returns over the lookback. The sign and slope tell you who is carrying the move. Avg Return % and Positive Sessions % — direction and hit rate. A low average but high hit rate implies many small moves; the reverse implies occasional big swings. Avg Volatility % — typical intrabars range for that session. Compare with Avg Return to judge efficiency. Return/Vol Ratio — return per unit of volatility. Higher is better for stability. Max Drawdown % — worst cumulative give-back within the lookback. A quick way to spot riskiness by session. Current Streak — consecutive up or down sessions. Useful for mean-reversion or regime awareness. Rolling Avg % — short-window drift indicator to catch recent turnarounds. Correlation matrix — green clusters indicate sessions tending to move together; red indicates offsetting behavior. Settings overview Basic Number of Sessions — how many recent days to include. Custom Instrument — analyze another ticker while staying on your current chart. Session Configuration and Times Enable or hide APAC, EU, US rows. Set hours per session and the specific time zone for each. Calculation Methods Return Calculation — Percent or Points. Volatility Calculation — Range or ATR; ATR Length when applicable. Advanced Analytics Correlation, Drawdown, Momentum, Sharpe-like ratio, Rolling Statistics, Rolling Period. Display Options and Colors Show Statistics Table and its position. Toggle columns for Volatility and Volume. Pick individual colors for each session line and row accents. Common applications Session bias mapping — find which window tends to trend in your market and plan exposure accordingly. Strategy scheduling — allocate attention or risk to the session with the best return-to-vol ratio. News and macro awareness — see if correlation rises around central bank cycles or major data releases. Cross-asset monitoring — set the Custom Instrument to a driver (index future, DXY, yields) to see if your symbol reacts in a particular session. Notes This indicator works on intraday charts, since sessions are defined within a day. If you change session clocks or time zones, give the script a few bars to accumulate fresh rows. Percent vs Points and Range vs ATR choices affect comparability across assets, so be consistent when comparing symbols. Session context is one of the simplest ways to explain a messy tape. By separating the day into three windows and scoring each one on return, volatility, and consistency, this tool shows not just where price ended up but when and how it got there. Use the cumulative lines to spot the steady driver, read the table to judge quality and risk, and glance at the heatmap to learn whether the sessions are amplifying or canceling one another. Adjust the hours to your market and let the data tell you which session deserves your focus.
Pine Script® 인디케이터
BackQuant의
Zarattini Intra-day Threshold Bands (ZITB)This indicator implements the intraday threshold band methodology described in the research paper by Carlo Zarattini et al. papers.ssrn.com Overview: Plots intraday threshold bands based on daily open/close levels. Supports visualization of BaseUp/BaseDown levels and Threshold Upper/Lower bands. Optional shading between threshold bands for easier interpretation. Usage Notes / Limitations: Originally studied on SPY (US equities), this implementation is adapted for NSE intraday market timing, specifically the NIFTY50 index. Internally, 2-minute candles are used if the chart timeframe is less than 2 minutes. Values may be inaccurate if the chart timeframe is more than 1 day. Lookback days are auto-capped to avoid exceeding TradingView’s 5000-bar limit. The indicator automatically aligns intraday bars across multiple days to compute average deltas. For better returns, it is recommended to use this indicator in conjunction with VWAP and a volatility-based position sizing mechanism. Can be used as a reference for Open Range Breakout (ORB) strategies. Customizations: Toggle plotting of base levels and thresholds. Toggle shading between thresholds. Line colors and styles can be adjusted in the Style tab. Author: Gokul Ramachandran – software architect, engineer, programmer. Interested in trading and investment. Currently trading and researching strategies that can be employed in NSE (Indian market). Contact: (mailto:gokul4trading@gmail.com) LinkedIn: www.linkedin.com Intended for educational and research purposes only.
Pine Script® 인디케이터
gokul4trading의
1
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading. "Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤖 THE MACHINE LEARNING Gaussian Mixture Models (GMM): Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering : Models data as coming from multiple Gaussian distributions Each market regime is a different Gaussian component Provides probability of belonging to each regime More sophisticated than simple clustering Expectation-Maximization Algorithm: The indicator continuously learns and adapts using the E-M algorithm: E-step: Calculate probability of current market belonging to each regime M-step: Update regime parameters based on new data Continuous learning without repainting Adapts to changing market conditions ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 THREE MARKET REGIMES The GMM identifies three distinct market states: Regime 1 - Low Volatility: Quiet, ranging markets Uses RSI-based momentum calculation Reduces false signals in choppy conditions Background: Pink tint Regime 2 - Normal Market: Standard trending conditions Uses Rate of Change momentum Balanced sensitivity Background: Gray tint Regime 3 - High Volatility: Strong trends or volatility events Uses Z-score based momentum Captures extreme moves Background: Cyan tint ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 KEY INNOVATIONS 1. Probabilistic Regime Detection: Instead of binary regime assignment, provides probabilities: 30% Regime 1, 60% Regime 2, 10% Regime 3 Smooth transitions between regimes No sudden indicator jumps 2. Weighted Momentum Calculation: Combines three different momentum formulas Weights based on regime probabilities Automatically adapts to market conditions 3. Confidence Indicator: Shows how certain the model is (white line) High confidence = strong regime identification Low confidence = transitional market state Line transparency changes with confidence ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION Training Period (50-500): 50-100: Quick adaptation to recent conditions 100: Balanced (default) 200-500: Stable regime identification Number of Components (2-5): 2: Simple bull/bear regimes 3: Low/Normal/High volatility (default) 4-5: More granular regime detection Learning Rate (0.1-1.0): 0.1-0.3: Slow, stable learning 0.3: Balanced (default) 0.5-1.0: Fast adaptation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Visual Signals: Cyan gradient: Bullish momentum Magenta gradient: Bearish momentum Background color: Current regime Confidence line: Model certainty 1. Regime-Based Trading: Regime 1 (pink): Expect mean reversion Regime 2 (gray): Standard trend following Regime 3 (cyan): Strong momentum trades 2. Confidence-Filtered Signals: Only trade when confidence > 70% High confidence = clearer market state Avoid transitions (low confidence) 3. Adaptive Position Sizing: Regime 1: Smaller positions (choppy) Regime 2: Normal positions Regime 3: Larger positions (trending) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 ADVANTAGES OVER OTHER ML INDICATORS vs K-Means Clustering: Soft clustering (probabilities) vs hard boundaries Captures uncertainty and transitions More mathematically robust vs KNN (K-Nearest Neighbors): Unsupervised learning (no historical labels needed) Continuous adaptation Lower computational complexity vs Neural Networks: Interpretable (know what each regime means) No overfitting issues Works with limited data ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Best Market Conditions: Markets with clear regime shifts Volatile to trending transitions Multi-timeframe analysis Cryptocurrency markets (high regime variation) Key Strengths: Automatically adapts to market changes No manual parameter adjustment needed Smooth transitions between regimes Probabilistic confidence measure ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 TECHNICAL BACKGROUND Gaussian Mixture Models are used extensively in: Speech recognition (Google Assistant) Computer vision (facial recognition) Astronomy (galaxy classification) Genomics (gene expression analysis) Finance (risk modeling at investment banks) The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 PRO TIPS Watch regime transitions: Best opportunities often occur when regimes change Combine with volume: High volume + regime change = strong signal Use confidence filter: Avoid low confidence periods Multi-timeframe: Compare regimes across timeframes Adjust position size: Scale based on identified regime ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTES Machine learning adapts but doesn't predict the future Best used with other confirmation indicators Allow time for model to learn (100+ bars) Not financial advice - educational purposes Backtest thoroughly on your instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides: Automatic adaptation to market conditions Clear regime identification with confidence levels Smooth, professional signal generation True unsupervised machine learning This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in: Google's speech recognition Tesla's computer vision NASA's data analysis Wall Street risk models "Let the machine learn the market regimes. Trade with statistical confidence." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Machine Learning Trading Systems Version: 1.0 Algorithm: Gaussian Mixture Model with E-M Classification: Unsupervised Learning Oscillator Not financial advice. Always DYOR.
Pine Script® 인디케이터
AlphaNatt의
Script_Algo - Pivot Trend Rider Strategy📌 This strategy aims to enter a trade in the direction of the trend, catching a reversal point at the end of a correction. The script is unique due to the combination of three key elements: 🔹 Detection of reversal points through searching for local lows and highs 🔹 Trend filter based on SMA for trading only in the trend direction 🔹 Adaptive risk management using ATR for dynamic stop-losses and take-profits This allows the strategy to work effectively in various market conditions, minimizing false signals and adapting to market volatility. ⚙️ Principle of Operation The strategy is based on the following logical components: 📈 Entry Signals: Long: when a local low (pivot low) is detected in an uptrend Short: when a local high (pivot high) is detected in a downtrend 📉 Position Management: Stop-loss and take-profit are calculated based on ATR Automatic reverse switching when an opposite signal appears 📊 Trend Filter: Uses SMA to determine trend direction (can be disabled if needed) 🔧 Default Settings Pivot detection: 11 bars SMA filter length: 16 periods ATR period: 14 SL multiplier: 2.5 TP multiplier: 10 Trend filter: enabled 🕒 Usage Recommendations Timeframe: from 1 hour and above Assets: cryptocurrency pairs, stocks 🤖 Trading Automation This script is fully ready for integration with cryptocurrency exchanges via Webhook. 📊 Backtest Results As seen from testing results, over 4.5 years this strategy could have potentially generated about $5000 profit or 50% of initial capital on the NAERUSDT crypto pair on the 4H timeframe. Position size: $1000 Max drawdown: $1400 Total trades: 376 Win rate: 38% Profit factor: 1.34 ⚠️ Disclaimer Please note that the results of the strategy are not guaranteed to repeat in the future. The market constantly changes, and no algorithm can predict exactly how an asset will behave. The author of this strategy is not responsible for any financial losses associated with using this script. All trading decisions are made solely by the user. Trading financial markets carries high risks and can lead to loss of your investments. Before using the strategy, it is strongly recommended to: ✅ Backtest the strategy on historical data ✅ Start with small trading volumes ✅ Use only risk capital you are ready to lose ✅ Fully understand how the strategy works 🔮 Further Development The strategy will continue to evolve and improve. Planned updates include: Adding additional filters to reduce false signals Optimizing position management algorithms Expanding functionality for various market conditions 💡 Wishing everyone good luck and profitable trading! 📈 May your charts be green and your portfolios keep growing! Developed by Script_Algo | MIT License | Version 1.0
Pine Script™ 전략
Script_Algo의
Pro Trend: Double BB + Chandelier + ZigZag by KidevThis indicator combines multiple powerful tools into a single overlay: Bollinger Bands (0.5σ & 2σ): Tracks short-term and wider volatility ranges. SMA 75: Smooth trend filter to identify medium-term direction. Centered Chandelier Exit: Dynamic stop/trend tool based on ATR; midline highlights trend bias. Double ZigZag with HH/LL Labels: Two independent ZigZags (configurable periods) mark pivots and identify Higher Highs / Higher Lows / Lower Highs / Lower Lows. Quickly visualize volatility channels and trend direction. Identify breakout vs. mean-reversion conditions. Spot pivot structure (HH/HL vs. LH/LL) for market structure analysis. Combine ATR-based stop levels with SMA filter for trade entries/exit
Pine Script® 인디케이터
kidevswamynathan의
Pivot Point TrendOverview A trend-following trailing line built from confirmed pivot highs/lows and ATR bands. The line turns green in uptrends and red in downtrends. A flip happens only when price closes on the other side of the opposite trail, helping filter noise. How it works: Finds confirmed swing points (pivots) and builds a smoothed center from them. From that center, creates ATR-based bands. The active trail “locks” in the trend: in uptrends it never moves down; in downtrends it never moves up. Close above the prior upper trail → bullish; close below the prior lower trail → bearish. Inputs Pivot Point Period (prd) – strictness of pivot confirmation (delay = prd bars). ATR Period (pd) and ATR Factor (factor) – band width; higher values = fewer flips. Calculation timeframe (calcTF) – leave empty to use chart TF, or set a hard TF like 1D, 4H. Show Center Line – optional central guide. Line Width – trail thickness. Alerts Bullish Flip – trend turns bullish. Bearish Flip – trend turns bearish. Trend Changed – any flip event. Usage tips Typical crypto intraday starters: prd 2–5, pd 10–14, factor 2.5–3.5. For smoother signals, compute on a higher TF (e.g., calcTF = 1D) and time entries on your lower TF. Prefer actions on bar close of the calculation TF to avoid intrabar whipsaw. Notes on repainting The script uses request.security(..., lookahead_off). Pivots confirm after prd bars by design; once confirmed, the center and trails do not use future data. Evaluate flips on bar close for consistency, especially when calcTF > chart TF. Disclaimer Educational use only. Not financial advice. Trading involves risk.
Pine Script® 인디케이터
trading_mura의
MatrixScalper Tablo + 3 Bant Osilatör MatrixScalper “Table + 3-Band Oscillator” is a lightweight, multi-timeframe trend-momentum filter that stacks three histograms (TF1/TF2/TF3—default 5m/15m/1h) and a compact table showing EMA trend, Supertrend, RSI and MACD direction for each timeframe. Green bars/✓ mean bullish alignment, red bars/✗ bearish; mixed or gray implies neutrality. Use it to trade with the higher-timeframe bias (e.g., look for longs when 15m & 60m are bullish and the 5m band flips back to green after a pullback). It’s a filter—not a standalone signal—so combine with price action/S&R/volume; optional alerts can be added for “all-bull” or “all-bear” alignment.
Pine Script® 인디케이터
NizamettinGOZEL의
Deadband Hysteresis Supertrend [BackQuant]Deadband Hysteresis Supertrend A two-stage trend tool that first filters price with a deadband baseline, then runs a Supertrend around that baseline with optional flip hysteresis and ATR-based adverse exits. What this is A hybrid of two ideas: Deadband Hysteresis Baseline that only advances when price pulls far enough from the baseline to matter. This suppresses micro noise and gives you a stable centerline. Supertrend bands wrapped around that baseline instead of raw price. Flips are further gated by an extra margin so side changes are more deliberate. The goal is fewer whipsaws in chop and clearer regime identification during trends. How it works (high level) Deadband step — compute a per-bar “deadband” size from one of four modes: ATR, Percent of price, Ticks, or Points. If price deviates from the baseline by more than this amount, move the baseline forward by a fraction of the excess. If not, hold the line. Centered Supertrend — build upper and lower bands around the baseline using ATR and a user factor. Track the usual trailing logic that tightens a band while price moves in its favor. Flip hysteresis — require price to exceed the active band by an extra flip offset × ATR before switching sides. This adds stickiness at the boundary. Adverse exit — once a side is taken, trigger an exit if price moves against the entry by K × ATR . If you would like to check out the filter by itself: What it plots DBHF baseline (optional) as a smooth centerline. DBHF Supertrend as the active trailing band. Candle coloring by trend side for quick read. Signal markers 𝕃 and 𝕊 at flips plus ✖ on adverse exits. Inputs that matter Price Source — series being filtered. Close is typical. HL2 or HLC3 can be steadier. Deadband mode — ATR, Percent, Ticks, or Points. This defines the “it’s big enough to matter” zone. ATR Length / Mult (DBHF) — only used when mode = ATR. Larger values widen the do-nothing zone. Percent / Ticks / Points — alternatives to ATR; pick what fits your market’s convention. Enter Mult — scales the deadband you must clear before the baseline moves. Increase to filter more noise. Response — fraction of the excess applied to baseline movement. Higher responds faster; lower is smoother. Supertrend ATR Period & Factor — traditional band size controls; higher factor widens and flips less often. Flip Offset ATR — extra ATR buffer required to flip. Useful in choppy regimes. Adverse Stop K·ATR — per-trade danger brake that forces an exit if price moves K×ATR against entry. UI — toggle baseline, supertrend, signals, and bar painting; choose long and short colors. How to read it Green regime — candles painted long and the Supertrend running below price. Pullbacks toward the baseline that fail to breach the opposite band often resume higher. Red regime — candles painted short and the Supertrend running above price. Rallies that cannot reclaim the band may roll over. Frequent side swaps — reduce sensitivity by increasing Enter Mult, using ATR mode, raising the Supertrend factor, or adding Flip Offset ATR. Use cases Bias filter — allow entries only in the direction of the current side. Use your preferred triggers inside that bias. Trailing logic — treat the active band as a dynamic stop. If the side flips or an adverse K·ATR exit prints, reduce or close exposure. Regime map — on higher timeframes, the combination baseline + band produces a clean up vs down template for allocation decisions. Tuning guidance Fast markets — ATR deadband, modest Enter Mult (0.8–1.2), response 0.2–0.35, Supertrend factor 1.7–2.2, small Flip Offset (0.2–0.5 ATR). Choppy ranges — widen deadband or raise Enter Mult, lower response, and add more Flip Offset so flips require stronger evidence. Slow trends — longer ATR periods and higher Supertrend factor to keep you on side longer; use a conservative adverse K. Included alerts DBHF ST Long — side flips to long. DBHF ST Short — side flips to short. Adverse Exit Long / Short — K·ATR stop triggers against the current side. Strengths Deadbanded baseline reduces micro whipsaws before Supertrend logic even begins. Flip hysteresis adds a second layer of confirmation at the boundary. Optional adverse ATR stop provides a uniform risk cut across assets and regimes. Clear visuals and minimal parameters to adjust for symbol behavior. Putting it together Think of this tool as two decisions layered into one view. The deadband baseline answers “does this move even count,” then the Supertrend wrapped around that baseline answers “if it counts, which side should I be on and where do I flip.” When both parts agree you tend to stay on the correct side of a trend for longer, and when they disagree you get an early warning that conditions are changing. When the baseline bends and price cannot reclaim the opposite band , momentum is usually continuing. Pullbacks into the baseline that stall before the far band often resolve in trend. When the baseline flattens and the bands compress , expect indecision. Use the Flip Offset ATR to avoid reacting to the first feint. Wait for a clean band breach with follow through. When an adverse K·ATR exit prints while the side has not flipped , treat it as a risk event rather than a full regime change. Many users cut size, re-enter only if the side reasserts, and let the next flip confirm a new trend. Final thoughts Deadband Hysteresis Supertrend is best read as a regime lens. The baseline defines your tolerance for noise, the bands define your trailing structure, and the flip offset plus adverse ATR stop define how forgiving or strict you want to be at the boundary. On strong trends it helps you hold through shallow shakeouts. In choppy conditions it encourages patience until price does something meaningful. Start with settings that reflect the cadence of your market, observe how often flips occur, then nudge the deadband and flip offset until the tool spends most of its time describing the move you care about rather than the noise in between.
Pine Script® 인디케이터
BackQuant의
2
Trend FriendTrend Friend — What it is and how to use it I built Trend Friend to stop redrawing the same trendlines all day. It automatically connects confirmed swing points (fractals) and keeps the most relevant lines in front of you. The goal: give you clean, actionable structure without the guesswork. What it does (in plain English) Finds swing highs/lows using a Fractal Period you choose. Draws auto-trendlines between the two most recent confirmed highs and the two most recent confirmed lows. Colours by intent: Lines drawn from highs (potential resistance / bearish) = Red Lines drawn from lows (potential support / bullish) = Green Keeps the chart tidy: The newest lines are styled as “recent,” older lines are dimmed as “historical,” and it prunes anything beyond your chosen limit. Optional crosses & alerts: You can highlight when price closes across the most recent line and set alerts for new lines formed and upper/lower line crosses. Structure labels: It tags HH, LH, HL, LL at the swing points, so you can quickly read trend/rotation. How it works (under the hood) A “fractal” here is a confirmed pivot: the highest high (or lowest low) with n bars on each side. That means pivots only confirm after n bars, so signals are cleaner and less noisy. When a new pivot prints, the script connects it to the prior pivot of the same type (high→high, low→low). That gives you one “bearish” line from highs and one “bullish” line from lows. The newest line is marked as recent (brighter), and the previous recent line becomes historical (dimmed). You can keep as many pairs as you want, but I usually keep it tight. Inputs you’ll actually use Fractal Period (n): this is the big one. It controls how swingy/strict the pivots are. Lower n → more swings, more lines (faster, noisier) Higher n → fewer swings, cleaner lines (slower, swing-trade friendly) Max pair of lines: how many pairs (up+down) to keep on the chart. 1–3 is a sweet spot. Extend: extend lines Right (my default) or Both ways if you like the context. Line widths & colours: recent vs. historical are separate so you can make the active lines pop. Show crosses: toggle the X markers when price crosses a line. I turn this on when I’m actively hunting breakouts/retests. Reading the chart Red lines (from highs): I treat these as potential resistance. A clean break + hold above a red line often flips me from “fade” to “follow.” Green lines (from lows): Potential support. Same idea in reverse: break + hold below and I stop buying dips until I see structure reclaim. HH / LH / HL / LL dots: quick read on structure. HH/HL bias = uptrend continuation potential LH/LL bias = downtrend continuation potential Mixed prints = rotation/chop—tighten risk or wait for clarity. My H1 guidance (fine-tuning Fractal Period) If you’re mainly on H1 (my use case), tune like this: Fast / aggressive: n = 6–8 (lots of signals, good for momentum days; more chop risk) Balanced (recommended): n = 9–12 (keeps lines meaningful but responsive) Slow / swing focus: n = 13–21 (filters noise; better for trend days and higher-TF confluence) Rule of thumb: if you’re getting too many touches and whipsaws, increase n. If you’re late to obvious breaks, decrease n. How I trade it (example workflow) Pick your n for the session (H1: start at 9–12). Mark the recent red & green lines. That’s your immediate structure. Look for interaction: Rejections from a line = fade potential back into the range. Break + close across a line = watch the retest for continuation. Confirm with context: session bias, HTF structure, and your own tools (VWAP, RSI, volume, FVG/OB, etc.). Plan the trade: enter on retest or reclaim, stop beyond the line/last swing, target the opposite side or next structure. Alerts (set and forget) “New trendline formed” — fires when a new high/low pivot confirms and a fresh line is drawn. “Upper/lower trendline crossed” — fires when price crosses the most recent red/green line. Use these to track structure shifts without staring at the screen. Good to know (honest limitations) Confirmation lag: pivots need n bars on both sides, so signals arrive after the swing confirms. That’s by design—less noise, fewer fake lines. Lines update as structure evolves: when a new pivot forms, the previous “recent” line becomes “historical,” and older ones can be removed based on your max setting. Not an auto trendline crystal ball: it won’t predict which line holds or breaks—it just keeps the most relevant structure clean and up to date. Final notes Works on any timeframe; I built it with H1 in mind and scale to H4/D1 by increasing n. Pairs nicely with session tools and VWAP for intraday, or with supply/demand / FVGs for swing planning. Risk first: lines are structure, not guarantees. Manage position size and stops as usual. Not financial advice. Trade your plan. Stay nimble.
Pine Script® 인디케이터
OakleyJM의
1
BUY & SELL Probability (M5..D1) - MTFMTF Probability Indicator (M5 to D1) Indicator — Dual Histogram with Buy/Sell Labels This indicator is designed to provide a probabilistic bias for bullish or bearish conditions by combining three different analytical components across multiple timeframes. The goal is to reduce noise from single-indicator signals and instead highlight confluence where trend, momentum, and strength agree. Why this combination is useful - EMA(200) Trend Filter: Identifies whether price is trading above or below a widely used long-term moving average. - MACD Momentum: Detects short-term directional momentum through line crossovers. - ADX Strength: Measures how strong the trend is, preventing signals in weak or flat markets. By combining these, the indicator avoids situations where one tool signals a trade but others do not, helping to filter out low-probability setups. How it works - Each timeframe (M5, M15, H1, H4, D1) generates its own trend, momentum, and strength score. - Scores are weighted according to user-defined importance and then aggregated into a single probability. - Proximity to recent support and resistance levels can adjust the final score, accounting for nearby barriers. - The final probability is displayed as: - Histogram (subwindow): Green bars for bullish probability >50%, red bars for bearish <50%. - On-chart labels: Showing exact buy/sell percentages on the last bar for quick reference. Inputs - EMA length (default 200), MACD settings, ADX period. - Weights for each timeframe and component (trend, momentum, strength). - Optional boost for the chart’s current timeframe. - Smoothing length for probability values. - Lookback period for support/resistance adjustment. How to use it - A green histogram above zero indicates bullish probability >50%. - A red histogram below zero indicates bearish probability >50%. - Neutral readings near 50% show low confluence and may be best avoided. - Users can adjust weights to emphasize higher or lower timeframes, depending on their trading style. Notes - This script does not guarantee profitable trades. - Best used together with price action, volume, or additional confirmation tools. - Signals are calculated only on closed bars to avoid repainting. - For testing and learning purposes — not financial advice.
Pine Script® 인디케이터
DenizTheTrader의
NN Crypto Scalping ULTIMATE v6 - MTF mapercivNeural Network Crypto Trading System v6.1 Complete Technical Documentation Author : Neural Network Ensemble Trading System Version : 6.1 - MTF Corrected & Bias Fixed Date : January 2025 Platform : TradingView PineScript v6 Executive Summary The Neural Network Crypto Trading System v6.1 is an advanced algorithmic trading system that combines three specialized neural networks into an intelligent ensemble to generate cryptocurrency trading signals. The system integrates multi-timeframe analysis, crypto-specific optimizations, dynamic risk management, and continuous learning to maximize performance in highly volatile markets. Key Features: Ensemble of 3 specialized Neural Networks (Primary, Momentum, Volatility) Multi-Timeframe Analysis with 5 timeframes (5m, 15m, 1h, 4h, 1D) 22 Advanced Features for each model Anti-repainting guaranteed with confirmed data 8 Market Regime automatic detections 6 Signal Levels (Strong/Moderate/Weak Buy/Sell) Professional dashboard with 15+ real-time metrics Intelligent alert system with webhook integration
Pine Script® 인디케이터
maperciv의
Crypto OI AgregatedCrypto OI Aggregated — Open Interest Aggregator for Crypto Exchanges General Description The indicator is designed for comprehensive analysis of Open Interest (OI) across major cryptocurrency exchanges. It consolidates data from multiple platforms, visualizes it as candlestick charts or deltas, and builds tables with breakdowns by exchange and contract type. This allows traders to quickly understand where market interest is concentrated and how the market structure is shifting. Unlike standard tools that only show data from a single exchange, this indicator provides a full market overview and makes it easy to compare dynamics across different platforms. ⸻ Key Features • Aggregation of OI data from exchanges: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit (feel free to leave a comment if you’d like me to add other exchanges that provide open interest data) • Support for contract types: USDT.P, USD.P, USDC.P, USD.PM • Automatic normalization of various OI data formats from different providers • Display modes: • OI candlestick chart (total aggregated OI) • OI Delta (change in OI per bar) • Full table with detailed data by exchange and contract type • Short summary table with totals in USD and base assets • Support for USD or COIN denomination • Convenient formatting for large numbers • Customizable colors ⸻ How to Use the Indicator 1. Select Exchanges In the settings, enable or disable specific exchanges. It is recommended to activate only the ones you need for analysis — this will make the indicator faster. 2. Choose Data Type • OI — aggregated open interest from selected exchanges. • OI delta — delta (change in OI compared to the previous bar). 3. Denomination • USD — values are converted into USD equivalents. • COIN — values are shown in the base asset (BTC, ETH, etc.). 4. Reading the Chart • OI candlesticks show the overall OI dynamics. • Delta histogram highlights how much OI has grown or decreased per bar. • Colors are fully customizable. 5. Tables • Enabled via the Show table option. • Full Table → Rows = exchanges, Columns = contract types. Cells contain OI values in either USD or the base asset, depending on settings. Quickly shows where the main interest is concentrated. • Short Table → Displays only the total OI values in USD and the base asset. ⸻ Important Notes • For better readability of large values, two custom formatting functions were implemented. They work similarly to format.volume, but with improved digit grouping and adjustable decimal precision. In the tables, the top row is formatted using format.volume, while the bottom row uses the improved formatting functions for clearer representation. str(d, n, s) => str.substring(d, 0, str.length(d) - n) + '.' + str.substring(d, str.length(d) - n, str.length(d) - (n - 2)) + s format(_r) => d = str.tostring(math.round(_r)) str.length(d) > 9 ? str(d, 9, " B") : str.length(d) > 6 ? str(d, 6, " M") : str.length(d) > 3 ? str(d, 3, " K") : d ⸻ Conclusion: Crypto OI Aggregated is a convenient and powerful tool for cryptocurrency derivatives traders. It enables tracking of OI dynamics across multiple exchanges simultaneously, detecting imbalances between contracts, and identifying signals that are not visible when analyzing a single exchange.
Pine Script® 인디케이터
NoveltyTrade의
Pattern ScannerUltimate Pattern Scanner — multi-timeframe candlestick discovery tool (educational use only). Purpose: This script scans user-selected timeframes for classical candlestick patterns (for example: engulfing, morning/evening stars, hammers, dojis, tasuki gaps, three soldiers/crows, tweezers, marubozu, and others) and reports pattern name, detection price, directional signal (Bull / Bear / Neutral), and a simple volume participation metric. It is intended as an idea-generation and training tool to help traders learn pattern mechanics, not as an automated trading system. Main modules and rationale: 1) Pattern engine — applies classical candle structure rules to detect formations; 2) SMA trend filter (configurable length) — provides a directional bias to favor trade-with-trend setups; 3) Volume heuristic — approximates participation by separating candles into buy-like and sell-like volume and comparing total volume to a moving average; 4) Multi-timeframe aggregator — collects and presents pattern results from multiple timeframes; 5) Alerts — optional alerts list detected patterns and TFs. Combining these modules is intentional: patterns provide structure, SMA provides context, and volume supplies participation confirmation. Together they improve the educational value and practical relevance of each detected pattern. How to use: Choose timeframes and SMA length that match your trading horizon. Use the scanner to locate pattern candidates, then confirm with higher-timeframe agreement and volume ratio before considering trade entry. Use structural stops (recent swing highs/lows or ATR-based stops) and define risk:reward rules. For learning, replay alerted bars and record outcomes over fixed horizons to build empirical statistics. Limitations: Volume classification (close>open) is a heuristic and not a true bid/ask tape. SMA is a lagging trend proxy. Multi-timeframe agreement reduces but does not eliminate false signals, especially around news or in low-liquidity instruments. Use demo accounts and backtesting before live trading. Inputs you can adjust: timeframe list, SMA length, volume MA length, which patterns to enable/disable, display options. Compliance notes: This description explains why modules are combined and what the script does without exposing source code logic; it is non-promotional and contains no contact links. Remove any trademark symbols unless registration details are provided. Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Backtest thoroughly and use proper risk management.
Pine Script® 인디케이터
aiTrendview-Charting-System의
3