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Trend Analizi

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® göstergesi
BackQuant tarafından
2
Bank Strategy v1 Pro # Bank Strategy v1 Pro - Advanced Institutional Trading System ## Overview Bank Strategy v1 Pro is a sophisticated institutional-grade trading indicator designed for professional traders who understand advanced market microstructure concepts. This system implements the precise methodologies used by institutional traders to identify high-probability reversal opportunities through liquidity manipulation patterns. ## Core Methodology ### 🏦 **Institutional Trading Framework** This strategy is built upon the fundamental principle that institutional players (banks, hedge funds, market makers) create specific patterns when accumulating or distributing positions. The indicator identifies these patterns through: - **Liquidity Manipulation Sequences** - Detection of deliberate stop-loss hunting - **False Move (FU) Patterns** - Identification of engineered price movements - **Order Block Analysis** - Recognition of institutional accumulation/distribution zones - **Imbalance Trading** - Exploitation of price inefficiencies - **Market Structure Context** - Trend-based signal filtering ### 📊 **Advanced Signal Components** #### 1. **Liquidity Zone Identification** - Automated detection of swing highs/lows where retail stops accumulate - Dynamic liquidity level tracking with 30-bar extension - Real-time monitoring of liquidity sweeps and hunts #### 2. **False Move (FU) Pattern Recognition** - **Bullish FU**: High manipulation → Close below previous low (bearish trap) - **Bearish FU**: Low manipulation → Close above previous high (bullish trap) - Institutional reversal confirmation after liquidity grab #### 3. **Order Block Detection** - Bullish Engulfing: Strong institutional buying after bearish candle - Bearish Engulfing: Strong institutional selling after bullish candle - 20-bar forward projection for order block validity #### 4. **Price Imbalance Analysis** - Bullish Imbalance: Gap up indicating buying pressure - Bearish Imbalance: Gap down indicating selling pressure - 15-bar tracking with automatic labeling ## Signal Generation Logic ### 🎯 **Entry Criteria** **Buy Signal Requirements:** - Bearish FU pattern detected (liquidity grab below previous low) - Price above 200 SMA (bullish market context) - Liquidity lows available for targeting - Signal confirmation enabled **Sell Signal Requirements:** - Bullish FU pattern detected (liquidity grab above previous high) - Price below 200 SMA (bearish market context) - Liquidity highs available for targeting - Signal confirmation enabled ### 📈 **Advanced Entry Management** - **Entry Level**: 50% retracement of manipulation candle body - **Stop Loss**: 20% extension below/above manipulation range - **Take Profit**: Configurable risk-reward ratio (1:1 to 1:5) - **Timeout**: 15-bar automatic signal expiry ## Professional Features ### 🔧 **Customizable Parameters** - **Signal Control**: Independent buy/sell signal toggles - **Visual Elements**: Modular display of order blocks, imbalances, liquidity zones - **Risk Management**: Adjustable risk-reward ratios up to 1:5 - **Market Structure**: Configurable swing length (3-20 periods) - **MA Filter**: Optional 200 SMA trend context ### 📊 **Real-Time Status Monitoring** Professional status table displaying: - Current market trend direction - Liquidity availability status - Active entry waiting status - Risk-reward configuration - System health indicators ### 🚨 **Professional Alert System** - **Signal Alerts**: Instant notification of buy/sell opportunities - **Entry Alerts**: Confirmation when entry levels are reached - **Custom Messages**: Detailed alert descriptions for trade management ## Advanced Visual Analysis ### 🎨 **Color-Coded Elements** - **Green Boxes**: Bullish order blocks (institutional buying zones) - **Red Boxes**: Bearish order blocks (institutional selling zones) - **Blue/Orange Boxes**: Price imbalances requiring fill - **Purple Boxes**: FU patterns with directional labels - **Dotted Lines**: Key liquidity levels with labels - **Yellow Lines**: Pending entry levels ### 📍 **Professional Labeling** - Clear identification of all pattern types - Directional bias indicators - Entry confirmation markers - Liquidity level annotations ## Risk Management Framework ### ⚠️ **Professional Trading Guidelines** - **Timeframe Recommendation**: 4H+ for institutional signal reliability - **Position Sizing**: Risk no more than 1-2% per signal - **Confirmation**: Wait for entry level hits before position entry - **Context**: Always consider overall market structure and sentiment ### 🛡️ **Built-in Protections** - Automatic signal timeout prevents stale entries - Trend context filtering reduces counter-trend risks - Liquidity requirement ensures sufficient market depth - Risk-reward enforcement maintains positive expectancy ## Performance Optimization ### ⚡ **Technical Specifications** - **Pine Script v5**: Latest version compatibility - **Resource Limits**: Optimized for 500 bars, 200 lines, 100 boxes, 200 labels - **Processing**: Efficient array management for liquidity tracking - **Memory**: Automatic cleanup of expired signals and objects ### 🎯 **Signal Quality** - High-probability setups through multi-factor confirmation - Institutional pattern recognition reduces retail noise - Trend context filtering improves win rate - Professional entry timing reduces slippage ## Educational Framework ### 📚 **Institutional Concepts** This indicator teaches professional trading concepts: - Market microstructure understanding - Institutional order flow analysis - Liquidity-based trading strategies - Professional risk management techniques ### 🎓 **Skill Development** - Pattern recognition training - Market structure analysis - Trade timing optimization - Risk management discipline ## Disclaimer This indicator is designed for professional traders with experience in institutional trading concepts. It requires understanding of market microstructure, liquidity dynamics, and professional risk management. Past performance does not guarantee future results. Always implement proper risk management and consider multiple analysis factors before making trading decisions. ## Compatibility - **Markets**: Forex, Indices, Cryptocurrencies, Commodities - **Timeframes**: Optimized for 1H and above (4H+ recommended) - **Platform**: TradingView Pine Script v5 - **Features**: Full alert integration, customizable display options
Pine Script® göstergesi
Aliasqar414 tarafından
VIDYA with trend centered SDs with Chandelier Exit By KidevThis multi-tool overlay combines adaptive averaging, volatility envelopes, and structural swing detection into a single, configurable indicator. Features • Selectable MA75 — choose SMA / EMA / WMA / VWMA / HMA as the 75-length baseline. • MA Trend Mode — optional up/side/down regime coloring driven by MA slope (configurable colors). • VIDYA (Variable Index Dynamic Average) — adaptive moving average with cross (C>V / CV / C
Pine Script® göstergesi
kidevswamynathan tarafından
2
Confluence Engine Confluence Engine is a practical, non-repainting decision aid that scores market conditions from −100…+100 by combining six proven modules: Trend, Momentum, Volatility, Volume, Structure, and an HTF confirmation. It’s designed for crypto, forex, indices, and stocks, and it fires entries only on confirmed bar closes. What’s inside Trend: EMA 20/50/200 alignment plus a Supertrend/KAMA toggle (you choose the baseline). Momentum: RSI + MACD with confirmed-pivot divergence detection. Volatility: ATR% and Bollinger Band width vs its average to favor expansion over chop. Volume: OBV-style cumulative flow slope + volume surge vs SMA×multiplier. Market Structure: Confirmed pivots, BOS (break of structure) and CHOCH (change of character). HTF Filter: Closed higher-timeframe context via request.security(..., barmerge.gaps_on, barmerge.lookahead_off). Why it does not repaint Signals are computed and plotted on closed bars only. Pivots/divergences use confirmed pivot points (no forward look). HTF series are fetched with lookahead_off and use the last closed HTF bar in realtime. No future bar references are used for entries or alerts. How to use (3 steps) Pick a timeframe pair: use a 4–6× HTF multiplier (5m→30m, 15m→1h, 1h→4h, 4h→1D, 1D→1W). Trade with the HTF: take longs only when the HTF filter is bullish; shorts only when bearish. Prefer expansion: act when BB width > its average and ATR% is elevated; skip most signals in compression. Suggested presets (start here) Crypto (BTC/ETH): 15m→1h, 1h→4h. stLen=10, stMult=3.0, bbLen=20, surgeMul=1.8–2.2, thresholds +40 / −40 (intraday can try +35 / −35). Forex majors: 15m→1h, 1h→4h. stLen=10–14, stMult=2.5–3.0, surgeMul=1.5–1.8, thresholds +35 / −35 (swing: +45 / −45). US equities (liquid): 5m→30m/1h, 15m→1h/2h. stMult=3.0–3.5, surgeMul=1.6–2.0, thresholds +45 / −45 to reduce chop. Indices (ES/NQ): 5m→30m, 15m→1h. Defaults are fine; start at +40 / −40. Gold/Oil: 15m→1h, 1h→4h. Thresholds +35 / −35, surgeMul=1.6–1.9. Inputs (plain English) Use Supertrend (off = KAMA): choose the trend baseline. EMA Fast/Mid/Slow: 20/50/200 by default for classic stack. RSI/MACD + divergence pivots: momentum and exhaustion context. ATR Length & BB Length: volatility regime detection. Volume SMA & Surge Multiplier: defines “meaningful” volume spikes. Pivot left/right & “Confirm BOS/CHOCH on Close”: structure strictness. Enable HTF & Higher Timeframe: confirms the lower timeframe direction. Thresholds (+long / −short): when the score crosses these, you get signals. Signals & alerts (IDs preserved) Entry shapes plot at bar close when the score crosses thresholds. Alerts you can enable: CONFLUENCE LONG — long entry signal CONFLUENCE SHORT — short entry signal BULLISH BIAS — score turned positive BEARISH BIAS — score turned negative Best practices Focus on signals with HTF agreement and volatility expansion; require volume participation (surge or rising OBV slope) for higher quality. Raise thresholds (+45/−45 or +50/−50) to reduce whipsaws in choppy sessions. Lower thresholds (+35/−35) only if you also require volatility/volume filters. Performance & scope Works across crypto/FX/equities/indices; no broker data or special feeds required. No repainting by design; signals/alerts are computed on closed bars. As with any tool, results vary by regime; always combine with risk management. Disclosure This script is for educational purposes only and is not financial advice. Trading involves risk. Test on historical data and paper trade before using live.
Pine Script® göstergesi
Finntech1 tarafından
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® göstergesi
AlphaNatt tarafından
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® göstergesi
BackQuant tarafından
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® göstergesi
OakleyJM tarafından
1
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® stratejisi
Script_Algo tarafından
Volatility Cone Forecaster Lite [PhenLabs]📊 Volatility Cone Forecaster Version: PineScript™v6 📌Description The Volatility Cone Forecaster (VCF) is an advanced indicator designed to provide traders with a forward-looking perspective on market volatility. Instead of merely measuring past price fluctuations, the VCF analyzes historical volatility data to project a statistical “cone” that outlines a probable range for future price movements. Its core purpose is to contextualize the current market environment, helping traders to anticipate potential shifts from low to high volatility periods (and vice versa). By identifying whether volatility is expanding or contracting relative to historical norms, it solves the critical problem of preparing for significant market moves before they happen, offering a clear statistical edge in strategy development. This indicator moves beyond lagging measures by employing percentile analysis to rank the current volatility state. This allows traders to understand not just what volatility is, but how significant it is compared to the recent past. The VCF is built for discretionary traders, system developers, and options strategists who need a sophisticated understanding of market dynamics to manage risk and identify high-probability opportunities. 🚀Points of Innovation Forward-Looking Volatility Projection: Unlike standard indicators that only show historical data, the VCF projects a statistical cone of future volatility. Percentile-Based Regime Analysis: Ranks current volatility against historical data (e.g., 90th, 75th percentiles) to provide objective context. Automated Regime Detection: Automatically identifies and labels the market as being in a ‘High’, ‘Low’, or ‘Normal’ volatility regime. Expansion & Contraction Signals: Clearly indicates whether volatility is currently increasing or decreasing, signaling shifts in market energy. Integrated ATR Comparison: Plots an ATR-equivalent volatility measure to offer a familiar point of reference against the statistical model. Dynamic Visual Modeling: The cone visualization directly on the price chart provides an intuitive guide for future expected price ranges. 🔧Core Components Realized Volatility Engine: Calculates historical volatility using log returns over multiple user-defined lookback periods (short, medium, long) for a comprehensive view. Percentile Analysis Module: A custom function calculates the 10th, 25th, 50th, 75th, and 90th percentiles of volatility over a long-term lookback (e.g., 252 days). Forward Projection Calculator: Uses the calculated volatility percentiles to mathematically derive and draw the upper and lower bounds of the future volatility cone. Volatility Regime Classifier: A logic-based system that compares current volatility to the historical percentile bands to classify the market state. 🔥Key Features Customizable Lookback Periods: Adjust short, medium, and long-term lookbacks to fine-tune the indicator’s sensitivity to different market cycles. Configurable Forward Projection: Set the number of days for the forward cone projection to align with your specific trading horizon. Interactive Display Options: Toggle visibility for percentile labels, ATR levels, and regime coloring to customize the chart display. Data-Rich Information Table: A clean, on-screen table displays all key metrics, including current volatility, percentile rank, regime, and trend. Built-in Alert Conditions: Set alerts for critical events like volatility crossing the 90th percentile, dropping below the 10th, or switching between expansion and contraction. 🎨Visualization Volatility Cone: Shaded bands projected onto the future price axis, representing the probable price range at different statistical confidence levels (e.g., 75th-90th percentile). Color-Coded Volatility Line: The primary volatility plot dynamically changes color (e.g., red for high, green for low) to reflect the current volatility regime, providing instant context. Historical Percentile Bands: Horizontal lines plotted across the indicator pane mark the key percentile levels, showing how current volatility compares to the past. On-Chart Labels: Clear labels automatically display the current volatility reading, its percentile rank, the detected regime, and trend (Expanding/Contracting). 📖Usage Guidelines Setting Categories Short-term Lookback: Default: 10, Range: 5-50. Controls the most sensitive volatility calculation. Medium-term Lookback: Default: 21, Range: 10-100. The primary input for the current volatility reading. Long-term Lookback: Default: 63, Range: 30-252. Provides a baseline for long-term market character. Percentile Lookback Period: Default: 252, Range: 100-1000. Defines the period for historical ranking; 252 represents one trading year. Forward Projection Days: Default: 21, Range: 5-63. Determines how many bars into the future the cone is projected. ✅Best Use Cases Breakout Trading: Identify periods of deep consolidation when volatility falls to low percentile ranks (e.g., below 25th) and begins to expand, signaling a potential breakout. Mean Reversion Strategies: Target trades when volatility reaches extreme high percentile ranks (e.g., above 90th), as these periods are often unsustainable and lead to contraction. Options Strategy: Use the cone’s projected upper and lower bounds to help select strike prices for strategies like iron condors or straddles. Risk Management: Widen stop-losses and reduce position sizes when the indicator signals a transition into a ‘High’ volatility regime. ⚠️Limitations Probabilistic, Not Predictive: The cone represents a statistical probability, not a guarantee of future price action. Extreme, unpredictable news events can drive prices outside the cone. Lagging by Nature: All calculations are based on historical price data, meaning the indicator will always react to, not pre-empt, market changes. Non-Directional: The indicator forecasts the *magnitude* of future moves, not the *direction*. It should be paired with a directional analysis tool. 💡What Makes This Unique Forward Projection: Its primary distinction is projecting a data-driven, statistical forecast of future volatility, which standard oscillators do not do. Contextual Analysis: It doesn’t just provide a number; it tells you what that number means through percentile ranking and automated regime classification. 🔬How It Works 1. Data Calculation: The indicator first calculates the logarithmic returns of the asset’s price. It then computes the annualized standard deviation of these returns over short, medium, and long-term lookback periods to generate realized volatility readings. 2. Percentile Ranking: Using a 252-day lookback, it analyzes the history of the medium-term volatility and determines the values that correspond to the 10th, 25th, 50th, 75th, and 90th percentiles. This builds a statistical map of the asset’s volatility behavior. 3. Cone Projection: Finally, it takes these historical percentile values and projects them forward in time, calculating the potential upper and lower price bounds based on what would happen if volatility were to run at those levels over the next 21 days. 💡Note: The Volatility Cone Forecaster is most effective on daily and weekly charts where statistical volatility models are more reliable. For lower timeframes, consider shortening the lookback periods. Always use this indicator as part of a comprehensive trading plan that includes other forms of analysis.
Pine Script® göstergesi
PhenLabs tarafından
TEWMA Supertrend - [JTCAPITAL]TEWMA Supertrend is a modified way to use Triple Exponential Weighted Moving Average inside Supertrend logic for Trend-Following The indicator works by calculating in the following steps: 1. Calculate the Triple Exponential Moving Average with Weighted Moving Average as input. 2. Calculate the ATR over the Supertrend Length 3. Use the Triple Exponential Weighted Moving Average, and add the multiplier times the ATR for the upper limit, and subtract the multiplier times the ATR for the lower limit. 4. Define Buy and Sell conditions based on the price closing above or below the upper and lower limits. --Buy and sell conditions-- - The buy and sell conditions are defined by the price going above/below the upper and lower limits, calculated by (TEWMA +/- multi * ATR). - When this goes on the opposite direction of the current trend, the trend changes. If this goes in the same direction of the current trend, the line follows the price by moving up. - When price gets closer to the limits the limits do not change. The upper limit only moves when the upper decreases, and the lower limit only moves when the lower increases. - The ATR gets subtracted from the lows or added onto the highs to eliminate false signals in choppy markets, while enforcing fast entries and exits. --Features and Parameters-- - Allows the usage of different sources - Allows the changing of the length of the ATR - Allows the changing of the length of the TEWMA - Allows the changing of the multiplier to increase or decrease ATR usage --Details-- This script is using TEWMA as input for the modified Supertrend. Using a TEWMA and getting a higher multiplier to the ATR is meant to decrease false signals. Which can be a problem when using a normal Supertrend. Using the TEWMA also ensures fast entries and exits from fast market moves after a calm period. Ensuring you don't stay left behind. Be aware that lowering the multiplier for the ATR will allow for faster entries and exits but also allow for more false signals. It is recommended to change the parameters to fit your liking and to adjust to the timeframe you are working on. Enjoy!
Pine Script® göstergesi
JTCapitalNL tarafından
1
TCI Key Institutional Levels v2.0This script is a modified version of the Smart Money Concepts (SMC) framework originally published by LuxAlgo here: Smart Money Concepts – LuxAlgo . All credit and ownership of the original code goes to LuxAlgo. Original indicator Credits: The purpose of this publication is not to copy-paste the LuxAlgo indicator, but to present a modified version adapted in line with the concepts taught by Trading Cafe India (TCI). These modifications include adjustments and refinements to better reflect the methodology followed by TCI, while still acknowledging the foundation laid by LuxAlgo. ⚠️ Important Notes: This script is not an official LuxAlgo product. This script is not an official TCI product. This pretty much aligns with the TCI theory. It is an independent, educational adaptation created for users who wish to see SMC concepts in the context of TCI-style modifications. The modifications are original contributions and the script has been republished with the intention of providing additional learning value to the TradingView community. By publishing this indicator, I fully respect and acknowledge the original author (LuxAlgo), while making clear that the changes applied are my own interpretation of SMC principles influenced by TCI’s teachings. 🔧 Key Functionalities & Modifications Market Structure Labels The standard Break of Structure (BOS) is now presented as Breaker, aligning with TCI’s interpretation. The standard Change of Character (CHoCH) is now presented as Trap, reflecting how false moves and liquidity traps are often observed in Indian indices like Nifty & Bank Nifty. Order Block & Liquidity Concepts Retains core order block, supply-demand, and liquidity zone logic from the SMC framework. Visuals and labels have been adjusted for easier interpretation by intraday traders in Indian markets. Custom Adaptation for Indian Audience Naming conventions and alerts have been optimized so beginners and experienced traders in India can relate to the terminology taught by TCI. Chart annotations have been simplified to reduce clutter, making it more practical for real-time option trading and scalping strategies.
Pine Script® göstergesi
The_Stock_Yogi tarafından
Supertrend Channel Histogram OscillatorThis histogram is based on the script "Supertrend Channels " The idea of the indicator is to visually represent the interaction of price with several different supertrend channels of various lengths in an oscillator in order to make it much more clear to the trader how the longer trends are interacting with shorter trends of the price movement of an asset. I got this idea from the "Kurutoga Cloud" and "Kurutoga Histogram" by D7R which is based on the centerlines of 3 Donchian Channels, however after I started using the Supertrend Channel by LuxAlgo I found that it was a more reliable price range channel than a standard Donchian Channel and I made this indicator to accompany it. This indicator plots a positive value above 0 when the price is above the centerline of the supertrend channel and a negative value below 0 when the price is below the centerline. The first supertrend's length and multiple can be adjusted in the settings. The given supertrend input is then doubled and quadrupled in both length and multiplication so that a supertrend histogram with the values of 3, 3 will be accompanied by 2 additional supertrend histograms with the values of 6, 6 and 12, 12. The larger price trend histograms are clearly visible behind the short term supertrend channel's histogram, giving traders a balanced view of short and long term trends interacting. The less visible columns of the larger trend remain above or below the 0 line behind the more visible short term channel trend, helping to spot pullbacks within a larger trend. Additionally, when the 3 separate histograms are all positive or all negative but the histogram columns are separating from each other this can indicate a potential trend exhaustion leading to reversal or pullback about to happen. The overbought and oversold lines at 50 and -50 are representative primarily of the short term trend with above 50 or below -50 indicating that the price is pushing the boundary and potentially beginning a new short term supertrend in the opposite direction. If values do not noticably exceed these levels, then the current short term trend movement can be viewed as a pullback within a larger trend, with continuation potentially to follow. I have had troubles converting the original code to v6 so this will be published here in v5 of pinescript to be used in conjunction with the original. I was intending to create a companion indicator for this oscillator that represents 3 supertrends with corresponding 2x and 4x calculations based on LuxAlgo's script, but I can't seem to get it to work correctly in v5. For best visualization of the trends 3 LuxAlgo Supertrend channels with 2x and 4x values should be used in conjunction with each other to fully visualize the histogram. Used in conjunction with other indicators this can be a very effective strategy to capture larger trend moves and pullbacks within trends, as well as warn of potential price trend exhaustion.
Pine Script® göstergesi
nathanieljens tarafından
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® göstergesi
gokul4trading tarafından
1
TrendSpark⚡ Trend Spark 📖 Description Trend Spark is a multi-tool trading indicator that combines the WaveTrend Oscillator, EMA Ribbon, and custom signal markers to help traders identify momentum shifts, reversals, and high-probability entry/exit zones. Unlike traditional templates, Trend Spark uses unique visual cues — triangles, diamonds, and squares — to highlight important conditions in price action, making signals more intuitive and easier to act on. Whether you’re scalping, swing trading, or analyzing long-term trends, Trend Spark adapts to your strategy. ⚙️ Features WaveTrend Oscillator → Detects overbought/oversold conditions and momentum reversals. EMA Ribbon (8 EMAs) → Reveals bullish and bearish market phases. RSI → Confirms strength or weakness behind moves. Custom Signal Shapes 🔼 Green Triangle Up → Bullish EMA crossover. 🔽 Red Triangle Down → Bearish EMA crossover. 🔶 Orange Diamond → WaveTrend crossover (potential reversal). 🟨 Yellow Square → Bullish candle confirmation. 📌 How to Use Identify Trend EMA2 above EMA8 (blue ribbon) → Bullish trend. EMA8 above EMA2 (red ribbon) → Bearish trend. Entry Signals Look for 🔼 green triangles during bullish trends. Look for 🔽 red triangles during bearish trends. Use 🔶 orange diamonds as early warning signs of reversals. Confirm Strength A 🟨 yellow square below a bullish candle signals potential continuation. Cross-check with RSI for stronger confirmation. Risk Management Always confirm with multiple timeframes. Place stop-losses below/above recent swing levels. 🔔 Alerts Trend Spark supports alerts for: ✅ Long EMA crossover (triangle up) ✅ Short EMA crossover (triangle down) ✅ WaveTrend crossover (diamond) Stay ahead of market moves without constantly watching the charts.
Pine Script® göstergesi
Cryptobingbong tarafından
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® göstergesi
DenizTheTrader tarafından
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® göstergesi
NizamettinGOZEL tarafından
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® göstergesi
kidevswamynathan tarafından
APC – Anti-Analysis-Paralysis Kompass APC – Anti-Analysis-Paralysis Compass (Pine v5). Research/education indicator that compresses trend from 5 timeframes into one compass with Direction, Score, and Coherence (TF agreement). Non-repainting with a high-contrast breakdown table and in-chart help. No financial advice. What it is APC is a research/education tool that condenses trend information from five timeframes into a single compass. It shows Direction (↑/↓/→), a weighted Score, and Coherence (how strongly timeframes agree). The script is non-repainting (security(..., lookahead=off)) and includes a readable breakdown panel and example alerts. How it works • For each timeframe APC fits a linear regression to price, measures the slope change over k bars, optionally normalizes by ATR%, then maps it to +1 / 0 / −1 using a Deadzone (small slopes → neutral). • A (weighted) sum of the five signs forms the Score. • Coherence = |Score| / maxScore (0–100%), i.e., degree of TF alignment. Quick start (suggested defaults) • Timeframes: 15m · 1h · 4h · 1D · 1W • Weights: 1, 1, 1, 1.5, 2 • LinReg length: 100 • Slope Δ window: 10 • ATR normalization: ON • Deadzone: 0.03–0.05 • Coherence lock (for example alerts): 60% Example research filters (non-advisory) Many users test: Bullish bias when Score ≥ +3 and Coherence ≥ 60%; bearish bias when Score ≤ −3 and Coherence ≥ 60%. These are illustrative defaults only—configure and test your own thresholds. Optional: pair with Kagi Use APC for bias/conviction and Kagi turns for timing. Typical Kagi (swing): base 15m–1h, reversal ATR(14) × 1.5–2.5 or 1–3%. Notes Raise Deadzone in choppy markets; lower it for earlier flips. On very illiquid or young symbols, lengthen lenLR. Disclaimer APC is a research & educational indicator. It does not provide financial advice or recommendations. Use at your own risk. License: MIT.
Pine Script® göstergesi
SamBou76 tarafından
VWAP CloudThe VWAP Cloud is a dynamic intraday/rolling VWAP indicator with customizable standard deviation bands. It helps traders identify value zones, overbought/oversold areas, and trend bias based on whether price is trading above or below the VWAP. VWAP (Volume-Weighted Average Price) acts as a fair-value benchmark. Inner Cloud (±1 stdev by default) highlights short-term deviations from VWAP. Outer Cloud (±2 stdev by default) shows extreme zones where reversals or continuation moves are more likely. Cloud colors adjust dynamically: 🟩 Green = VWAP is rising (bullish bias) 🟥 Red = VWAP is falling (bearish bias) 🩶 Gray Outer Cloud = volatility envelope This makes the VWAP Cloud useful for scalpers, day traders, and swing traders alike. ⚙️ Inputs & Settings VWAP Source → Price input for VWAP calculation (default: hlc3). Reset each session → ON = Session VWAP (resets daily), OFF = Rolling VWAP. Stdev Lookback → Window length for standard deviation calculation. Inner Band Multiplier → Width of the first (inner) band. Outer Band Multiplier → Width of the second (outer) band. Show VWAP Midline → Toggle the VWAP line on/off. Cloud Colors → Customize bullish, bearish, and neutral shading. 📊 How to Use Add VWAP Cloud to your chart. Choose between Session VWAP (intraday resets) or Rolling VWAP (continuous). Use Inner Cloud as a short-term fair value zone: Price inside = balanced trading. Breakouts above/below = possible momentum continuation. Watch Outer Cloud for extremes: Price reaching outer bands often signals exhaustion or potential reversals. Trend bias: Price above VWAP = bullish bias. Price below VWAP = bearish bias. ⚠️ Disclaimer: This tool is for educational purposes. Always combine it with proper risk management and other confluence factors.
Pine Script® göstergesi
Cryptobingbong tarafından