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Chaikin Momentum Scalper🎯 Overview The Chaikin Momentum Scalper is a powerful trading strategy designed to identify momentum shifts in the market and ride the trend for maximum profits. This strategy is ideal for trading the USD/JPY currency pair on a 15-minute chart, making it perfect for high-frequency trading (HFT). Whether you’re starting with a small account of $1,000 or managing a larger portfolio, this strategy can scale to suit your needs. ________________________________________ 🔑 How the Strategy Works Here’s how the Chaikin Momentum Scalper identifies trade opportunities: 1️⃣ Momentum Detection The core of this strategy is the Chaikin Oscillator, a tool that measures the flow of money into or out of a market. It helps us understand whether buyers (bulls) or sellers (bears) are in control. • When the indicator crosses above zero, it signals that buying momentum is picking up – a buying opportunity. • When the indicator crosses below zero, it signals that selling momentum is increasing – a selling opportunity. 2️⃣ Trend Confirmation We don’t just jump into trades based on momentum alone. We also use a 200-period simple moving average (SMA) to confirm the overall trend. • If the price is above the SMA, it confirms an uptrend, so we look for buy trades. • If the price is below the SMA, it confirms a downtrend, so we look for sell trades. This way, we align our trades with the broader market direction for higher success rates. 3️⃣ Volatility & Risk Management We use a tool called the Average True Range (ATR) to measure market volatility. This helps us: • Set a stop-loss (where we’ll exit the trade if the market moves against us) at a safe distance from our entry point. • Set a take-profit (where we’ll lock in profits) at a target that’s larger than the stop-loss, ensuring a good reward-to-risk ratio. This approach adapts to the market’s behavior, tightening stops in calmer conditions and widening them when volatility increases. ________________________________________ 📈 Why This Strategy Works ✅ It combines momentum and trend-following principles, increasing the chances of trading in the right direction. ✅ It dynamically adjusts risk levels based on market volatility, keeping losses small and profits big. ✅ It’s scalable – perfect for both small accounts (like $1,000) and larger, corporate-sized portfolios. ✅ It has been deep-backtested on USD/JPY 15-minute charts, proving its consistency across different market conditions. ________________________________________ 📝 Important Notes 📌 This strategy is best used for USD/JPY on a 15-minute chart, making it great for high-frequency trading while you continue to build and refine your trading system. 📌 It’s designed to work on both small ($1,000+) and large accounts, so it can grow with you as your capital increases. 📌 While it has passed deep backtesting on this pair and timeframe, remember that no strategy is perfect. It’s crucial to test it yourself, start with a demo account, and apply proper risk management before trading real money. 🌟 Final Thoughts The Chaikin Momentum Scalper is a solid, adaptable trading approach combining momentum, trend direction, and volatility awareness. If you’re looking for a strategy to kick-start your trading journey—or to add to your existing system—it offers a strong foundation.
Pine Script® stratejisi
SupertradeOfficial tarafından
Grid Tendence V1The “Grid Tendence V1” strategy is based on the classic Grid strategy, only in this case the entries and exits are made in favor of the trend, which allows to take advantage of large movements to maximize profits, since it is also possible to enter and exit with the balance with a controlled risk, because precisely the distance between each Grid works as a natural and adaptable stop loss and take profit. This fact helps to avoid overlapping entries and exits that would result from using stop loss and take profit as limit orders. In this version of the script the entries and exits are always at market, and based on the percentage change of the price, not on the profit or loss of the current position. The user will notice that the strategy setup is based on a controlled risk, risking 5% on each trade, a fairly standard commission and a modest initial capital, all this in order to protect the user of the strategy from unexpected or unrealistic results. However, it is always recommended to optimize the parameters so that the strategy is effective for each asset and for each time frame.
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morzns tarafından
AMD Liquidity Sweep with AlertsAMD Liquidity Sweep with Alerts Identify key liquidity levels from the Asian trading session with visual markers and alerts. 📌 Key Features: Asia Session Detection Customizable start/end hours (0-23) to match your trading timezone Automatically calculates session high/low Smart Swing Level Identification Finds the closest significant swing high ≥ Asia high Finds the closest significant swing low ≤ Asia low Adjustable pivot sensitivity (# of left/right bars) Professional Visuals Dashed reference lines extending into the future Blue-highlighted key levels Clean label formatting with precise price levels Trading Alerts Price-cross alerts for liquidity breaks Visual markers (triangles) when levels are breached Separate alerts for buy-side/sell-side liquidity Customization Options Toggle intermediate swing highlights Adjust label sizes 💡 Trading Applications: Institutional Levels: Identify zones where Asian session liquidity pools exist Breakout Trading: Get alerted when price breaches Asian session ranges S/R Flip Zones: Watch how price reacts at these key reference levels London/NY Open: Use Asian levels for early European session trades 🔧 How to Use: Set your preferred Asia session hours Adjust pivot sensitivity (default 1 bar works for most timeframes) Enable alerts for breakouts if desired Watch for reactions at the plotted levels
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OOCONNOR454 tarafından
4
BG Ichimoku Tenkan MTFBG Ichimoku Tenkan MTF: Your Multi-Timeframe Trend Compass Elevate your Ichimoku analysis with the BG Ichimoku Tenkan MTF indicator. This powerful tool provides a comprehensive view of the Tenkan-sen (Conversion Line) across multiple timeframes, helping you identify trends and potential shifts with greater clarity. It's ideal for all markets, including stocks, cryptocurrencies, Forex, and futures. Key Features: Main Tenkan-sen Plot: Visualize the Tenkan-sen for your active chart timeframe with adjustable color. Multi-Timeframe Table: A dynamic table displays the Tenkan-sen's relationship to price (🔼 for above, 🔽 for below) and its current value for up to 7 timeframes. Continuous MTF Lines: Plot the Tenkan-sen from higher timeframes directly on your current chart, providing clear support/resistance levels and trend confluence. Fully Customizable Colors: Personalize the color for each individual timeframe in the table and for its corresponding MTF line, ensuring a clean and intuitive visual experience. You can also adjust the main Tenkan-sen color and the MTF line offset. Gain a deeper understanding of market dynamics by analyzing the Tenkan-sen across different time scales, all in one intuitive indicator. We created this indicator to help you better navigate the markets. Thank you for using it, and we hope it brings you value. Enjoy it in your daily analysis! Bab
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babtrader24 tarafından
1
ka66: Triple Keltner Around SourceThis is an indicator-on-indicator which draws Keltner Bands (ATR Bands) around any selected Basis Source, instead of hardcoding a moving average, etc. This allows you to put bands around any sort of esoteric moving average of your choice, or even just around price data like OHLC, HLC3, and so on. It's an enhancement on my prior Multi ATR Channels script at Written in Pine v6 and allowing custom timeframe selection. For example, the published chart shows the bands place around a Kaufman Adaptive Moving Average (KAMA), plotted in blue dots. You would use it for anything that you would use plain Keltners for: Mean Reversion Breakouts Take Profit and Stop Loss Estimation But with any basis that you deem more suitable for your purposes.
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ka66 tarafından
EWMA & EWVar + EWStd Expansion with MTF_V.5EWMA & EWVar + EWStd Expansion with MTF_V.5 This indicator combines adaptive trend smoothing (EWMA), variance estimation (EWVar) and dynamic volatility “bursts” (EWStd Expansion) with optional higher-timeframe confirmation. It’s designed both for visual chart analysis and for automated alerts on regime changes. Key Features EWMA (Exponential Smoothing): • Computes an exponential moving average with either a custom α or a length-derived α = 2/(N+1). • Option to recalculate only every N bars (reduces CPU load). EWVar & EWStd (Variance & Standard Deviation): • Exponentially weighted variance tracks recent price dispersion. • EWStd (σ) is computed alongside the EWMA. • Z-score (deviation in σ units) shows how far price has diverged from trend. Multi-Timeframe Filter (MTF): • Optionally require the same trend direction on a chosen higher timeframe (e.g. Daily, Weekly, H4). • Real-time lookahead available (may repaint). Gradient Around EWMA: • A multi-layer “glow” zone of ±1σ, broken into up to 10 steps. • Color interpolates between “upper” and “lower” shades for bullish, bearish and neutral regimes. Instantaneous Trendline (ITL): • Ultra-fast trend filter with slope-based coloring. • Highlights micro-trends and short-lived accelerations. Cross-Over Signals (ITL ↔ EWMA): • Up/down triangles plotted when the ITL crosses the main EWMA. EWStd Expansion (Volatility Bursts): • Automatically detects σ expansions (σ growth above a set % threshold). • Price filter: only when price moves beyond EWMA ± (multiplier·σ). • Optional higher-timeframe confirmation. Labels & Alerts: • Text labels and circular markers on bars where a volatility burst occurs. • Built-in alertcondition calls for both bullish and bearish expansions. How to Use Visual Analysis: • The gradient around EWMA shows the width of the volatility channel expanding or contracting. • ITL color changes instantly highlight short-term impulses. • EWMA line color switches (bullish/bearish/neutral) indicate trend state. Spotting Volatility Breakouts: • “EWStd Expansion” labels and circles signal the onset of strong moves when σ spikes. • Useful for entering at the start of new impulses. Automated Alerts: • Set alerts on the built-in conditions “Bullish EWStd Expansion Alert” or “Bearish EWStd Expansion Alert” to receive a popup or mobile push when a burst occurs. This compact tool unifies trend, volatility and multi-timeframe analysis into a single indicator—ideal for traders who want to see trend direction, current dispersion, and timely volatility burst signals all at once.
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Sesilya tarafından
2
EMD Trend [InvestorUnknown]EMD Trend is a dynamic trend-following indicator that utilizes Exponential Moving Deviation (EMD) to build adaptive channels around a selected moving average. Designed for traders who value responsive trend signals with built-in volatility sensitivity, this tool highlights directional bias, market regime shifts, and potential breakout opportunities. How It Works Instead of using standard deviation, EMD Trend employs the exponential moving average of the absolute deviation from a moving average—producing smoother, faster-reacting upper and lower bounds: Bullish (Risk-ON Long): Price crosses above the upper EMD band Bearish (Risk-ON Short): Price crosses below the lower EMD band Neutral: Price stays within the channel, indicating potential mean reversion or low momentum Trend direction is defined by price interaction with these bands, and visual cues (color-coded bars and fills) help quickly identify market conditions. Features 7 Moving Average Types: SMA, EMA, HMA, DEMA, TEMA, RMA, FRAMA Custom Price Source: Choose close, hl2, ohlc4, or others EMD Multiplier: Controls the width of the deviation envelope Bar Coloring: Candles change color based on current trend Intra-bar Signal Option: Enables faster updates (with optional repainting) Speculative Zones: Fills highlight aggressive momentum moves beyond EMD bounds Backtest Mode Switch to Backtest Mode for performance evaluation over historical data: Equity Curve Plot: Compare EMD Trend strategy vs. Buy & Hold Trade Metrics Table: View number of trades, win/loss stats, profits Performance Metrics Table: Includes CAGR, Sharpe, max drawdown, and more Custom Start Date: Select from which date the backtest should begin Trade Sizing: Configure capital and trade percentage per entry Signal Filters: Choose from Long Only, Short Only, or Both Alerts Built-in alerts let you automate entries, exits, and trend transitions: LONG (EMD Trend) - Trend flips to Long SHORT (EMD Trend) - Trend flips to Short RISK-ON LONG - Price crosses above upper EMD band RISK-OFF LONG - Price crosses back below upper EMD band RISK-ON SHORT - Price crosses below lower EMD band RISK-OFF SHORT - Price crosses back above lower EMD band Use Cases Trend Confirmation with volatility-sensitive boundaries Momentum Entry Filtering via breakout zones Mean Reversion Avoidance in sideways markets Backtesting & Strategy Building with real-time metrics Disclaimer This indicator is intended for informational and educational purposes only. It does not constitute investment advice. Historical performance does not guarantee future results. Always backtest and use in simulation before live trading.
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InvestorUnknown tarafından
3
RMSD Trend [InvestorUnknown]RMSD Trend is a trend-following indicator that utilizes Root Mean Square Deviation (RMSD) to dynamically construct a volatility-weighted trend channel around a selected moving average. This indicator is designed to enhance signal clarity, minimize noise, and offer quantitative insights into market momentum, ideal for both discretionary and systematic traders. How It Works At its core, RMSD Trend calculates a deviation band around a selected moving average using the Root Mean Square Deviation (similar to standard deviation but with squared errors), capturing the magnitude of price dispersion over a user-defined period. The logic is simple: When price crosses above the upper deviation band, the market is considered bullish (Risk-ON Long). When price crosses below the lower deviation band, the market is considered bearish (Risk-ON Short). If price stays within the band, the market is interpreted as neutral or ranging, offering low-risk decision zones. The indicator also generates trend flips (Long/Short) based on crossovers and crossunders of the price and the RMSD bands, and colors candles accordingly for enhanced visual feedback. Features 7 Moving Average Types: Choose between SMA, EMA, HMA, DEMA, TEMA, RMA, and FRAMA for flexibility. Customizable Source Input: Use price types like close, hl2, ohlc4, etc. Volatility-Aware Channel: Adjustable RMSD multiplier determines band width based on volatility. Smart Coloring: Candles and bands adapt their colors to reflect trend direction (green for bullish, red for bearish). Intra-bar Repainting Toggle: Option to allow more responsive but repaintable signals. Speculation Fill Zones: When price exceeds the deviation channel, a semi-transparent fill highlights potential momentum surges. Backtest Mode Switching to Backtest Mode unlocks a robust suite of simulation features: Built-in Equity Curve: Visualizes both strategy equity and Buy & Hold performance. Trade Metrics Table: Displays the number of trades, win rates, gross profits/losses, and long/short breakdowns. Performance Metrics Table: Includes key stats like CAGR, drawdown, Sharpe ratio, and more. Custom Date Range: Set a custom start date for your backtest. Trade Sizing: Simulate results using position sizing and initial capital settings. Signal Filters: Choose between Long & Short, Long Only, or Short Only strategies. Alerts The RMSD Trend includes six built-in alert conditions: LONG (RMSD Trend) - Trend flips from Short to Long SHORT (RMSD Trend) - Trend flips from Long to Short RISK-ON LONG (RMSD Trend) - Price crosses above upper RMSD band RISK-OFF LONG (RMSD Trend) - Price falls back below upper RMSD band RISK-ON SHORT (RMSD Trend) - Price crosses below lower RMSD band RISK-OFF SHORT (RMSD Trend) - Price rises back above lower RMSD band Use Cases Trend Confirmation: Confirms directional bias with RMSD-weighted confidence zones. Breakout Detection: Highlights moments when price breaks free from historical volatility norms. Mean Reversion Filtering: Avoids false signals by incorporating RMSD’s volatility sensitivity. Strategy Development: Backtest your signals or integrate with a broader system for alpha generation. Settings Summary Display Mode: Overlay (default) or Backtest Mode Average Type: Choose from SMA, EMA, HMA, DEMA, etc. Average Length: Lookback window for moving average RMSD Multiplier: Band width control based on RMS deviation Source: Input price source (close, hl2, ohlc4, etc.) Intra-bar Updating: Real-time updates (may repaint) Color Bars: Toggle bar coloring by trend direction Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice. Past performance, including backtest results, is not indicative of future results. Use with caution and always test thoroughly before live deployment.
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InvestorUnknown tarafından
1
Trailing Stop Loss [TradingFinder] 4 Machine Learning Methods🔵 Introduction The trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward. Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision. SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading. The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management. A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making. 🔵 How to Use 🟣 SL Levels The trailing stop indicator sets SL based on pivot levels and ATR, offering four options: very tight, tight, wide, or very wide. Very tight SLs suit scalpers, while wide SLs fit swing traders. Select the base level to match your strategy. If price hits the SL, the trade closes, and the indicator evaluates the next trade using the selected filter. This ensures disciplined trade management. The cycle restarts with a new confirmed entry. Very tight SLs, set near recent pivots, trigger exits early to minimize risk but limit profits in volatile markets. Wide SLs, shown as farther lines, allow more price movement but increase exposure to losses. Adjust based on ATR and conditions, noting SL breaches open new positions. 🟣 Visualization The indicator’s visual cues, like colored profit zones, simplify monitoring, with light green showing the profit area from EP to trailed SL. Dashed lines mark entry points, while solid lines track the trailed SL, triggering new positions when breached. When price moves into profit, the area between EP and SL is colored—light green for longs, light red for shorts. This highlights the profit zone visually. The SL trails price, locking in gains as the trade progresses. 🟣 Filters Upon trade entry, the indicator requires confirmation via filters like SMA 2x or ADX to validate momentum. Filters reduce false entries, though no guarantee exists for improved outcomes. Monitor price action post-entry for trade validity. Filters like Momentum or ADX assess trend strength before entry. For example, ADX above 25 confirms strong trends. Choose “none” for unfiltered entries. 🟣 Bullish Alert For a bullish trade, the indicator opens a long position with a green SL Line (after optional filters), trailing the SL below price. Set alerts to On in the settings for notifications, or Off to monitor manually. 🟣 Bearish Alert In a bearish trade, the indicator opens a short position with a red SL Line post-confirmation, trailing the SL above price. With alerts On in the settings, it notifies the potential reversal. 🟣 Panel A table displays all trades’ details, including Win Rates, PNL, and trade status. This real-time data aids in tracking performance. Check the table to assess trade outcomes instantly. Review the table regularly to evaluate trade performance and adjust settings. Consistent monitoring ensures alignment with market dynamics. This maximizes the indicator’s effectiveness. 🔵 Settings Length (Default: 10) : Sets the pivot period for calculating SL levels, balancing sensitivity and reliability. Base Level : Options (“Very tight,” “Tight,” “Wide,” “Very wide”) adjust SL distance via ATR. Show EP Checkbox : Toggles visibility of the entry point on the chart. Show PNL : Displays profit/loss data for active and closed trades. Filter : Options (“none,” “SMA 2x,” “Momentum,” “ADX”) validate trade entries. 🔵 Conclusion The trailing stop indicator, a dynamic risk management tool, adjusts SLs using pivot levels and ATR. Its confirmation filters reduce false entries, boosting precision. Backtests show 20% loss reduction in trending markets. Customizable SL settings and visual profit zones enhance usability across trading styles. The real-time table provides clear trade insights, streamlining analysis. It’s ideal for forex, stocks, or crypto. While filters like ADX improve entry accuracy, no setup guarantees success in all conditions. Contextual analysis, like trend strength, is key. This indicator empowers disciplined, data-driven trading.
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TFlab tarafından
12
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI) What is Lyapunov Market Instability? Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes. Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth. Theoretical Foundation (Chaos Theory & Lyapunov Exponents) In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories: λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect) λ < 0: System is stable—trajectories converge, perturbations die out λ ≈ 0: Edge of chaos—transition between regimes Phase Space Reconstruction Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions: Time-delay embedding: Create vectors from price at different lags Nearest neighbor search: Find historically similar market states Trajectory evolution: Track how these similar states diverged over time Divergence rate: Calculate average exponential separation Market Application Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work Transition zones: Market regime about to change, reduce position size, wait for confirmation How LMI Works 1. Phase Space Construction Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure. 2. Lyapunov Calculation For each current state, we: - Find similar historical states within epsilon (ε) distance - Track how these initially similar states evolved - Measure exponential divergence rate - Average across multiple trajectories for robustness 3. Signal Generation Chaos signals: When λ crosses above threshold, market enters trending regime Stability signals: When λ crosses below threshold, market enters ranging regime Divergence detection: Price/Lyapunov divergences signal potential reversals 4. Rothko Visualization Color fields: Background zones represent market states with Rothko-inspired palettes Glowing line: Lyapunov exponent with intensity reflecting market state Minimalist design: Focus on essential information without clutter Inputs: 📐 Lyapunov Parameters Embedding Dimension (default: 3) Dimensions for phase space reconstruction 2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns 4-5: Complex dynamics (stocks/indices) - captures intricate market structures Higher dimensions need exponentially more data but reveal deeper patterns Time Delay τ (default: 1) Lag between phase space coordinates 1: High-frequency (1m-15m charts) - captures rapid market shifts 2-3: Medium frequency (1H-4H) - balances noise and signal 4-5: Low frequency (Daily+) - focuses on major regime changes Match to your timeframe's natural cycle Initial Separation ε (default: 0.001) Neighborhood size for finding similar states 0.0001-0.0005: Highly liquid markets (major forex pairs) 0.0005-0.002: Normal markets (large-cap stocks) 0.002-0.01: Volatile markets (crypto, small-caps) Smaller = more sensitive to chaos onset Evolution Steps (default: 10) How far to track trajectory divergence 5-10: Fast signals for scalping - quick regime detection 10-20: Balanced for day trading - reliable signals 20-30: Slow signals for swing trading - major regime shifts only Nearest Neighbors (default: 5) Phase space points for averaging 3-4: Noisy/fast markets - adapts quickly 5-6: Balanced (recommended) - smooth yet responsive 7-10: Smooth/slow markets - very stable signals 📊 Signal Parameters Chaos Threshold (default: 0.05) Lyapunov value above which market is chaotic 0.01-0.03: Sensitive - more chaos signals, earlier detection 0.05: Balanced - optimal for most markets 0.1-0.2: Conservative - only strong trends trigger Stability Threshold (default: -0.05) Lyapunov value below which market is stable -0.01 to -0.03: Sensitive - quick stability detection -0.05: Balanced - reliable ranging signals -0.1 to -0.2: Conservative - only deep stability Signal Smoothing (default: 3) EMA period for noise reduction 1-2: Raw signals for experienced traders 3-5: Balanced - recommended for most 6-10: Very smooth for position traders 🎨 Rothko Visualization Rothko Classic: Deep reds for chaos, midnight blues for stability Orange/Red: Warm sunset tones throughout Blue/Black: Cool, meditative ocean depths Purple/Grey: Subtle, sophisticated palette Visual Options: Market Zones : Background fields showing regime areas Transitions: Arrows marking regime changes Divergences: Labels for price/Lyapunov divergences Dashboard: Real-time state and trading signals Guide: Educational panel explaining the theory Visual Logic & Interpretation Main Elements Lyapunov Line: The heart of the indicator Above chaos threshold: Market is trending, follow momentum Below stability threshold: Market is ranging, fade extremes Between thresholds: Transition zone, reduce risk Background Zones: Rothko-inspired color fields Red zone: Chaotic regime (trending) Gray zone: Transition (uncertain) Blue zone: Stable regime (ranging) Transition Markers: Up triangle: Entering chaos - start trend following Down triangle: Entering stability - start mean reversion Divergence Signals: Bullish: Price makes low but Lyapunov rising (stability breaking down) Bearish: Price makes high but Lyapunov falling (chaos dissipating) Dashboard Information Market State: Current regime (Chaotic/Stable/Transitioning) Trading Bias: Specific strategy recommendation Lyapunov λ: Raw value for precision Signal Strength: Confidence in current regime Last Change: Bars since last regime shift Action: Clear trading directive Trading Strategies In Chaotic Regime (λ > threshold) Follow trends aggressively: Breakouts have high success rate Use momentum strategies: Moving average crossovers work well Wider stops: Expect larger swings Pyramid into winners: Trends tend to persist In Stable Regime (λ < threshold) Fade extremes: Mean reversion dominates Use oscillators: RSI, Stochastic work well Tighter stops: Smaller expected moves Scale out at targets: Trends don't persist In Transition Zone Reduce position size: Uncertainty is high Wait for confirmation: Let regime establish Use options: Volatility strategies may work Monitor closely: Quick changes possible Advanced Techniques - Multi-Timeframe Analysis - Higher timeframe LMI for regime context - Lower timeframe for entry timing - Alignment = highest probability trades - Divergence Trading - Most powerful at regime boundaries - Combine with support/resistance - Use for early reversal detection - Volatility Correlation - Chaos often precedes volatility expansion - Stability often precedes volatility contraction - Use for options strategies Originality & Innovation LMI represents a genuine breakthrough in applying chaos theory to markets: True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement Rothko Aesthetic: Transforms complex math into meditative visual experience Regime Detection: Identifies market state changes before price makes them obvious Practical Application: Clear, actionable signals from theoretical physics This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics. Best Practices Start with defaults: Parameters are optimized for broad market conditions Match to your timeframe: Adjust tau and evolution steps Confirm with price action: LMI shows regime, not direction Use appropriate strategies: Chaos = trend, Stability = reversion Respect transitions: Reduce risk during regime changes Alerts Available Chaos Entry: Market entering chaotic regime - prepare for trends Stability Entry: Market entering stable regime - prepare for ranges Bullish Divergence: Potential bottom forming Bearish Divergence: Potential top forming Chart Information Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes Academic References Takens, F. (1981). "Detecting strange attractors in turbulence" Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series" Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents" Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering. Disclaimer This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results. See markets through the lens of chaos. Trade the regime, not the noise. Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
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DskyzInvestments tarafından
SpeedBullish Strategy Confirm V6.2SpeedBullish Strategy Confirm V6.2 SpeedBullish V6.2 is an advanced price-action + indicator-based strategy designed to confirm trend strength and signal entries with high precision. This version builds on the W/M pattern structure and adds dynamic filtering with EMA, MACD Histogram, RSI, ATR, and Volume. ✅ Signal Conditions 🔹 Buy Signal: Price above EMA10 or EMA15 MACD Histogram crosses above 0 RSI > 50 (Optional) Higher low via Pivot Low (Optional) ATR > ATR SMA * Multiplier (Optional) Volume > SMA * Multiplier 🔻 Sell Signal: Price below EMA10 or EMA15 MACD Histogram crosses below 0 RSI < 50 (Optional) Lower high via Pivot High (Optional) Confirmed high volatility and volume ⚙️ Strategy Features MACD Histogram for momentum shift detection RSI filtering for momentum confirmation EMA10/15 for trend direction ATR-based volatility filter Volume confirmation filter Dynamic TP/SL + Trailing Stop Webhook Integration for MT5 auto-trade Visual signal markers + background highlight 🔔 Alerts Alerts are sent in JSON format via alert() with the current symbol, action (buy/sell), and price. Webhook endpoint and secret key are configurable. 📈 How to Use Attach the strategy to any symbol and timeframe Customize filters and confirmations to fit your market conditions Enable webhook alerts for integration with your MT5 Expert Advisor or trading bot Backtest and optimize before live deployment
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thaungkmitl tarafından
Support and Resistance Profile with Volatility ClusteringThe indicator begins by looking at recent volatility behavior in the market: it measures the average true range over your chosen “Length” and compares it to the average true range over ten times that period. When volatility over the short window is high relative to longer-term volatility, we mark that period as a “cluster.” As price moves through these clusters—whether in a quiet period or a sudden burst of activity—the script isolates each cluster and examines the sequence of closing prices within it. Within every cluster, the algorithm next finds the points along the price path that matter most to a human eye, smoothing out minor wobbles and highlighting the peaks and valleys that define the cluster’s shape. It does this by drawing a straight line between the beginning and end of the cluster, then repeatedly snapping the single point that deviates most from that line back onto it and re-interpolating, until it has identified a fixed number of perceptually important points. Those points capture where price really turned or accelerated, stripping away noise so that you see the genuine memory-markers in each volatility episode. Each of those important points inherits a “weight” based on the cluster’s normalized volatility—essentially how large the average true range in that cluster was relative to its average close. Over your “Main Length for Profile” window, every time one of these weighted points occurs at a particular price level, it adds to a running total in that level’s bin. At the end of the window you see a silhouette of boxes extending to the right of the chart: where boxes are wide, many important points (with high volatility weight) have happened there in the past; where boxes are thin or absent, price memory is light. For a trader, the value of this profile lies in spotting zones where the market has repeatedly “remembered” price extremes during volatile episodes—those are areas where support or resistance is likely to be strongest. Conversely, gaps in the profile—price levels with little weighted history—suggest frictionless zones. If price enters such a gap, it may move swiftly until it encounters another region of heavy memory. You can use this in several ways: as a filter on breakouts and breakdowns (only trade through a gap when you see sufficient momentum), as a guide for scaling into positions (add when price enters a low-memory zone and tighten stops where memory boxes thicken), or to anticipate where price might pause or reverse (when it reaches a band of wide boxes). By turning raw volatility clusters into a human-readable map of price memory, this tool helps you see at a glance where the market is likely to push or pause—and plan entries, exits, and risk targets accordingly.
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mertenes3 tarafından
Directionality OscillatorDirectionality Oscillator is a simple momentum tool that measures net price displacement against total price activity over a chosen look-back period. It takes today’s closing price minus the close from “len” bars ago and divides that by the sum of all absolute bar-to-bar moves across the same span. The result is a value between –1 and +1, where positive values show that upward moves dominated and negative values show that downward moves prevailed. To smooth out short-term noise, the indicator applies a five-bar simple moving average to the normalized value. A color gradient—from red at –1, through gray at 0, to green at +1—paints the line, making it easy to see whether bearish or bullish pressure is strongest. Two horizontal lines at the user-defined threshold and its negative mark zones of extreme directional strength. Readings above the positive threshold signal strong bullish momentum, and readings below the negative threshold signal strong bearish momentum. Traders can watch for crossings above or below these threshold lines as trend confirmations or potential reversal warnings. A cross of the zero line indicates a shift in net directional control and can serve as an early trend-change alert when supported by price action or volume. Because it filters out sideways noise by normalizing against total activity, it highlights sustained directional thrust more clearly than a raw price-change measure.
Pine Script® göstergesi
mertenes3 tarafından
Eigenvector Centrality Drift (ECD) - Market State Network What is Eigenvector Centrality Drift (ECD)? Eigenvector Centrality Drift (ECD) is a groundbreaking indicator that applies concepts from network science to financial markets. Instead of viewing price as a simple series, ECD models the market as a dynamic network of “micro-states”—distinct combinations of price, volatility, and volume. By tracking how the influence of these states changes over time, ECD helps you spot regime shifts and transitions in market character before they become obvious in price. This is not another moving average or momentum oscillator. ECD is inspired by eigenvector centrality—a measure of influence in network theory—and adapts it to the world of price action, volatility, and volume. It’s about understanding which market states are “in control” and when that control is about to change. Theoretical Foundation Network Science: In complex systems, nodes (states) and edges (transitions) form a network. Eigenvector centrality measures how influential a node is, not just by its direct connections, but by the influence of the nodes it connects to. Market Micro-States: Each bar is classified into a “state” based on price change, volatility, and volume. The market transitions between these states, forming a network of possible regimes. Centrality Drift: By tracking the centrality (influence) of the current state, and how it changes (drifts) over time, ECD highlights when the market’s “center of gravity” is shifting—often a precursor to major moves or regime changes. How ECD Works State Classification: Each bar is assigned to one of N market micro-states, based on a weighted combination of normalized price change, volatility, and volume. Transition Matrix: Over a rolling window, ECD tracks how often the market transitions from each state to every other state, forming a transition probability matrix. Centrality Calculation: Using a simplified eigenvector approach, ECD calculates the “influence” score for each state, reflecting how central it is to the network of recent market behavior. Centrality Drift: The indicator tracks the Z-score of the change in centrality for the current state. Rapid increases or decreases, or a shift in the dominant state, signal a potential regime shift. Dominant State: ECD also highlights which state currently has the highest influence, providing insight into the prevailing market character. Inputs: 🌐 Market State Configuration Number of Market States (n_states, default 6): Number of distinct micro-states to track. 3–4: Simple (Up/Down/Sideways) 5–6: Balanced (recommended) 7–9: Complex, more nuanced Price Change Weight (price_weight, default 0.4): How much price movement defines a state. Higher = more directional. Volatility Weight (vol_weight, default 0.3): How much volatility defines a state. Higher = more regime focus. Volume Weight (volume_weight, default 0.3): How much volume defines a state. Higher = more participation focus. 🔗 Network Analysis Transition Matrix Window (transition_window, default 50): Lookback for building the state transition matrix. Shorter: Adapts quickly Longer: More stable Influence Decay Factor (influence_decay, default 0.85): How much influence propagates through the network. Higher: Distant transitions matter more Lower: Only immediate transitions matter Drift Detection Sensitivity (drift_sensitivity, default 1.5): Z-score threshold for significant centrality drift. Lower: More signals Higher: Only major shifts 🎨 Visualization Show Network Visualization (show_network, default true): Background color and effects based on network structure. Show Centrality Score (show_centrality, default true): Plots the current state’s centrality measure. Show Drift Indicator (show_drift, default true): Plots the centrality drift Z-score. Show State Map (show_state_map, default true): Dashboard showing all state centralities and which is dominant. Color Scheme (color_scheme, default "Quantum"): “Quantum”: Cyan/Magenta “Neural”: Green/Blue “Plasma”: Yellow/Pink “Matrix”: Green/Black Color Schemes Dynamic gradients reflect the current state’s centrality and drift, using your chosen color palette. Background network effect: The more central the current state, the more intense the background. Centrality and drift lines: Color-coded for clarity and regime shift detection. Visual Logic Centrality Score Line: Plots the influence of the current state, with glow for emphasis. Drift Indicator: Histogram of centrality drift Z-score, green for positive, red for negative. Threshold Lines: Dotted lines mark the drift sensitivity threshold for regime shift alerts. State Map Dashboard: Top-right panel shows all state centralities, highlights the current and dominant state, and visualizes influence with bars. Information Panel: Bottom-left panel summarizes current state, centrality, dominant state, drift Z-score, and regime shift status. How to Use ECD Centrality Score: High = current state is highly influential; low = state is peripheral. Drift Z-Score: Large positive/negative = rapid change in influence, regime shift likely. Near zero = stable network, no major shift. Dominant State: The state with the highest centrality is “in control” of the market’s transitions. State Map: Use to see which states are rising or falling in influence. Tips: Use fewer states for simple markets, more for nuanced analysis. Watch for drift Z-score crossing the threshold—these are your regime shift signals. Combine with your own system for confirmation. Alerts: ECD Regime Shift: Significant centrality drift detected—potential regime change. ECD State Change: Market state transition occurred. ECD Dominance Shift: Dominant market state has changed. Originality & Usefulness ECD is not a mashup or rehash of standard indicators. It is a novel application of network science and eigenvector centrality to market microstructure, providing a new lens for understanding regime shifts and market transitions. The state network, centrality drift, and dashboard are unique to this script. ECD is designed for anticipation, not confirmation—helping you see the market’s “center of gravity” shift before price action makes it obvious. Chart Info Script Name: Eigenvector Centrality Drift (ECD) – Market State Network Recommended Use: Any asset, any timeframe. Tune parameters to your style. Disclaimer This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results. See the market as a network. Anticipate the shift in influence. — Dskyz , for DAFE Trading Systems
Pine Script® göstergesi
DskyzInvestments tarafından
H4 Swing Grade Checklist English V.1✅ H4 Swing Grade Checklist – Auto Grading for Smart Money Setups This script helps manual traders assess the quality of a Smart Money swing trade setup by checking 7 key criteria. The system assigns a grade (A+, A, A−, or B) based on how many and which checklist items are met. 📋 Checklist Items (7 total): ✅ Sweep occurs within 4 candles ✅ MSS (strong break candle) ✅ Entry is placed outside the wick of the sweep ✅ FVG is fresh (not previously used) ✅ FVG overlaps Fibonacci 0.705 level ✅ FVG lies within Premium or Discount zone ✅ Entry is placed at 0.705 Fibonacci retracement 🏅 Grading Criteria: A+ → All 7 checklist items are satisfied A → Only missing #5 (FVG Overlap with 0.705) A− → Only missing #4 (FVG Fresh) B → Only missing #2 (MSS – clear break of structure) – → Any other combinations / fewer than 6 conditions met ⚙️ Features: Toggle visibility with one click Fixed display in top-right or bottom-right of the chart Color-coded grading logic (Green, Yellow, Orange, Blue) Clear checklist feedback for trade journaling or evaluation 🚀 Ideal For: ICT / Smart Money traders Prop firm evaluations Swing trade quality control
Pine Script® göstergesi
weewybravo tarafından
2
Reflexivity Resonance Factor (RRF) - Quantum Flow Reflexivity Resonance Factor (RRF) – Quantum Flow See the Feedback Loops. Anticipate the Regime Shift. What is the RRF – Quantum Flow? The Reflexivity Resonance Factor (RRF) – Quantum Flow is a next-generation market regime detector and energy oscillator, inspired by George Soros’ theory of reflexivity and modern complexity science. It is designed for traders who want to visualize the hidden feedback loops between market perception and participation, and to anticipate explosive regime shifts before they unfold. Unlike traditional oscillators, RRF does not just measure price momentum or volatility. Instead, it models the dynamic feedback between how the market perceives itself (perception) and how it acts on that perception (participation). When these feedback loops synchronize, they create “resonance” – a state of amplified reflexivity that often precedes major market moves. Theoretical Foundation Reflexivity: Markets are not just driven by external information, but by participants’ perceptions and their actions, which in turn influence future perceptions. This feedback loop can create self-reinforcing trends or sudden reversals. Resonance: When perception and participation align and reinforce each other, the market enters a high-energy, reflexive state. These “resonance” events often mark the start of new trends or the climax of existing ones. Energy Field: The indicator quantifies the “energy” of the market’s reflexivity, allowing you to see when the crowd is about to act in unison. How RRF – Quantum Flow Works Perception Proxy: Measures the rate of change in price (ROC) over a configurable period, then smooths it with an EMA. This models how quickly the market’s collective perception is shifting. Participation Proxy: Uses a fast/slow ATR ratio to gauge the intensity of market participation (volatility expansion/contraction). Reflexivity Core: Multiplies perception and participation to model the feedback loop. Resonance Detection: Applies Z-score normalization to the absolute value of reflexivity, highlighting when current feedback is unusually strong compared to recent history. Energy Calculation: Scales resonance to a 0–100 “energy” value, visualized as a dynamic background. Regime Strength: Tracks the percentage of bars in a lookback window where resonance exceeded the threshold, quantifying the persistence of reflexive regimes. Inputs: 🧬 Core Parameters Perception Period (pp_roc_len, default 14): Lookback for price ROC. Lower (5–10): More sensitive, for scalping (1–5min). Default (14): Balanced, for 15min–1hr. Higher (20–30): Smoother, for 4hr–daily. Perception Smooth (pp_smooth_len, default 7): EMA smoothing for perception. Lower (3–5): Faster, more detail. Default (7): Balanced. Higher (10–15): Smoother, less noise. Participation Fast (prp_fast_len, default 7): Fast ATR for immediate volatility. 5–7: Scalping. 7–10: Day trading. 10–14: Swing trading. Participation Slow (prp_slow_len, default 21): Slow ATR for baseline volatility. Should be 2–4x fast ATR. Default (21): Works with fast=7. ⚡ Signal Configuration Resonance Window (res_z_window, default 50): Z-score lookback for resonance normalization. 20–30: More reactive. 50: Medium-term. 100+: Very stable. Primary Threshold (rrf_threshold, default 1.5): Z-score level for “Active” resonance. 1.0–1.5: More signals. 1.5: Balanced. 2.0+: Only strong signals. Extreme Threshold (rrf_extreme, default 2.5): Z-score for “Extreme” resonance. 2.5: Major regime shifts. 3.0+: Only the most extreme. Regime Window (regime_window, default 100): Lookback for regime strength (% of bars with resonance spikes). Higher: More context, slower. Lower: Adapts quickly. 🎨 Visual Settings Show Resonance Flow (show_flow, default true): Plots the main resonance line with glow effects. Show Signal Particles (show_particles, default true): Circular markers at active/extreme resonance points. Show Energy Field (show_energy, default true): Background color based on resonance energy. Show Info Dashboard (show_dashboard, default true): Status panel with resonance metrics. Show Trading Guide (show_guide, default true): On-chart quick reference for interpreting signals. Color Mode (color_mode, default "Spectrum"): Visual theme for all elements. “Spectrum”: Cyan→Magenta (high contrast) “Heat”: Yellow→Red (heat map) “Ocean”: Blue gradients (easy on eyes) “Plasma”: Orange→Purple (vibrant) Color Schemes Dynamic color gradients are used for all plots and backgrounds, adapting to both resonance intensity and direction: Spectrum: Cyan/Magenta for bullish/bearish resonance. Heat: Yellow/Red for bullish, Blue/Purple for bearish. Ocean: Blue gradients for both directions. Plasma: Orange/Purple for high-energy states. Glow and aura effects: The resonance line is layered with multiple glows for depth and signal strength. Background energy field: Darker = higher energy = stronger reflexivity. Visual Logic Main Resonance Line: Shows the smoothed resonance value, color-coded by direction and intensity. Glow/Aura: Multiple layers for visual depth and to highlight strong signals. Threshold Zones: Dotted lines and filled areas mark “Active” and “Extreme” resonance zones. Signal Particles: Circular markers at each “Active” (primary threshold) and “Extreme” (extreme threshold) event. Dashboard: Top-right panel shows current status (Dormant, Building, Active, Extreme), resonance value, energy %, and regime strength. Trading Guide: Bottom-right panel explains all states and how to interpret them. How to Use RRF – Quantum Flow Dormant (💤): Market is in equilibrium. Wait for resonance to build. Building (🌊): Resonance is rising but below threshold. Prepare for a move. Active (🔥): Resonance exceeds primary threshold. Reflexivity is significant—consider entries or exits. Extreme (⚡): Resonance exceeds extreme threshold. Major regime shift likely—watch for trend acceleration or reversal. Energy >70%: High conviction, crowd is acting in unison. Above 0: Bullish reflexivity (positive feedback). Below 0: Bearish reflexivity (negative feedback). Regime Strength: % of bars in “Active” state—higher = more persistent regime. Tips: - Use lower lookbacks for scalping, higher for swing trading. - Combine with price action or your own system for confirmation. - Works on all assets and timeframes—tune to your style. Alerts RRF Activation: Resonance crosses above primary threshold. RRF Extreme: Resonance crosses above extreme threshold. RRF Deactivation: Resonance falls below primary threshold. Originality & Usefulness RRF – Quantum Flow is not a mashup of existing indicators. It is a novel oscillator that models the feedback loop between perception and participation, then quantifies and visualizes the resulting resonance. The multi-layered color logic, energy field, and regime strength dashboard are unique to this script. It is designed for anticipation, not confirmation—helping you see regime shifts before they are obvious in price. Chart Info Script Name: Reflexivity Resonance Factor (RRF) – Quantum Flow Recommended Use: Any asset, any timeframe. Tune parameters to your style. Disclaimer This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results. Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
Pine Script® göstergesi
DskyzInvestments tarafından
Tangent Extrapolation ForecastTangent Extrapolation Forecast This indicator visually projects price direction by drawing a smoothed sequence of tangent lines based on recent price movements. For each bar in a user-defined lookback window, it calculates the slope over a smoothing period and extends the projected price forward. The resulting polyline forecast connect the endpoints of the extrapolations, and is color-coded to reflect directional changes: green for upward moves, red for downward, and gray for flat segments. This tool can assist traders in visualizing short-term momentum and potential trend continuity without introducing artificial future gaps. Inputs: Bars to Use: Number of historical bars used in the forecast. Slope Smoothing Window: The number of bars used to calculate slope for projection. Source: Price input for calculations (default is close). This indicator does not generate buy/sell signals. It is intended as a visual aid to support discretionary analysis.
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Tradenometry tarafından
Math by Thomas Swing RangeMath by Thomas Swing Range is a simple yet powerful tool designed to visually highlight key swing levels in the market based on a user-defined lookback period. It identifies the highest high, lowest low, and calculates the midpoint between them — creating a clear range for swing trading strategies. These levels can help traders: Spot potential support and resistance zones Analyze price rejection near range boundaries Frame mean-reversion or breakout setups The indicator continuously updates and extends these lines into the future, making it easier to plan and manage trades with visual clarity. 🛠️ How to Use Add to Chart: Apply the indicator on any timeframe and asset (works best on higher timeframes like 1H, 4H, or Daily). Configure Parameters: Lookback Period: Number of candles used to detect the highest high and lowest low. Default is 20. Extend Lines by N Bars: Number of future bars the levels should be projected to the right. Interpret Lines: 🔴 Red Line: Swing High (Resistance) 🟢 Green Line: Swing Low (Support) 🔵 Blue Line: Midpoint (Mean level — useful for equilibrium-based strategies) Trade Ideas: Bounce trades from swing high/low zones. Breakout confirmation if price closes strongly outside the range. Reversion trades if price moves toward the midpoint after extreme moves.
Pine Script® göstergesi
MathThomas tarafından
5
Multi-Session ORBThe Multi-Session ORB Indicator is a customizable Pine Script (version 6) tool designed for TradingView to plot Opening Range Breakout (ORB) levels across four major trading sessions: Sydney, Tokyo, London, and New York. It allows traders to define specific ORB durations and session times in Central Daylight Time (CDT), making it adaptable to various trading strategies. Key Features: 1. Customizable ORB Duration: Users can set the ORB duration (default: 15 minutes) via the inputMax parameter, determining the time window for calculating the high and low of each session’s opening range. 2. Flexible Session Times: The indicator supports user-defined session and ORB times for: ◦ Sydney: Default ORB (17:00–17:15 CDT), Session (17:00–01:00 CDT) ◦ Tokyo: Default ORB (19:00–19:15 CDT), Session (19:00–04:00 CDT) ◦ London: Default ORB (02:00–02:15 CDT), Session (02:00–11:00 CDT) ◦ New York: Default ORB (08:30–08:45 CDT), Session (08:30–16:00 CDT) 3. Session-Specific ORB Levels: For each session, the indicator calculates and tracks the high and low prices during the specified ORB period. These levels are updated dynamically if new highs or lows occur within the ORB timeframe. 4. Visual Representation: ◦ ORB high and low lines are plotted only during their respective session times, ensuring clarity. ◦ Each session’s lines are color-coded for easy identification: ▪ Sydney: Light Yellow (high), Dark Yellow (low) ▪ Tokyo: Light Pink (high), Dark Pink (low) ▪ London: Light Blue (high), Dark Blue (low) ▪ New York: Light Purple (high), Dark Purple (low) ◦ Lines are drawn with a linewidth of 2 and disappear when the session ends or if the timeframe is not intraday (or exceeds the ORB duration). 5. Intraday Compatibility: The indicator is optimized for intraday timeframes (e.g., 1-minute to 15-minute charts) and only displays when the chart’s timeframe multiplier is less than or equal to the ORB duration. How It Works: • Session Detection: The script uses the time() function to check if the current bar falls within the user-defined ORB or session time windows, accounting for all days of the week. • ORB Logic: At the start of each session’s ORB period, the script initializes the high and low based on the first bar’s prices. It then updates these levels if subsequent bars within the ORB period exceed the current high or fall below the current low. • Plotting: ORB levels are plotted as horizontal lines during the respective session, with visibility controlled to avoid clutter outside session times or on incompatible timeframes. Use Case: Traders can use this indicator to identify key breakout levels for each trading session, facilitating strategies based on price action around the opening range. The flexibility to adjust ORB and session times makes it suitable for various markets (e.g., forex, stocks, or futures) and time zones. Limitations: • The indicator is designed for intraday timeframes and may not display on higher timeframes (e.g., daily or weekly) or if the timeframe multiplier exceeds the ORB duration. • Time inputs are in CDT, requiring users to adjust for their local timezone or market requirements. • If you need to use this for GC/CL/SPY/QQQ you have to adjust the times by one hour. This indicator is ideal for traders focusing on session-based breakout strategies, offering clear visualization and customization for global market sessions.
Pine Script® göstergesi
Eskemo_Bob tarafından
Multi-EnvelopeRMA Multi-Envelope Indicator The RMA Multi-Envelope Indicator is a technical analysis tool designed for TradingView, utilizing Pine Script v6. It creates eight customizable envelope bands around a 200-period Running Moving Average (RMA) on a 5-minute timeframe, based on current market measurements. Each band has independent upper and lower percentage deviations, preset to: Band 1 (0.42%, 0.46%), Band 2 (0.78%, 0.69%), Band 3 (1.01%, 1.03%), Band 4 (1.36%, 1.39%), Band 5 (1.80%, 1.62%), Band 6 (2.15%, 2.13%), Band 7 (2.93%, 2.81%), and Band 8 (4.65%, 4.18%). Users can adjust the timeframe, moving average type (RMA, SMA, or EMA), length, and colors for the basis line and bands via hex codes (e.g., #FF6D00 for the basis and Band 8) with semi-transparent color.rgb fills. Ideal for identifying support/resistance, overbought/oversold conditions, or trend boundaries on a 5-minute chart.
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Servantthought tarafından
Swing High/Low by %REnglish Description Swing High/Low by %R This indicator identifies potential swing high and swing low points by combining William %R overbought/oversold turning points with classic swing price structures. Swing High: Detected when William %R turns down from overbought territory and the price forms a local high (higher than both neighboring bars). Swing Low: Detected when William %R turns up from oversold territory and the price forms a local low (lower than both neighboring bars). This tool is designed to help traders spot possible market reversals and better time their entries and exits. Customizable parameters: Williams %R period Overbought & Oversold thresholds The indicator plots clear signals above/below price bars for easy visualization. For educational purposes. Please use with proper risk management! คำอธิบายภาษาไทย Swing High/Low by %R อินดิเคเตอร์นี้ใช้ระบุจุด Swing High และ Swing Low ที่มีโอกาสเป็นจุดกลับตัวของตลาด โดยอาศัยสัญญาณจาก William %R ที่พลิกกลับตัวบริเวณ overbought/oversold ร่วมกับโครงสร้างราคาแบบ swing Swing High: เกิดเมื่อ William %R พลิกกลับลงจากเขต Overbought และราคาแท่งกลางสูงกว่าทั้งสองแท่งข้างเคียง Swing Low: เกิดเมื่อ William %R พลิกกลับขึ้นจากเขต Oversold และราคาแท่งกลางต่ำกว่าทั้งสองแท่งข้างเคียง ช่วยให้เทรดเดอร์สามารถมองเห็นโอกาสในการกลับตัวของราคา และใช้ประกอบการวางแผนจังหวะเข้าหรือออกจากตลาดได้อย่างแม่นยำมากขึ้น ตั้งค่าได้: ระยะเวลา Williams %R ค่าขอบเขต Overbought & Oversold อินดิเคเตอร์จะแสดงสัญลักษณ์อย่างชัดเจนบนกราฟเพื่อความสะดวกในการใช้งาน ควรใช้ร่วมกับการบริหารความเสี่ยง
Pine Script® göstergesi
August_Supertrader tarafından
3
Beta Tracker [theUltimator5]This script calculates the Pearson correlation coefficient between the charted symbol and a dynamic composite of up to four other user-defined tickers. The goal is to track how closely the current asset’s normalized price behavior aligns with, or diverges from, the selected group (or basket) How can this indicator be valuable? You can compare the correlation of your current symbol against a basket of other tickers to see if it is moving independently, or being pulled with the basket.... or is it moving against the basket. It can be used to help identify 'swap' baskets of stocks or other tickers that tend to generally move together and visually show when your current ticker diverges from the basket. It can be used to track beta (or negative beta) with the market or with a specific ticker. This is best used as a supplement to other trading signals to give a more complete picture of the external forces potentially pulling or pushing the price action of the ticker. 🛠️ How It Works The current symbol and each selected comparison ticker are normalized over a custom lookback window, allowing fair pattern-based comparison regardless of price scale. The normalized values from 1 to 4 selected tickers are averaged into a composite, which represents the group’s collective movement. A Pearson correlation coefficient is computed over a separate correlation lookback period, measuring the relationship between the current asset and the composite. The result is plotted as a dynamic line, with color gradients: Blue = strongly correlated (near +1) Orange = strongly inverse correlation (near –1) Intermediate values fade proportionally A highlighted background appears when the correlation drops below a user-defined threshold (e.g. –0.7), helping identify strong negative beta periods visually. A toggleable info table displays which tickers are currently being compared, along with customizable screen positioning. ⚙️ User Inputs Ticker 1–4: Symbols to compare the current asset against (blank = ignored) Normalization Lookback: Period to normalize each series Correlation Lookback: Period over which correlation is calculated Negative Correlation Highlight: Toggle for background alert and threshold level Comparison Table: Toggle and position controls for an on-screen summary of selected tickers imgur.com ⚠️ Notes The script uses request.security() to pull data from external symbols; these must be available for the selected chart timeframe. A minimum of one valid ticker must be provided for the script to calculate a composite and render correlation.
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TheUltimator5 tarafından