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Parabolic Stoch SAR VisualizerParabolic Stoch SAR Visualizer — Momentum-Driven Trend Precision Tool Overview: Parabolic Stoch SAR Visualizer is a thoughtfully engineered hybrid indicator that blends momentum oscillation and trend-following mechanics into one robust system. By applying a custom Parabolic SAR calculation directly on a double-smoothed stochastic oscillator (rather than on price), it generates cleaner signals with enhanced trend detection and fewer false positives than typical Parabolic RSI or standard SAR variants. Unique Functionality: Momentum smoothing : The base stochastic %K undergoes double smoothing via consecutive simple moving averages, significantly cutting down random noise and erratic swings common in raw stochastic readings. This stabilizes momentum tracking, isolating true price strength and weakness. Custom Parabolic SAR on smoothed momentum : Traditional SAR algorithms operate on price data, acting as trailing stops. This indicator repurposes SAR to work on smoothed stochastic values, effectively converting it into a momentum-driven directional filter. This yields a more adaptive and responsive trend signal focused on genuine momentum shifts instead of price noise. Bounded SAR range and adjustable acceleration : SAR values are mathematically restricted between 0 and 100, aligning with the stochastic scale to prevent distortions. Traders can customize acceleration parameters (start, increment, max) to fine-tune trend sensitivity relative to market volatility or specific strategies. Signal clarity through filterin g: Minimum bar spacing and minimum SAR movement thresholds between plotted dots reduce chart clutter, highlighting only meaningful trend changes and filtering out insignificant fluctuations. Enhanced visuals : The oscillator line smoothly transitions its color gradient between defined uptrend and downtrend hues, intuitively signaling momentum strength. Parabolic SAR dots are offset from the oscillator line with multi-layered glow effects, making trend flips easy to spot at a glance. Trading Application: Trend identification : Momentum-based SAR dots offer precise marking of trend shifts, helping traders avoid false breakouts and premature trades. Entry and exit timing : Combining the double-smoothed stochastic oscillator and SAR dots creates a reliable framework to confirm momentum shifts and optimal trade entries or exits. Customizable for volatility regimes : Adjustable acceleration and filtering parameters allow scalpers to increase signal sensitivity, while swing traders can dial back noise for smoother trend recognition. Visual clarity for fast decisions : Gradient color coding and glowing SAR dots facilitate immediate momentum assessment without complex analysis, empowering quicker, more confident trade actions. Advantages over Parabolic RSI and similar indicators: Parabolic RSI’s direct application of SAR on RSI often results in noisy, choppy signals prone to whipsaws. This indicator’s double-smoothed stochastic foundation delivers a cleaner, steadier signal. Applying SAR to smoothed momentum rather than price transforms it into a directional filter that better captures true market strength with reduced lag. Adaptive plotting thresholds and enhanced visuals minimize clutter and ambiguity, improving trader focus and execution speed.
Indicatore Pine Script®
di BOSWaves
SMT Oscillator: Smarter Money Divergence Detector [PhenLabs]📊Phenlabs - SMT Oscillator: Smarter Money Divergence Detector Version: PineScript™v6 📌Description The SMT Oscillator is a sophisticated tool designed to identify smart money divergence between two correlated assets. By analyzing the momentum and volume-weighted price action of a primary and secondary symbol, traders can spot subtle shifts in market dynamics that often precede significant price movements. This indicator is built to provide a clearer, more filtered view of inter-market relationships, solving the common problem of false signals and market noise. Its primary purpose is to equip traders with a quantifiable edge in detecting potential reversals or continuations that are not obvious on a standard price chart. 🚀Points of Innovation Dual-Symbol Divergence Core: Directly compares momentum (RSI or MACD) between two user-selected symbols to pinpoint true SMT divergence. Volume-Weighted Analysis: Integrates volume delta into the divergence calculation, giving more weight to moves backed by significant market participation. Entropy Filter for Noise Reduction: Employs an entropy calculation to filter out low-quality signals during choppy or consolidating market conditions. Predictive Forecast Line: Utilizes a linear regression model to project the oscillator’s future trajectory, offering a forward-looking glimpse of potential momentum shifts. Customizable Signal Sensitivity: Allows fine-tuning of overbought and oversold levels to adapt to different market volatilities and trading styles. Integrated Signal Alerts: Provides built-in alerts for bullish/bearish zero crosses and overbought/oversold conditions. 🔧Core Components Momentum Engine: The user can select either RSI or MACD as the underlying engine for the divergence calculation, allowing for flexibility in analysis. Normalization Function: Price data from both symbols is normalized using percentage change to ensure a true “apples-to-apples” comparison, regardless of their nominal price differences. Divergence Calculator: The core algorithm that subtracts the secondary symbol’s momentum from the primary’s and normalizes the result using the combined standard deviation. Smoothing Mechanism: An Exponential Moving Average (EMA) is applied to the raw oscillator output to reduce choppiness and provide a clearer signal line. 🔥Key Features Multi-Asset Comparison: Go beyond single-asset analysis by comparing correlated pairs like ES/NQ or BTC/ETH to uncover hidden trading opportunities. Heatmap Visualization: An optional heatmap mode provides an intuitive visual representation of divergence strength, making it easier to gauge market sentiment at a glance. Configurable Lookback and Timeframe: Adjust the lookback period and analysis timeframe to suit your specific strategy, from short-term scalping to long-term trend analysis. Signal Markers: Visual markers are plotted directly on the chart for bullish and bearish zero-line crossovers, providing clear entry and exit signals. 🎨Visualization SMT Oscillator Line: The primary visual element, colored blue for bullish (positive) divergence and orange for bearish (negative) divergence. Zero Line: A solid horizontal line at the zero level, indicating the equilibrium point between the two assets. Crossovers of this line signal a shift in relative strength. Overbought/Oversold Zones: Dotted lines at the +80 and -80 levels (customizable) that highlight extreme divergence readings, often indicating potential exhaustion points. Forecast Line: A predictive line that plots the anticipated path of the oscillator, giving traders an advanced warning of potential changes in momentum. 📖Usage Guidelines Setting Categories Primary Symbol Default: (Chart Symbol) Description: The main asset you are analyzing. Leave blank to use the symbol currently on your chart. Secondary Symbol Default: CME_MINI:ES1! (used with NASDAQ futures due to inherent heavy correlation Description: The asset to compare against the primary symbol. Lookback Period Default: 14 Range: 8-100 Description: Controls the calculation window for momentum (RSI/MACD). Higher values result in a smoother, less sensitive oscillator. Divergence Type Default: RSI Options: RSI, MACD Description: Choose the momentum indicator to use for the divergence calculation. Enable Volume Weighting Default: true Description: When enabled, gives more weight to divergence signals that are accompanied by significant volume. ✅Best Use Cases Identifying high-probability reversal points by spotting divergence in overbought or oversold territory. Confirming the strength of a trend by observing sustained positive or negative divergence. Pairs trading by taking a long position on the outperforming asset and a short position on the underperforming one during a divergence. Risk management by recognizing when a current trend is losing its underlying momentum. ⚠️Limitations Requires Correlated Assets: The indicator’s effectiveness is highly dependent on the selection of two assets with a known correlation (e.g., ES and NQ). Not a Standalone System: Divergence signals should be used in conjunction with other forms of analysis (price action, market structure) and not as a complete trading system. Lagging by Nature: As it is based on moving averages and past price data, the oscillator is inherently lagging and may not capture all rapid price changes. 💡What Makes This Unique Combined Momentum & Volume: Unlike standard oscillators, it fuses momentum with volume delta for a more robust “Smart Money” perspective. Noise-Filtering Mechanism: The proprietary entropy filter is a unique feature designed to weed out insignificant market chatter and focus on high-conviction signals. 🔬How It Works Data Normalization: The script first normalizes the price data of the two selected symbols into percentage changes. This ensures that the comparison is fair, regardless of the difference in their price scales. Momentum Calculation: It then calculates the chosen momentum value (either RSI or MACD histogram) for each of the normalized price series. Divergence Computation: The core of the indicator lies in subtracting the momentum of the secondary symbol from the primary one. This raw divergence is then optionally weighted by volume and filtered for market noise (entropy) to produce the final oscillator value. 💡Note: For best results, use this indicator on adequate timeframes to filter out market noise. Always confirm signals with price action analysis before entering a trade.
Indicatore Pine Script®
di PhenLabs
TRI - Smart Zones============================================================================ # TRI - SMART ZONES v2.0 ## Professional Smart Money Concepts Indicator for Pine Script v6 ============================================================================ ## 📊 OVERVIEW **TRI - Smart Zones** is a comprehensive Smart Money Concepts indicator that combines multiple institutional trading concepts into a single, powerful tool. Built with Pine Script v6 for optimal performance and reliability. ## 🎯 CORE FEATURES ### **Fair Value Gaps (FVG)** - **Detection**: Automatic identification of price imbalances - **Types**: Bullish and Bearish Fair Value Gaps - **Threshold**: Customizable gap size requirements (0.1% default) - **Extension**: Configurable zone projection length - **Mitigation**: Real-time tracking of gap fills ### **Order Blocks (OB)** - **Detection**: Volume-based institutional footprint identification - **Types**: Bullish and Bearish Order Blocks - **Method**: Pivot-based volume analysis with configurable lookback - **Validation**: Market structure confirmation required - **Extension**: Adjustable zone projection ### **BSL/SSL Liquidity Levels** - **Multi-Timeframe**: Automatic higher timeframe reference - **Dynamic**: Real-time level updates and extensions - **Visual**: Clear line markings with timeframe labels - **Smart**: Adaptive timeframe selection based on current chart ### **Fibonacci Extensions** - **ZigZag Integration**: Advanced pivot point detection - **Levels**: Customizable Fibonacci ratios (38.2%, 61.8%, 100%, 161.8%) - **Projection**: Dynamic extension from swing points - **Visual**: Subtle dashed lines with level/price labels ### **Smart Dashboard** - **Zone Statistics**: Real-time FVG and OB counts - **Success Rates**: Mitigation percentages for each zone type - **Market Bias**: Intelligent bullish/bearish/neutral assessment - **Positioning**: Customizable location and size ### **Zone Analysis Engine** - **Technical Confluence**: RSI, ADX, ATR, Volume analysis - **VWAP Integration**: Institutional price reference - **Confidence Scoring**: High/Mid/Low signal classification - **Signal Arrows**: Visual trade direction indicators ## 🔔 ALERT SYSTEM ### **Market Structure Alerts** - `Market Bias Changed` - Shift in overall market sentiment - `BSL Touched` - Buy Side Liquidity level reached - `SSL Touched` - Sell Side Liquidity level reached ### **Zone Touch Alerts** - `OB Touched` - Any Order Block interaction - `Bullish OB Touched` - Bullish Order Block touch - `Bearish OB Touched` - Bearish Order Block touch - `FVG Touched` - Any Fair Value Gap interaction - `Bullish FVG Touched` - Bullish FVG touch - `Bearish FVG Touched` - Bearish FVG touch - `Zone Touched` - Any Smart Zone interaction - `Bullish Zone Touched` - Any bullish zone touch - `Bearish Zone Touched` - Any bearish zone touch ## ⚙️ CONFIGURATION ### **Zone Detection** - Enable/disable FVG and OB detection independently - Maximum zones per type (3-15, default: 8) - Zone-specific threshold and extension settings ### **Visual Customization** - Individual color schemes for each zone type - Adjustable transparency levels - Configurable line styles and widths - Dashboard positioning and sizing options ### **Technical Analysis** - RSI, ADX, ATR period customization - Volume threshold multipliers - Confidence level color coding - Signal display toggle ## 🚀 PINE SCRIPT v6 OPTIMIZATIONS - **User-Defined Types**: Structured data for zones and statistics - **Methods**: Type-specific operations for better code organization - **Enhanced Arrays**: Optimized memory management - **Switch Statements**: Improved performance for zone classification - **Error Handling**: Robust input validation and edge case management - **Performance**: Efficient algorithms for real-time analysis ## 📈 TRADING APPLICATIONS ### **Entry Strategies** - Zone confluence for high-probability setups - Multi-timeframe confirmation via BSL/SSL - Fibonacci extension targets - Signal arrows for directional bias ### **Risk Management** - Zone mitigation for stop-loss placement - Market bias for position sizing - Dashboard statistics for strategy validation ### **Market Analysis** - Institutional footprint identification - Liquidity level mapping - Market structure assessment - Trend continuation vs reversal analysis ## 🔧 TECHNICAL SPECIFICATIONS - **Version**: Pine Script v6 - **Overlay**: True (draws on price chart) - **Max Objects**: 100 boxes, 100 lines, 50 labels - **Performance**: Optimized for real-time analysis - **Compatibility**: All TradingView chart types and timeframes
Indicatore Pine Script®
di riccardo_tempesta
1
Sniper NAS100 Swiss Knife IndicatorSniper Trading System – Master Indicator Description: “Trade with the precision of the market makers themselves.” The Sniper Trading System – Master Indicator is the crown jewel of institutional-level trading tools, engineered for those who demand perfect timing, deadly accuracy, and surgical execution in any market. Designed by a 3× ASCAP Award-winning, multi–funded prop firm trader, this system fuses algorithmic precision with battle-tested price action logic, delivering an unmatched trading edge across Forex, Futures, Indices, and Crypto. Core Features Dealer Range Mapping – Auto-detects the hidden accumulation/distribution zones that drive market direction. Multi-Standard Deviation Targets – Projected with gradient precision (+1 to +4 / -1 to -4) for scalps or swing holds. 12 AM Bias Candle Logic – Reveals the true daily directional bias before the herd even wakes up. Liquidity Sweep Detection – Spots equal highs/lows & engineered stop hunts before the main move. Kill Zone Time Windows – Pre-programmed with the London Session Sniper Hours & New York Precision Plays. Multi-Timeframe RSI Filter – Filters false signals & highlights exhaustion points for sniper entries. Dynamic Alerts – Fire real-time push, email, or webhook notifications for entry, exit, and confluence events. How It Works Identify Bias – Use the 12 AM candle + DXY/RSI overlays to confirm bullish or bearish control. Wait for Liquidity Sweep – Let the market makers hunt stops; your job is to wait. Execute at Kill Zones – Follow the preloaded precision entry times for God-tier sniper plays. Ride to Target Zones – Exit at projected standard deviation levels for mathematically consistent profits. Ideal For Day Traders looking for clean entries and exits.
Indicatore Pine Script®
di Master-Jedi-Trader
Kelly Position Size CalculatorThis position sizing calculator implements the Kelly Criterion, developed by John L. Kelly Jr. at Bell Laboratories in 1956, to determine mathematically optimal position sizes for maximizing long-term wealth growth. Unlike arbitrary position sizing methods, this tool provides a scientifically solution based on your strategy's actual performance statistics and incorporates modern refinements from over six decades of academic research. The Kelly Criterion addresses a fundamental question in capital allocation: "What fraction of capital should be allocated to each opportunity to maximize growth while avoiding ruin?" This question has profound implications for financial markets, where traders and investors constantly face decisions about optimal capital allocation (Van Tharp, 2007). Theoretical Foundation The Kelly Criterion for binary outcomes is expressed as f* = (bp - q) / b, where f* represents the optimal fraction of capital to allocate, b denotes the risk-reward ratio, p indicates the probability of success, and q represents the probability of loss (Kelly, 1956). This formula maximizes the expected logarithm of wealth, ensuring maximum long-term growth rate while avoiding the risk of ruin. The mathematical elegance of Kelly's approach lies in its derivation from information theory. Kelly's original work was motivated by Claude Shannon's information theory (Shannon, 1948), recognizing that maximizing the logarithm of wealth is equivalent to maximizing the rate of information transmission. This connection between information theory and wealth accumulation provides a deep theoretical foundation for optimal position sizing. The logarithmic utility function underlying the Kelly Criterion naturally embodies several desirable properties for capital management. It exhibits decreasing marginal utility, penalizes large losses more severely than it rewards equivalent gains, and focuses on geometric rather than arithmetic mean returns, which is appropriate for compounding scenarios (Thorp, 2006). Scientific Implementation This calculator extends beyond basic Kelly implementation by incorporating state of the art refinements from academic research: Parameter Uncertainty Adjustment: Following Michaud (1989), the implementation applies Bayesian shrinkage to account for parameter estimation error inherent in small sample sizes. The adjustment formula f_adjusted = f_kelly × confidence_factor + f_conservative × (1 - confidence_factor) addresses the overconfidence bias documented by Baker and McHale (2012), where the confidence factor increases with sample size and the conservative estimate equals 0.25 (quarter Kelly). Sample Size Confidence: The reliability of Kelly calculations depends critically on sample size. Research by Browne and Whitt (1996) provides theoretical guidance on minimum sample requirements, suggesting that at least 30 independent observations are necessary for meaningful parameter estimates, with 100 or more trades providing reliable estimates for most trading strategies. Universal Asset Compatibility: The calculator employs intelligent asset detection using TradingView's built-in symbol information, automatically adapting calculations for different asset classes without manual configuration. ASSET SPECIFIC IMPLEMENTATION Equity Markets: For stocks and ETFs, position sizing follows the calculation Shares = floor(Kelly Fraction × Account Size / Share Price). This straightforward approach reflects whole share constraints while accommodating fractional share trading capabilities. Foreign Exchange Markets: Forex markets require lot-based calculations following Lot Size = Kelly Fraction × Account Size / (100,000 × Base Currency Value). The calculator automatically handles major currency pairs with appropriate pip value calculations, following industry standards described by Archer (2010). Futures Markets: Futures position sizing accounts for leverage and margin requirements through Contracts = floor(Kelly Fraction × Account Size / Margin Requirement). The calculator estimates margin requirements as a percentage of contract notional value, with specific adjustments for micro-futures contracts that have smaller sizes and reduced margin requirements (Kaufman, 2013). Index and Commodity Markets: These markets combine characteristics of both equity and futures markets. The calculator automatically detects whether instruments are cash-settled or futures-based, applying appropriate sizing methodologies with correct point value calculations. Risk Management Integration The calculator integrates sophisticated risk assessment through two primary modes: Stop Loss Integration: When fixed stop-loss levels are defined, risk calculation follows Risk per Trade = Position Size × Stop Loss Distance. This ensures that the Kelly fraction accounts for actual risk exposure rather than theoretical maximum loss, with stop-loss distance measured in appropriate units for each asset class. Strategy Drawdown Assessment: For discretionary exit strategies, risk estimation uses maximum historical drawdown through Risk per Trade = Position Value × (Maximum Drawdown / 100). This approach assumes that individual trade losses will not exceed the strategy's historical maximum drawdown, providing a reasonable estimate for strategies with well-defined risk characteristics. Fractional Kelly Approaches Pure Kelly sizing can produce substantial volatility, leading many practitioners to adopt fractional Kelly approaches. MacLean, Sanegre, Zhao, and Ziemba (2004) analyze the trade-offs between growth rate and volatility, demonstrating that half-Kelly typically reduces volatility by approximately 75% while sacrificing only 25% of the growth rate. The calculator provides three primary Kelly modes to accommodate different risk preferences and experience levels. Full Kelly maximizes growth rate while accepting higher volatility, making it suitable for experienced practitioners with strong risk tolerance and robust capital bases. Half Kelly offers a balanced approach popular among professional traders, providing optimal risk-return balance by reducing volatility significantly while maintaining substantial growth potential. Quarter Kelly implements a conservative approach with low volatility, recommended for risk-averse traders or those new to Kelly methodology who prefer gradual introduction to optimal position sizing principles. Empirical Validation and Performance Extensive academic research supports the theoretical advantages of Kelly sizing. Hakansson and Ziemba (1995) provide a comprehensive review of Kelly applications in finance, documenting superior long-term performance across various market conditions and asset classes. Estrada (2008) analyzes Kelly performance in international equity markets, finding that Kelly-based strategies consistently outperform fixed position sizing approaches over extended periods across 19 developed markets over a 30-year period. Several prominent investment firms have successfully implemented Kelly-based position sizing. Pabrai (2007) documents the application of Kelly principles at Berkshire Hathaway, noting Warren Buffett's concentrated portfolio approach aligns closely with Kelly optimal sizing for high-conviction investments. Quantitative hedge funds, including Renaissance Technologies and AQR, have incorporated Kelly-based risk management into their systematic trading strategies. Practical Implementation Guidelines Successful Kelly implementation requires systematic application with attention to several critical factors: Parameter Estimation: Accurate parameter estimation represents the greatest challenge in practical Kelly implementation. Brown (1976) notes that small errors in probability estimates can lead to significant deviations from optimal performance. The calculator addresses this through Bayesian adjustments and confidence measures. Sample Size Requirements: Users should begin with conservative fractional Kelly approaches until achieving sufficient historical data. Strategies with fewer than 30 trades may produce unreliable Kelly estimates, regardless of adjustments. Full confidence typically requires 100 or more independent trade observations. Market Regime Considerations: Parameters that accurately describe historical performance may not reflect future market conditions. Ziemba (2003) recommends regular parameter updates and conservative adjustments when market conditions change significantly. Professional Features and Customization The calculator provides comprehensive customization options for professional applications: Multiple Color Schemes: Eight professional color themes (Gold, EdgeTools, Behavioral, Quant, Ocean, Fire, Matrix, Arctic) with dark and light theme compatibility ensure optimal visibility across different trading environments. Flexible Display Options: Adjustable table size and position accommodate various chart layouts and user preferences, while maintaining analytical depth and clarity. Comprehensive Results: The results table presents essential information including asset specifications, strategy statistics, Kelly calculations, sample confidence measures, position values, risk assessments, and final position sizes in appropriate units for each asset class. Limitations and Considerations Like any analytical tool, the Kelly Criterion has important limitations that users must understand: Stationarity Assumption: The Kelly Criterion assumes that historical strategy statistics represent future performance characteristics. Non-stationary market conditions may invalidate this assumption, as noted by Lo and MacKinlay (1999). Independence Requirement: Each trade should be independent to avoid correlation effects. Many trading strategies exhibit serial correlation in returns, which can affect optimal position sizing and may require adjustments for portfolio applications. Parameter Sensitivity: Kelly calculations are sensitive to parameter accuracy. Regular calibration and conservative approaches are essential when parameter uncertainty is high. Transaction Costs: The implementation incorporates user-defined transaction costs but assumes these remain constant across different position sizes and market conditions, following Ziemba (2003). Advanced Applications and Extensions Multi-Asset Portfolio Considerations: While this calculator optimizes individual position sizes, portfolio-level applications require additional considerations for correlation effects and aggregate risk management. Simplified portfolio approaches include treating positions independently with correlation adjustments. Behavioral Factors: Behavioral finance research reveals systematic biases that can interfere with Kelly implementation. Kahneman and Tversky (1979) document loss aversion, overconfidence, and other cognitive biases that lead traders to deviate from optimal strategies. Successful implementation requires disciplined adherence to calculated recommendations. Time-Varying Parameters: Advanced implementations may incorporate time-varying parameter models that adjust Kelly recommendations based on changing market conditions, though these require sophisticated econometric techniques and substantial computational resources. Comprehensive Usage Instructions and Practical Examples Implementation begins with loading the calculator on your desired trading instrument's chart. The system automatically detects asset type across stocks, forex, futures, and cryptocurrency markets while extracting current price information. Navigation to the indicator settings allows input of your specific strategy parameters. Strategy statistics configuration requires careful attention to several key metrics. The win rate should be calculated from your backtest results using the formula of winning trades divided by total trades multiplied by 100. Average win represents the sum of all profitable trades divided by the number of winning trades, while average loss calculates the sum of all losing trades divided by the number of losing trades, entered as a positive number. The total historical trades parameter requires the complete number of trades in your backtest, with a minimum of 30 trades recommended for basic functionality and 100 or more trades optimal for statistical reliability. Account size should reflect your available trading capital, specifically the risk capital allocated for trading rather than total net worth. Risk management configuration adapts to your specific trading approach. The stop loss setting should be enabled if you employ fixed stop-loss exits, with the stop loss distance specified in appropriate units depending on the asset class. For stocks, this distance is measured in dollars, for forex in pips, and for futures in ticks. When stop losses are not used, the maximum strategy drawdown percentage from your backtest provides the risk assessment baseline. Kelly mode selection offers three primary approaches: Full Kelly for aggressive growth with higher volatility suitable for experienced practitioners, Half Kelly for balanced risk-return optimization popular among professional traders, and Quarter Kelly for conservative approaches with reduced volatility. Display customization ensures optimal integration with your trading environment. Eight professional color themes provide optimization for different chart backgrounds and personal preferences. Table position selection allows optimal placement within your chart layout, while table size adjustment ensures readability across different screen resolutions and viewing preferences. Detailed Practical Examples Example 1: SPY Swing Trading Strategy Consider a professionally developed swing trading strategy for SPY (S&P 500 ETF) with backtesting results spanning 166 total trades. The strategy achieved 110 winning trades, representing a 66.3% win rate, with an average winning trade of $2,200 and average losing trade of $862. The maximum drawdown reached 31.4% during the testing period, and the available trading capital amounts to $25,000. This strategy employs discretionary exits without fixed stop losses. Implementation requires loading the calculator on the SPY daily chart and configuring the parameters accordingly. The win rate input receives 66.3, while average win and loss inputs receive 2200 and 862 respectively. Total historical trades input requires 166, with account size set to 25000. The stop loss function remains disabled due to the discretionary exit approach, with maximum strategy drawdown set to 31.4%. Half Kelly mode provides the optimal balance between growth and risk management for this application. The calculator generates several key outputs for this scenario. The risk-reward ratio calculates automatically to 2.55, while the Kelly fraction reaches approximately 53% before scientific adjustments. Sample confidence achieves 100% given the 166 trades providing high statistical confidence. The recommended position settles at approximately 27% after Half Kelly and Bayesian adjustment factors. Position value reaches approximately $6,750, translating to 16 shares at a $420 SPY price. Risk per trade amounts to approximately $2,110, representing 31.4% of position value, with expected value per trade reaching approximately $1,466. This recommendation represents the mathematically optimal balance between growth potential and risk management for this specific strategy profile. Example 2: EURUSD Day Trading with Stop Losses A high-frequency EURUSD day trading strategy demonstrates different parameter requirements compared to swing trading approaches. This strategy encompasses 89 total trades with a 58% win rate, generating an average winning trade of $180 and average losing trade of $95. The maximum drawdown reached 12% during testing, with available capital of $10,000. The strategy employs fixed stop losses at 25 pips and take profit targets at 45 pips, providing clear risk-reward parameters. Implementation begins with loading the calculator on the EURUSD 1-hour chart for appropriate timeframe alignment. Parameter configuration includes win rate at 58, average win at 180, and average loss at 95. Total historical trades input receives 89, with account size set to 10000. The stop loss function is enabled with distance set to 25 pips, reflecting the fixed exit strategy. Quarter Kelly mode provides conservative positioning due to the smaller sample size compared to the previous example. Results demonstrate the impact of smaller sample sizes on Kelly calculations. The risk-reward ratio calculates to 1.89, while the Kelly fraction reaches approximately 32% before adjustments. Sample confidence achieves 89%, providing moderate statistical confidence given the 89 trades. The recommended position settles at approximately 7% after Quarter Kelly application and Bayesian shrinkage adjustment for the smaller sample. Position value amounts to approximately $700, translating to 0.07 standard lots. Risk per trade reaches approximately $175, calculated as 25 pips multiplied by lot size and pip value, with expected value per trade at approximately $49. This conservative position sizing reflects the smaller sample size, with position sizes expected to increase as trade count surpasses 100 and statistical confidence improves. Example 3: ES1! Futures Systematic Strategy Systematic futures trading presents unique considerations for Kelly criterion application, as demonstrated by an E-mini S&P 500 futures strategy encompassing 234 total trades. This systematic approach achieved a 45% win rate with an average winning trade of $1,850 and average losing trade of $720. The maximum drawdown reached 18% during the testing period, with available capital of $50,000. The strategy employs 15-tick stop losses with contract specifications of $50 per tick, providing precise risk control mechanisms. Implementation involves loading the calculator on the ES1! 15-minute chart to align with the systematic trading timeframe. Parameter configuration includes win rate at 45, average win at 1850, and average loss at 720. Total historical trades receives 234, providing robust statistical foundation, with account size set to 50000. The stop loss function is enabled with distance set to 15 ticks, reflecting the systematic exit methodology. Half Kelly mode balances growth potential with appropriate risk management for futures trading. Results illustrate how favorable risk-reward ratios can support meaningful position sizing despite lower win rates. The risk-reward ratio calculates to 2.57, while the Kelly fraction reaches approximately 16%, lower than previous examples due to the sub-50% win rate. Sample confidence achieves 100% given the 234 trades providing high statistical confidence. The recommended position settles at approximately 8% after Half Kelly adjustment. Estimated margin per contract amounts to approximately $2,500, resulting in a single contract allocation. Position value reaches approximately $2,500, with risk per trade at $750, calculated as 15 ticks multiplied by $50 per tick. Expected value per trade amounts to approximately $508. Despite the lower win rate, the favorable risk-reward ratio supports meaningful position sizing, with single contract allocation reflecting appropriate leverage management for futures trading. Example 4: MES1! Micro-Futures for Smaller Accounts Micro-futures contracts provide enhanced accessibility for smaller trading accounts while maintaining identical strategy characteristics. Using the same systematic strategy statistics from the previous example but with available capital of $15,000 and micro-futures specifications of $5 per tick with reduced margin requirements, the implementation demonstrates improved position sizing granularity. Kelly calculations remain identical to the full-sized contract example, maintaining the same risk-reward dynamics and statistical foundations. However, estimated margin per contract reduces to approximately $250 for micro-contracts, enabling allocation of 4-5 micro-contracts. Position value reaches approximately $1,200, while risk per trade calculates to $75, derived from 15 ticks multiplied by $5 per tick. This granularity advantage provides better position size precision for smaller accounts, enabling more accurate Kelly implementation without requiring large capital commitments. Example 5: Bitcoin Swing Trading Cryptocurrency markets present unique challenges requiring modified Kelly application approaches. A Bitcoin swing trading strategy on BTCUSD encompasses 67 total trades with a 71% win rate, generating average winning trades of $3,200 and average losing trades of $1,400. Maximum drawdown reached 28% during testing, with available capital of $30,000. The strategy employs technical analysis for exits without fixed stop losses, relying on price action and momentum indicators. Implementation requires conservative approaches due to cryptocurrency volatility characteristics. Quarter Kelly mode is recommended despite the high win rate to account for crypto market unpredictability. Expected position sizing remains reduced due to the limited sample size of 67 trades, requiring additional caution until statistical confidence improves. Regular parameter updates are strongly recommended due to cryptocurrency market evolution and changing volatility patterns that can significantly impact strategy performance characteristics. Advanced Usage Scenarios Portfolio position sizing requires sophisticated consideration when running multiple strategies simultaneously. Each strategy should have its Kelly fraction calculated independently to maintain mathematical integrity. However, correlation adjustments become necessary when strategies exhibit related performance patterns. Moderately correlated strategies should receive individual position size reductions of 10-20% to account for overlapping risk exposure. Aggregate portfolio risk monitoring ensures total exposure remains within acceptable limits across all active strategies. Professional practitioners often consider using lower fractional Kelly approaches, such as Quarter Kelly, when running multiple strategies simultaneously to provide additional safety margins. Parameter sensitivity analysis forms a critical component of professional Kelly implementation. Regular validation procedures should include monthly parameter updates using rolling 100-trade windows to capture evolving market conditions while maintaining statistical relevance. Sensitivity testing involves varying win rates by ±5% and average win/loss ratios by ±10% to assess recommendation stability under different parameter assumptions. Out-of-sample validation reserves 20% of historical data for parameter verification, ensuring that optimization doesn't create curve-fitted results. Regime change detection monitors actual performance against expected metrics, triggering parameter reassessment when significant deviations occur. Risk management integration requires professional overlay considerations beyond pure Kelly calculations. Daily loss limits should cease trading when daily losses exceed twice the calculated risk per trade, preventing emotional decision-making during adverse periods. Maximum position limits should never exceed 25% of account value in any single position regardless of Kelly recommendations, maintaining diversification principles. Correlation monitoring reduces position sizes when holding multiple correlated positions that move together during market stress. Volatility adjustments consider reducing position sizes during periods of elevated VIX above 25 for equity strategies, adapting to changing market conditions. Troubleshooting and Optimization Professional implementation often encounters specific challenges requiring systematic troubleshooting approaches. Zero position size displays typically result from insufficient capital for minimum position sizes, negative expected values, or extremely conservative Kelly calculations. Solutions include increasing account size, verifying strategy statistics for accuracy, considering Quarter Kelly mode for conservative approaches, or reassessing overall strategy viability when fundamental issues exist. Extremely high Kelly fractions exceeding 50% usually indicate underlying problems with parameter estimation. Common causes include unrealistic win rates, inflated risk-reward ratios, or curve-fitted backtest results that don't reflect genuine trading conditions. Solutions require verifying backtest methodology, including all transaction costs in calculations, testing strategies on out-of-sample data, and using conservative fractional Kelly approaches until parameter reliability improves. Low sample confidence below 50% reflects insufficient historical trades for reliable parameter estimation. This situation demands gathering additional trading data, using Quarter Kelly approaches until reaching 100 or more trades, applying extra conservatism in position sizing, and considering paper trading to build statistical foundations without capital risk. Inconsistent results across similar strategies often stem from parameter estimation differences, market regime changes, or strategy degradation over time. Professional solutions include standardizing backtest methodology across all strategies, updating parameters regularly to reflect current conditions, and monitoring live performance against expectations to identify deteriorating strategies. Position sizes that appear inappropriately large or small require careful validation against traditional risk management principles. Professional standards recommend never risking more than 2-3% per trade regardless of Kelly calculations. Calibration should begin with Quarter Kelly approaches, gradually increasing as comfort and confidence develop. Most institutional traders utilize 25-50% of full Kelly recommendations to balance growth with prudent risk management. Market condition adjustments require dynamic approaches to Kelly implementation. Trending markets may support full Kelly recommendations when directional momentum provides favorable conditions. Ranging or volatile markets typically warrant reducing to Half or Quarter Kelly to account for increased uncertainty. High correlation periods demand reducing individual position sizes when multiple positions move together, concentrating risk exposure. News and event periods often justify temporary position size reductions during high-impact releases that can create unpredictable market movements. Performance monitoring requires systematic protocols to ensure Kelly implementation remains effective over time. Weekly reviews should compare actual versus expected win rates and average win/loss ratios to identify parameter drift or strategy degradation. Position size efficiency and execution quality monitoring ensures that calculated recommendations translate effectively into actual trading results. Tracking correlation between calculated and realized risk helps identify discrepancies between theoretical and practical risk exposure. Monthly calibration provides more comprehensive parameter assessment using the most recent 100 trades to maintain statistical relevance while capturing current market conditions. Kelly mode appropriateness requires reassessment based on recent market volatility and performance characteristics, potentially shifting between Full, Half, and Quarter Kelly approaches as conditions change. Transaction cost evaluation ensures that commission structures, spreads, and slippage estimates remain accurate and current. Quarterly strategic reviews encompass comprehensive strategy performance analysis comparing long-term results against expectations and identifying trends in effectiveness. Market regime assessment evaluates parameter stability across different market conditions, determining whether strategy characteristics remain consistent or require fundamental adjustments. Strategic modifications to position sizing methodology may become necessary as markets evolve or trading approaches mature, ensuring that Kelly implementation continues supporting optimal capital allocation objectives. Professional Applications This calculator serves diverse professional applications across the financial industry. Quantitative hedge funds utilize the implementation for systematic position sizing within algorithmic trading frameworks, where mathematical precision and consistent application prove essential for institutional capital management. Professional discretionary traders benefit from optimized position management that removes emotional bias while maintaining flexibility for market-specific adjustments. Portfolio managers employ the calculator for developing risk-adjusted allocation strategies that enhance returns while maintaining prudent risk controls across diverse asset classes and investment strategies. Individual traders seeking mathematical optimization of capital allocation find the calculator provides institutional-grade methodology previously available only to professional money managers. The Kelly Criterion establishes theoretical foundation for optimal capital allocation across both single strategies and multiple trading systems, offering significant advantages over arbitrary position sizing methods that rely on intuition or fixed percentage approaches. Professional implementation ensures consistent application of mathematically sound principles while adapting to changing market conditions and strategy performance characteristics. Conclusion The Kelly Criterion represents one of the few mathematically optimal solutions to fundamental investment problems. When properly understood and carefully implemented, it provides significant competitive advantage in financial markets. This calculator implements modern refinements to Kelly's original formula while maintaining accessibility for practical trading applications. Success with Kelly requires ongoing learning, systematic application, and continuous refinement based on market feedback and evolving research. Users who master Kelly principles and implement them systematically can expect superior risk-adjusted returns and more consistent capital growth over extended periods. The extensive academic literature provides rich resources for deeper study, while practical experience builds the intuition necessary for effective implementation. Regular parameter updates, conservative approaches with limited data, and disciplined adherence to calculated recommendations are essential for optimal results. References Archer, M. D. (2010). Getting Started in Currency Trading: Winning in Today's Forex Market (3rd ed.). John Wiley & Sons. Baker, R. D., & McHale, I. G. (2012). An empirical Bayes approach to optimising betting strategies. Journal of the Royal Statistical Society: Series D (The Statistician), 61(1), 75-92. Breiman, L. (1961). Optimal gambling systems for favorable games. In J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability (pp. 65-78). University of California Press. Brown, D. B. (1976). Optimal portfolio growth: Logarithmic utility and the Kelly criterion. In W. T. Ziemba & R. G. Vickson (Eds.), Stochastic Optimization Models in Finance (pp. 1-23). Academic Press. Browne, S., & Whitt, W. (1996). Portfolio choice and the Bayesian Kelly criterion. Advances in Applied Probability, 28(4), 1145-1176. Estrada, J. (2008). Geometric mean maximization: An overlooked portfolio approach? The Journal of Investing, 17(4), 134-147. Hakansson, N. H., & Ziemba, W. T. (1995). Capital growth theory. In R. A. Jarrow, V. Maksimovic, & W. T. Ziemba (Eds.), Handbooks in Operations Research and Management Science (Vol. 9, pp. 65-86). Elsevier. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. Kaufman, P. J. (2013). Trading Systems and Methods (5th ed.). John Wiley & Sons. Kelly Jr, J. L. (1956). A new interpretation of information rate. Bell System Technical Journal, 35(4), 917-926. Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton University Press. MacLean, L. C., Sanegre, E. O., Zhao, Y., & Ziemba, W. T. (2004). Capital growth with security. Journal of Economic Dynamics and Control, 28(4), 937-954. MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific. Michaud, R. O. (1989). The Markowitz optimization enigma: Is 'optimized' optimal? Financial Analysts Journal, 45(1), 31-42. Pabrai, M. (2007). The Dhandho Investor: The Low-Risk Value Method to High Returns. John Wiley & Sons. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423. Tharp, V. K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill. Thorp, E. O. (2006). The Kelly criterion in blackjack sports betting, and the stock market. In L. C. MacLean, E. O. Thorp, & W. T. Ziemba (Eds.), The Kelly Capital Growth Investment Criterion: Theory and Practice (pp. 789-832). World Scientific. Van Tharp, K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill Education. Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons. Vince, R., & Zhu, H. (2015). Optimal betting under parameter uncertainty. Journal of Statistical Planning and Inference, 161, 19-31. Ziemba, W. T. (2003). The Stochastic Programming Approach to Asset, Liability, and Wealth Management. The Research Foundation of AIMR. Further Reading For comprehensive understanding of Kelly Criterion applications and advanced implementations: MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific. Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons. Thorp, E. O. (2017). A Man for All Markets: From Las Vegas to Wall Street. Random House. Cover, T. M., & Thomas, J. A. (2006). Elements of Information Theory (2nd ed.). John Wiley & Sons. Ziemba, W. T., & Vickson, R. G. (Eds.). (2006). Stochastic Optimization Models in Finance. World Scientific.
Indicatore Pine Script®
di EdgeTools
Quant Signals: Entropy w/ ForecastThis is the first of many quantitative signals I plan to create for TV users. Most technical analysis (TA) tools—like moving averages, oscillators, or chart patterns—are heuristic: they’re based on visually identifiable shapes, threshold crossovers, or empirically chosen rules. These methods rarely quantify the information content or structural complexity of market data. By quantifying market predictability before making a forecast, this method filters out noise and focuses your trading only during statistically favorable conditions—something traditional TA cannot objectively measure. This MEPP-based approach is quantitative and model-free: It comes from information theory and measures Shannon entropy rate to assess how predictable the market is at any moment. Instead of interpreting price formations, it uses a data-compression algorithm (Lempel–Ziv) to capture hidden structure in the sequence of returns. Forecasts are generated using a principle from statistical physics (Maximum Entropy Production), not historical chart patterns. In short, this method measures the market's predictability BEFORE deciding a directional forecast is worth trusting. This tool is to inform TA traders on the market's current regime, whether it is smooth and predictable or it is volatile and turbulent. Technical Introduction: In information theory, Shannon entropy measures the uncertainty (or information content) in a sequence of data. For markets, the entropy rate captures how much new information price returns generate over time: Low entropy rate → price changes are more structured and predictable. High entropy rate → price changes are more random and unpredictable. By discretizing recent returns into quartile-based states, this indicator: Calculates the normalized entropy rate as a regime filter. Uses MEPP to forecast the next state that maximizes entropy production. Displays both the regime status (predictable vs chaotic) and the forecast bias (bullish/bearish) in a dashboard. Measurements & How to Use Them TLDR: HIGH ENTROPY -> information generation/market shift -> Don't trust forecast/strategy 1. H (bits/sym) Shannon entropy rate of the last μ discrete returns, in bits per symbol (0–2). Lower → more predictable; higher → more random. Use as a raw measure of market structure. 2. H_max (log₂Ω) Theoretical maximum entropy for Ω states. Here Ω = 4 → H_max = 2.0 bits. Reference value for normalization. 3. Entropy (norm) H / H_max, scaled between 0 and 1. < 0.5–0.6 → predictable regime; > 0.6 → chaotic regime. Main regime filter — forecasts are more reliable when below your threshold. 4. Regime Label based on Entropy (norm) vs your entThresh. LOW (predictable) = higher odds forecast will be correct. HIGH (chaotic) = forecasts less reliable. 5. Next State (MEPP Forecast) Discrete return state (1–4) predicted to occur next, chosen to maximize entropy production: Large Down (strong bearish) Small Down (mild bearish) Small Up (mild bullish) Large Up (strong bullish) Use as your bias direction. 6. Bias Simplified label from the Next State: States 1–2 = Bearish bias (red) States 3–4 = Bullish bias (green) Align strategy direction with bias only in LOW regime.
Indicatore Pine Script®
di Faduzzle
Clean Multi-Indicator Alignment System Overview A sophisticated multi-indicator alignment system designed for 24/7 trading across all markets, with pure signal-based exits and no time restrictions. Perfect for futures, forex, and crypto markets that operate around the clock. Key Features 🎯 Multi-Indicator Confluence System EMA Cross Strategy: Fast EMA (5) and Slow EMA (10) for precise trend direction VWAP Integration: Institution-level price positioning analysis RSI Momentum: 7-period RSI for momentum confirmation and reversal detection MACD Signals: Optimized 8/17/5 configuration for scalping responsiveness Volume Confirmation: Customizable volume multiplier (default 1.6x) for signal validation 🚀 Advanced Entry Logic Initial Full Alignment: Requires all 5 indicators + volume confirmation Smart Continuation Entries: EMA9 pullback entries when trend momentum remains intact Flexible Time Controls: Optional session filtering or 24/7 operation 🎪 Pure Signal-Based Exits No Forced Closes: Positions exit only on technical signal reversals Dual Exit Conditions: EMA9 breakdown + RSI flip OR MACD cross + EMA20 breakdown Trend Following: Allows profitable trends to run their full course Perfect for Swing Scalping: Ideal for multi-session position holding 📊 Visual Interface Real-Time Status Dashboard: Live alignment monitoring for all indicators Color-Coded Candles: Instant visual confirmation of entry/exit signals Clean Chart Display: Toggle-able EMAs and VWAP with professional styling Signal Differentiation: Clear labels for entries, X-crosses for exits 🔔 Alert System Entry Notifications: Separate alerts for buy/sell signals Exit Warnings: Technical breakdown alerts for position management Mobile Ready: Push notifications to TradingView mobile app Market Applications Perfect For: Gold Futures (GC): 24-hour precious metals trading NASDAQ Futures (NQ): High-volatility index scalping Forex Markets: Currency pairs with continuous operation Crypto Trading: 24/7 cryptocurrency momentum plays Energy Futures: Oil, gas, and commodity swing trades Optimal Timeframes: 1-5 Minutes: Ultra-fast scalping during high volatility 5-15 Minutes: Balanced approach for most markets 15-30 Minutes: Swing scalping for trend following 🧠 Smart Position Management Tracks implied position direction Prevents conflicting signals Allows trend continuation entries State-aware exit logic ⚡ Scalping Optimized Fast-reacting indicators with shorter periods Volume-based confirmation reduces false signals Clean entry/exit visualization Minimal lag for time-sensitive trades Configuration Options All parameters fully customizable: EMA Lengths: Adjustable from 1-30 periods RSI Period: 1-14 range for different market conditions MACD Settings: Fast (1-15), Slow (1-30), Signal (1-10) Volume Confirmation: 0.5-5.0x multiplier range Visual Preferences: Colors, displays, and table options Risk Management Features Clear visual exit signals prevent emotion-based decisions Volume confirmation reduces false breakouts Multi-indicator confluence improves signal quality Optional time filtering for session-specific strategies Best Use Cases Futures Scalping: NQ, ES, GC during active sessions Forex Swing Trading: Major pairs during overlap periods Crypto Momentum: Bitcoin, Ethereum trend following 24/7 Automated Systems: Algorithmic trading implementation Multi-Market Scanning: Portfolio-wide signal monitoring
Indicatore Pine Script®
di Fizeks
1
Dynamic Swing Anchored VWAP (Zeiierman)█ Overview Dynamic Swing Anchored VWAP (Zeiierman) is a price–volume tool that anchors VWAP at fresh swing highs/lows and then adapts its responsiveness as conditions change. Instead of one static VWAP that drifts away over time, this indicator re-anchors at meaningful structure points (swings). It computes a decayed, volume-weighted average that can speed up in volatile markets and slow down during quiet periods. Blending swing structure with an adaptive VWAP engine creates a fair-value path that stays aligned with current price behavior, making retests, pullbacks, and mean reversion opportunities easier to spot and trade. █ How It Works ⚪ Swing Anchor Engine The script scans for swing highs/lows using your Swing Period. When market direction flips (new pivot confirmed), the indicator anchors a new VWAP at that pivot and starts tracking from there. ⚪ Adaptive VWAP Core From each anchor , VWAP is computed using a decay model (recent price×volume matters more; older data matters less). Adaptive Price Tracking lets you set the base responsiveness in “bars.” Lower = more reactive, higher = smoother. Volatility Adjustment (ATR vs Avg ATR) can automatically speed up the VWAP during spikes and slow it during compression, so the line stays relevant to live conditions. █ Why This Adaptive Approach Beats a Simple VWAP Standard VWAP is cumulative from the anchor point. As time passes and volume accumulates, it often drifts far from current price, especially in prolonged trends or multi-session moves. That drift makes retests rare and unreliable. Dynamic Swing Anchored VWAP solves this in two ways: ⚪ Event-Driven Anchoring (Swings): By restarting at fresh swing highs/lows, the VWAP reference reflects today’s structure. You get frequent, meaningful retests because the anchor stays near the action. ⚪ Adaptive Responsiveness (Volatility-Aware): Markets don’t move at one speed. When volatility expands, a fixed VWAP lags; when volatility contracts, it can overreact to noise. Here, the “tracking speed” can auto-adjust using ATR vs its average. High Volatility → faster tracking: VWAP hugs price more tightly, preserving retest relevance. Low Volatility → smoother tracking: VWAP filters chop and stays stable. Result: A VWAP that follows price more accurately, creating plenty of credible retest opportunities and more trustworthy mean-reversion/continuation reads than a simple, ever-growing VWAP. █ How to Use ⚪ S wing-Aware Fair Value Use the VWAP as a dynamic fair-value guide that restarts at key structural pivots. Pullbacks to the VWAP after impulsive moves often provide retest entries. ⚪ Trend Trading In trends, the adaptive VWAP will ride closer to price, offering continuation pullbacks. █ Settings Swing Period: Number of bars to confirm swing highs/lows. Larger = bigger, cleaner pivots (slower); smaller = more frequent pivots (noisier). Adaptive Price Tracking: Sets the base reaction speed (in bars). Lower = faster, tighter to price; higher = smoother, slower. Adapt APT by ATR ratio: When ON, the tracking speed auto-adjusts with market volatility (ATR vs its own average). High vol → faster; low vol → calmer. Volatility Bias: Controls how strongly volatility affects the speed. >1 = stronger effect; <1 = lighter touch. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicatore Pine Script®
di Zeiierman
48
BuySell-byALHELWANI🔱 BuySell-byALHELWANI | مؤشر التغيرات الاتجاهية الذكية BuySell-byALHELWANI هو مؤشر احترافي متقدّم يرصد نقاط الانعكاس الحقيقية في حركة السوق، باستخدام خوارزمية تعتمد على تحليل القمم والقيعان الهيكلية للسعر (Structure-Based Detection) وليس على مؤشرات تقليدية. المؤشر مبني على مكتبة signalLib_yashgode9 القوية، مع تخصيص كامل لأسلوب العرض والتنبيهات. ⚙️ ما يقدمه المؤشر: 🔹 إشارات واضحة للشراء والبيع تعتمد على كسر هيكل السوق. 🔹 تخصيص مرن للعمق والانحراف وخطوات التراجع (Backstep) لتحديد الدقة المطلوبة. 🔹 علامات ذكية (Labels) تظهر مباشرة على الشارت عند كل نقطة قرار. 🔹 تنبيهات تلقائية فورية عند كل تغير في الاتجاه (Buy / Sell). 🧠 الآلية المستخدمة: DEPTH_ENGINE: يتحكم في مدى عمق النظر لحركة السعر. DEVIATION_ENGINE: يحدد المسافة المطلوبة لتأكيد نقطة الانعكاس. BACKSTEP_ENGINE: يضمن أن كل إشارة تستند إلى تغير هيكلي حقيقي في الاتجاه. 📌 المميزات: ✅ لا يعيد الرسم (No Repaint) ✅ يعمل على كل الأطر الزمنية وكل الأسواق (فوركس، مؤشرات، كريبتو، أسهم) ✅ تصميم بصري مرن (ألوان، حجم، شفافية) ✅ يدعم الاستخدام في السكالبينغ والسوينغ ملاحظة: المؤشر لا يعطي إشارات عشوائية، بل يستند إلى منطق السعر الحقيقي عبر تتبع التغيرات الحركية للسوق. يُفضّل استخدامه مع خطة تداول واضحة وإدارة رأس مال صارمة. 🔱 BuySell-byALHELWANI | Smart Reversal Detection Indicator BuySell-byALHELWANI is a high-precision, structure-based reversal indicator designed to identify true directional shifts in the market. Unlike traditional indicators, it doesn't rely on lagging oscillators but uses real-time swing analysis to detect institutional-level pivot points. Powered by the robust signalLib_yashgode9, this tool is optimized for traders who seek clarity, timing, and strategic control. ⚙️ Core Engine Features: 🔹 Accurate Buy/Sell signals generated from structural highs and lows. 🔹 Adjustable sensitivity using: DEPTH_ENGINE: Defines how deep the algorithm looks into past swings. DEVIATION_ENGINE: Sets the deviation required to confirm a structural change. BACKSTEP_ENGINE: Controls how many bars are validated before confirming a pivot. 🧠 What It Does: 🚩 Detects market structure shifts and confirms them visually. 🏷️ Plots clear Buy-point / Sell-point labels directly on the chart. 🔔 Sends real-time alerts when a directional change is confirmed. 🎯 No repainting – what you see is reliable and final. ✅ Key Benefits: Works on all timeframes and all asset classes (FX, crypto, indices, stocks). Fully customizable: colors, label size, transparency. Ideal for scalping, swing trading, and strategy automation. High visual clarity with minimal noise. 🔐 Note: This script is designed for serious traders. It highlights real market intent, especially when used with trendlines, zones, and volume analysis. Pair it with disciplined risk management for best results.
Indicatore Pine Script®
di mohamad-alhelwani
4
Repulse OB/OS Z-Score Repulse OB/OS Z-Score (v6) is an advanced oscillator that measures market momentum and potential exhaustion zones using the Repulse algorithm. The indicator applies double smoothing (customizable EMA) to highlight bullish and bearish power, and automatically marks overbought (+100), oversold (–100), and neutral (0) regions. The core feature is a custom Z-Score mapping of the Repulse oscillator: – Z-Score quantifies where Repulse stands between strong bullish and bearish extremes (from +3 to –3), interpolating smoothly between levels (e.g., 0, ±1, ±2, ±3) for easier interpretation of market state. – The colored Repulse line visually confirms current direction and momentum shifts. Customize the Repulse period and smoothing multiplier for your timeframe or asset. Usage: Look for Z-Score readings near ±2 or ±3 for strong overbought/oversold signals. Watch for reversals as the Z-Score crosses 0 or leaves extreme regions. Combine with price action or other indicators for best results.
Indicatore Pine Script®
di S0905B
SMC Structure IndicatorTitle: SMC Structures Indicator Description: The SMC Structures indicator is a powerful tool designed to identify and visualize key structural elements in price action, based on the principles of Smart Money Concepts (SMC). This indicator helps traders identify potential areas of support, resistance, and price reversals by highlighting significant market structures. Key Features: Structure Identification: The indicator automatically detects and marks important high and low structures in the market. Break of Structure (BOS) Detection: It identifies and labels instances where previous structures are broken, indicating potential trend changes or continuations. Change of Character (CHoCH) Detection: The indicator recognizes and marks Changes of Character, which are significant shifts in market behavior. Customizable Visuals: Users can personalize the appearance of BOS and CHoCH markings, including colors, line styles, and widths. Current Structure Display: The indicator can optionally show the current active structure, helping traders understand the immediate market context. Historical Structure Tracking: Users can specify the number of historical structure breaks to display, allowing for a cleaner chart while maintaining relevant information. Flexible Break Confirmation: The indicator offers the option to confirm structure breaks using either the candle body or wick, accommodating different trading styles. Technical Details: The indicator uses advanced algorithms to identify significant price structures based on local highs and lows. It employs a lookback period of 10 bars for structure detection, ensuring relevance to current market conditions. The code includes safeguards to handle different market phases and avoid false signals during ranging periods. Customization Options: Colors for Bullish and Bearish BOS and CHoCH markings Line styles and widths for all structure markings Number of historical breaks to display Option to show or hide the current active structure Choice between candle body or wick for structure break confirmation Use Cases: Trend Analysis: Identify the start of new trends or potential trend reversals. Support and Resistance: Pinpoint key levels where price may react. Trade Entry and Exit: Use structure breaks as potential entry or exit signals. Market Context: Understand the broader market structure to make informed trading decisions.
Indicatore Pine Script®
di kylemorton494
Cumulative Volume Delta (SB-1) 2.0 📈 Cumulative Volume Delta (CVD) — Stair-Step + Threshold Alerts 🔍 Overview This Cumulative Volume Delta (CVD) tool visualizes aggressive buying and selling pressure in the market by plotting candlestick-style bars based on volume delta. It helps traders understand which side — buyers or sellers — is exerting more control on lower timeframes and highlights momentum shifts through stair-step patterns and delta threshold breaks. Resets to zero at EOD Ideal for futures traders, scalpers, and intraday strategists looking for orderflow-based confirmation. 🧠 What Is CVD? CVD (Cumulative Volume Delta) measures the difference between market buys and sells over a specific timeframe. When the delta is rising, it suggests buyers are being more aggressive. Falling delta suggests seller dominance. This script aggregates volume delta from a lower timeframe and plots it in a higher timeframe context, allowing you to track microstructure shifts within larger candles. 📊 Features ✅ CVD Candlesticks Each bar represents volume delta as an OHLC-style candle using: Open: Delta at the start of the bar High/Low: Peak delta range Close: Final delta value at bar close Teal candles = Net buying pressure Red candles = Net selling pressure ✅ Threshold Levels (Key Visual Zones) The script includes horizontal dashed lines at: +5,000 and +10,000 → Signify strong buying pressure -5,000 and -10,000 → Signify strong selling pressure 0 line → Neutrality line (no net pressure) These levels act as volume-based support/resistance zones and breakout confirmation tools. For example: A CVD cross above +5,000 shows buyers taking control A CVD cross above +10,000 implies strong bullish momentum A CVD cross below -5,000 or -10,000 signals intense selling pressure 📈 Stair-Step Pattern Detection Detects two specific volume-based continuation setups: Bullish Stair-Step: Both the high and low of the CVD candle are higher than the previous candle Bearish Stair-Step: Both the high and low of the CVD candle are lower than the previous candle These patterns often appear during trending moves and serve as confirmation of strength or continuation. Visual markers: 🟢 Green triangles below bars = Bullish stair-step 🔴 Red triangles above bars = Bearish stair-step 🔔 Alert Conditions Get real-time alerts when: Bullish Stair-Step is detected Bearish Stair-Step is detected CVD crosses above +5,000 CVD crosses below -5,000 📢 Alerts only trigger on crossover, not every time CVD remains above or below. This avoids repetitive notifications. ⚙️ Inputs & Customization Anchor Timeframe: The higher timeframe to which CVD data is applied (default: 1D) Lower Timeframe: The timeframe used to calculate the CVD delta (default: 5 minutes) Optional Override: Use custom timeframe toggle to force your own micro timeframe 📌 How to Use This CVD Indicator (Step-by-Step Guide) ✅ 1. Confirm Bias Using the Zero Line The zero line (0 CVD) represents neutral pressure — neither buyers nor sellers are dominating. Use it as your first filter: 🔼 If CVD is above 0 and rising → Buyer control 🔽 If CVD is below 0 and falling → Seller control 🧠 Tip: CVD rising while price is consolidating may signal hidden buyer interest. ✅ 2. Watch for Crosses of Key Levels: +5,000 and +10,000 These levels act as momentum thresholds: Level Signal Type What It Means +5,000 Buyer breakout Buyers are starting to dominate +10,000 Strong bull bias Strong institutional or algorithmic buying flow -5,000 Seller breakout Sellers are taking control -10,000 Strong bear bias Heavy selling pressure is entering the market Wait for CVD to cross above +5K or below -5K to confirm the active side. Use these crossovers as entry triggers, breakout confirmations, or trade filters. 🔔 Alerts fire only when the level is first crossed, not every bar above/below. ✅ 3. Use Stair-Step Patterns for Continuation Confirmation The indicator shows stair-step patterns using triangle signals: 🟢 Green triangle below bar = Bullish stair-step Suggests a higher high and higher low in delta → buyers stepping up 🔴 Red triangle above bar = Bearish stair-step Suggests lower highs and lower lows in delta → selling pressure building Use stair-step signals: To confirm a continuation of trend As an entry or add-on signal Especially after a threshold breakout 🧠 Example: If CVD breaks above +5K and forms bullish stairs → confirms strong trend, ideal for momentum entries. ✅ 4. Combine with Price Action or Structure CVD works best when used with price, not in isolation. For example: 📉 Price makes a new low but CVD doesn’t → potential bullish divergence 📈 CVD surges while price lags → buyers are absorbing, breakout likely Use it with: VWAP Orderblocks Liquidity sweeps Break of market structure/MSS/BOS ✅ 5. Set Anchor Timeframe = Daily Set Lower Timeframe = 5 minutes (default) This lets you: See intraday flow inside daily bars Confirm whether a daily candle is being built on net buying or selling 🧠 You’re essentially seeing intra-bar aggression within a bigger time structure. 🧭 Example Trading Setup Bullish Scenario: CVD is rising and above 0 CVD crosses above +5,000 → alert fires Green stair-step appears Price breaks local resistance or liquidity sweep completes ✅ Consider long entry with structure and CVD alignment 🎯 Place stops below last stair-step or structural low 📌 Final Notes This tool does not repaint and is designed to work in real-time across all futures, crypto, and equity instruments that support volume data. If your symbol does not provide volume, the script will notify you. Use it in confluence with VWAP, liquidity zones, or structure breaks for high-confidence trades.
Indicatore Pine Script®
di samb817
Smooth Cloud + RSI Liquidity Spectrum + Zig Zag Volume ProfileSmooth Cloud + RSI Liquidity Spectrum + Zig Zag++ Volume Profile" Indicator | Advanced Trend & Liquidity Analysis. --- 📌 Key Features & Enhancements (Zig Zag++) This advanced indicator combines **trend-following moving averages, RSI momentum with liquidity factors, and an improved Zig Zag++ algorithm with volume profiling** for precise swing detection. 🔹 Zig Zag++ Upgrades: ✅ **Dynamic Reversal Detection** – Adapts to volatility using percentage-based pivots. ✅ **Volume-Weighted Swing Points** – Highlights high-liquidity turning points. ✅ **Multi-Timeframe Confirmation** – Uses historical pivots for stronger signals. ✅ **Volume Profile Clustering** – Reveals key support/resistance zones based on traded volume. --- 📊 Indicator Components Breakdown 1️⃣ Smooth Cloud (Trend Filter) - **Fast MA (20-period) & Slow MA (50-period)** – Configurable as EMA, SMA, or WMA. - **Cloud Coloring** – Green when fast MA > slow MA (bullish), red otherwise (bearish). - **Purpose**: Acts as a trend filter—only take trades in the direction of the cloud. 2️⃣ RSI Liquidity Spectrum (Momentum + Volume) - **RSI (14-period default)** – Standard momentum oscillator. - **Liquidity-Adjusted Momentum** = `(RSI + ROC(RSI,3)) * (Volume / SMA(Volume, RSI Length))` - **Purpose**: Identifies overbought/oversold conditions with volume confirmation (high volume = stronger signal). 3️⃣ Zig Zag++ (Swing Detection & Volume Profiling) 📈 Zig Zag Logic:** - **Percentage-Based Reversals** (default: 5%) – Only plots swings exceeding this threshold. - **Pivot Tracking** – Stores price & bar index of each swing point in arrays. - **Dynamic Line Drawing** – Connects swing points with yellow trendlines. 📊 Volume Profile at Swings: - **Lookback Period** (200 bars default) – Analyzes volume distribution between Zig Zag turns. - **10-Price Bin Clustering** – Splits the price range into 10 levels and calculates traded volume at each. - **Transparency Scaling** – Higher volume zones appear darker (stronger support/resistance). --- 🎯 Step-by-Step Trading Strategies 📈 Strategy 1: Trend-Following with RSI Liquidity Confirmation** 1. **Enter Long** when: - Smooth Cloud is **green** (fast MA > slow MA). - RSI Liquidity Momentum crosses above **30** (bullish momentum + volume). - Price pulls back to the **Volume Profile high-volume zone** (demand area). 2. **Enter Short** when: - Smooth Cloud is **red** (fast MA < slow MA). - RSI Liquidity Momentum crosses below **70** (bearish momentum + volume). - Price rallies into the **Volume Profile high-volume zone** (supply area). 3. **Exit** when: - Zig Zag++ detects a new reversal (5% move against position). - RSI Liquidity Momentum crosses back mid-level (50). --- 📉 Strategy 2: Swing Trading with Zig Zag++ Pivots** 1. **Buy at Swing Lows** when: - Zig Zag++ prints a **higher low** (bullish structure). - Volume Profile shows **strong absorption** (high volume at the low). - RSI Liquidity Momentum is rising from oversold (<30). 2. **Sell at Swing Highs** when: - Zig Zag++ prints a **lower high** (bearish structure). - Volume Profile shows **distribution** (high volume at the top). - RSI Liquidity Momentum is falling from overbought (>70). 3. **Stop Loss**: - Below the recent Zig Zag low (for longs). - Above the recent Zig Zag high (for shorts). --- 📌 Additional Enhancements (Pro Tips)** - **Combine with Higher Timeframe (HTF) Cloud** – Use a 4H/1D cloud to filter trades. - **Divergence Detection** – Hidden bullish/bearish divergences between Zig Zag & RSI Liquidity. - **Volume Spike Confirmation** – Only trade if volume exceeds SMA(volume, 20) at reversal points. --- 🚀 Conclusion This **all-in-one indicator** provides: ✔ **Trend direction** (Smooth Cloud) ✔ **Momentum + Liquidity strength** (RSI Spectrum) ✔ **Precise swing points** (Zig Zag++) ✔ **Volume-based S/R zones** (Profile Clustering) Best used on **15M-4H timeframes** for swing/day trading. Adjust parameters based on asset volatility.
Indicatore Pine Script®
di Markking77
2
SuperTrend Strategy with Trend-Based Exits🟩 SuperTrend Strategy with Trend-Based Exits This is a fully automated trend-following strategy based on the popular SuperTrend indicator, enhanced with a position sizing algorithm tied to stop-loss distance and dynamic entry/exit rules. The strategy is designed for futures trading with an emphasis on sustainable risk, realistic backtesting, and transparent logic. 🧠 Concept and Methodology The strategy uses the SuperTrend indicator, which is derived from ATR (Average True Range) and is widely used to capture medium- to long-term market trends. Key features: ✅ Entries are triggered only when the SuperTrend direction changes (trend reversal). ✅ Exits are performed using a dynamic stop-loss placed at the SuperTrend line. ✅ Position size is automatically calculated based on the trader’s fixed dollar risk per trade and the current distance to the stop-loss. ✅ Rounding logic is included to ensure quantity is valid for the exchange’s lot size. This strategy does not use any take-profit or classic trailing stop — the position is only closed when the trend reverses or the stop is hit by touching the SuperTrend line. ⚙️ Default Parameters ATR Length: 300 Factor: 7.5 Risk per trade: $90 (3% of the default $3,000 capital) Lot step: 10 Commission: 0.05% These default parameters are not universal. They were optimized specifically for STXUSDT swap at 15M timeframe at Bybit and may not produce viable results on other pairs and timeframes. Users are encouraged to customize the settings according to specific asset’s volatility, timeframe and other characteristics. ❗ These default settings yield meaningful backtesting results on STXUSDT with a reasonable number of trades (105+) over 7-month period. If applied to other assets, results may vary significantly. 📈 Position Sizing Logic The strategy uses a dynamic position sizing formula: Pine Script® position_size = floor((risk_per_trade / stop_loss_distance) / lot_step) * lot_step This ensures the trader always risks a fixed dollar amount per trade and never exceeds a sustainable equity exposure (recommended 2% or less). ✅ Realism in Backtesting To ensure realistic and non-misleading backtest results, this strategy includes: — Slippage and commission settings matching average exchange conditions (commission = 0.05%, slippage 5 ticks). — Position sizing based on stop-loss distance (not fixed contract quantity).* — A fixed risk-per-trade model that adheres to responsible capital management principles. — This is in compliance with TradingView's Script publishing rules and House Rules. 📌 How to Use Apply the strategy to a clean chart (preferably 15M for STXUSDT by default). If using another asset, adjust: - ATR Length - Factor - Risk per trade - Qty step (lot precision for the symbol) Avoid using with other indicators unless you understand their purpose. Use the Strategy Tester to evaluate performance and optimize parameters. ⚠️ Disclaimer This is not financial advice. Always perform forward testing and assess risk before deploying any strategy on live capital. The strategy is designed for educational and experimental use.
Strategia Pine Script®
di nefyodov.artyom
Helper Lib by tristanlee85Library "helpers" This library offers various functions and types based on the algorithmic concepts as authored by ICT. kv(key, value)   Returns a string of the key/value set, suitable for debug logging   Parameters:      key (string)      value (string)   Returns: A string formatted as "{key}: {value}" kv(key, value)   Parameters:      key (string)      value (int) kv(key, value)   Parameters:      key (string)      value (float) kv(key, value)   Parameters:      key (string)      value (bool) method enable(this, enable)   Enable/Disable debug logging   Namespace types: Debugger   Parameters:      this (Debugger)      enable (bool) : Set to `true` by default. method group(this, label)   Creates a group label for nested debug() invocations   Namespace types: Debugger   Parameters:      this (Debugger)      label (string) method groupEnd(this, label)   Ends the specified debug group   Namespace types: Debugger   Parameters:      this (Debugger)      label (string) method log(this, s, arg1, arg2, arg3, arg4, arg5)   Logs the param values if debug mode is enabled   Namespace types: Debugger   Parameters:      this (Debugger)      s (string) : Title of the log message      arg1 (string)      arg2 (string)      arg3 (string)      arg4 (string)      arg5 (string) method logIf(this, expr, s, arg1, arg2, arg3, arg4, arg5)   Same behavior as debug() except will only log if the passed expression is true   Namespace types: Debugger   Parameters:      this (Debugger)      expr (bool) : Boolean expression to determine if debug logs should be logged      s (string) : Title of the log message      arg1 (string)      arg2 (string)      arg3 (string)      arg4 (string)      arg5 (string) style_getLineStyleFromType(opt)   Returns the corresponding line style constant for the given LineStyleType   Parameters:      opt (series LineStyleType) : The selected line style type   Returns: The Pine Script line style constant style_getTextSizeFromType(opt)   Returns the corresponding text size constant for the given TextSizeType   Parameters:      opt (series TextSizeType) : The selected text size type   Returns: The Pine Script text size constant style_getTextHAlignFromType(t)   Returns the corresponding horizontal text align constant for the given HAlignType   Parameters:      t (series HAlignType) : The selected text align type   Returns: The Pine Script text align constant style_getTextVAlignFromType(t)   Returns the corresponding vertical text align constant for the given VAlignType   Parameters:      t (series VAlignType) : The selected text align type   Returns: The Pine Script text align constant format_sentimentType(sentiment, pd)   Used to produce a string with the sentiment and PD array type (e.g., "+FVG")   Parameters:      sentiment (series SentimentType) : The sentiment value (e.g., SentimentType.BULLISH)      pd (series PDArrayType) : The price data array (e.g., PDArrayType.FVG)   Returns: A formatted string with the sentiment and PD array (e.g., "+FVG") format_timeToString(timestamp)   Formats a UNIX timestamp into a date and time string based on predefined formats   Parameters:      timestamp (int) : The UNIX timestamp to format   Returns: A formatted string as "MM-dd (E) - HH:mm" method init(this)   Initializes the session and validates the configuration. This MUST be called immediately after creating a new instance.   Namespace types: Session   Parameters:      this (Session) : The Session object reference   Returns: The Session object (chainable) or throws a runtime error if invalid method isActive(this, _time)   Determines if the session is active based on the current bar time   Namespace types: Session   Parameters:      this (Session) : The Session object reference      _time (int)   Returns: `true` if the session is currently active; `false` otherwise method draw(this)   Draws the line and optional label   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference   Returns: The LineLabel object (chainable) method extend(this, x)   Extends the line and label right to the specified bar index   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference      x (int) : The bar index to extend to   Returns: The LineLabel object (chainable) method destroy(this)   Removes the line and label from the chart   Namespace types: LineLabel   Parameters:      this (LineLabel) : The LineLabel object reference isFVG(includeVI, barIdx)   Checks if the previous bars form a Fair Value Gap (FVG)   Parameters:      includeVI (bool) : If true, includes Volume Imbalance in the FVG calculation      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if a FVG is detected; otherwise, `na` isVolumeImbalance(barIdx)   Checks if the previous bars form a Volume Imbalance (VI)   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if a VI is detected; otherwise, `na` isLiquidityVoid(barIdx)   Checks if the previous bars form a Liquidity Void (LV)   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A Gap object if an LV is detected; otherwise, `na` isSwingPoint(barIdx)   Checks if the previous bars form a swing point   Parameters:      barIdx (int) : The index of the bar to check from (default is 0 for the current bar)   Returns: A SwingPoint object if a swing point is detected; otherwise, `na` Debugger   A debug logging utility with group support   Fields:      enabled (series bool)      _debugGroupStack (array) Session   Defines a trading session with a name and time range. When creating a new instance of this type, you MUST call init() immediately.   Fields:      name (series string) : A display-friendly name (e.g., "NY AM")      session (series string) : A string defining the session time range (e.g., "1300-1400")      enabled (series bool) : Optional flag for custom logic; defaults to false      start (series int) : UNIX time representing the session start (set via isActive())      end (series int) : UNIX time representing the session end (set via isActive())      _t (series int)      _start_HH (series float)      _start_mm (series float)      _end_HH (series float)      _end_mm (series float) Gap   Represents a price inefficiency (gap) with details on sentiment and price levels   Fields:      type (series SentimentType) : The sentiment of the gap (e.g., SentimentType.BULLISH)      name (series string) : A display-friendly name (e.g., "+FVG")      startTime (series int) : UNIX time value for the gap's start      endTime (series int) : UNIX time value for the gap's end      startIndex (series int) : Bar index where the gap starts      endIndex (series int) : Bar index where the gap ends      gapLow (series float) : The lowest price level of the gap      gapHigh (series float) : The highest price level of the gap      ce (series float) : The consequent encroachment level of the gap SwingPoint   Represents a swing point with details on type and price level   Fields:      type (series SwingPointType) : The type of swing point (e.g., SwingPointType.HIGH)      time (series int) : UNIX time value for the swing point      barIdx (series int) : Bar index where the swing point occurs      price (series float) : The price level of the swing point which is either the high or low of the middle bar LineLabel   Combines a line and box type to produce a line with a label that is properly aligned   Fields:      x (series int) : The X-axis starting point as a bar index      y (series float) : The Y-axis starting point as the price level      color (series color) : Both the line and text color      width (series int) : Thickness of the line      label (series string) : Text to display      showLabel (series bool) : Boolean to conditionally show/hide the label (default is false)      lineStyle (series LineStyleType) : The style of the line      textSize (series TextSizeType)      _b (series box)      _l (series line)
Libreria Pine Script®
di tristanlee85
Cryptokazancev Strategy PackCryptokazancev Strategy Pack Комплексный инструмент для анализа рыночной структуры / Comprehensive Market Structure Analysis Tool 🇷🇺 Описание на русском Cryptokazancev Strategy Pack by ZeeZeeMon - это мощный набор инструментов для технического анализа, включающий: • Ордерблоки (Order Blocks) с настройкой количества и цветов • Пивоты (Pivot Points) различных таймфреймов • Рыночную структуру с зонами Фибоначчи (0.618, 0.786) • Разворотные конструкции (пинбары и поглощения) • Зоны интереса на основе скопления свингов 📊 Основные функции: 1. Ордерблоки - Автоматическое определение бычьих/медвежьих OB - Настройка максимального количества блоков (до 30) - Кастомизация цветов 2. Пивоты - Поддержка таймфреймов: Дневные/Недельные/Месячные/Квартальные/Годовые - Уровни Camarilla (P, R1-R4, S1-S4) 3. Рыночная структура - Четкое определение тренда (UP/DOWN) - Ключевые уровни Фибо (0.618 и 0.786) - Настройка глубины анализа (10-1000 баров) 4. Разворотные конструкции - Обнаружение пинбаров - Обнаружение поглощений - Настройка чувствительности 5. Зоны интереса - Алгоритм кластеризации свингов - Настройка через ATR-мультипликатор - Лимит отображаемых зон 🇬🇧 English Description ZeeZeeMon Pack is a comprehensive market analysis toolkit featuring: • Order Blocks with customizable count and colors • Pivot Points for multiple timeframes • Market Structure with Fibonacci zones • Reversal patterns (pinbars and engulfings) • Interest Zones based on swing clustering 📊 Key Features: 1. Order Blocks - Auto-detection of bullish/bearish OB - Configurable max blocks (up to 30) - Custom color schemes 2. Pivot Points - Supports: Daily/Weekly/Monthly/Quarterly/Yearly - Camarilla levels (P, R1-R4, S1-S4) 3. Market Structure - Clear trend detection (UP/DOWN) - Key Fibonacci levels (0.618 & 0.786) - Adjustable analysis depth (10-1000 bars) 4. Reversal Patterns - Smart pinbar detection - ATR-based engulfing filter - Sensitivity adjustment 5. Interest Zones - Swing clustering algorithm - ATR-multiplier configuration - Display limit (up to 10 zones) ⚙️ Technical Highlights: • Built with Pine Script v5 • Performance-optimized • Well-commented code • Flexible settings system ⚠️ Важно / Important: Индикатор в бета-версии. Тестируйте перед использованием в реальной торговле. This is BETA version. Please test before live trading. 💬 Поддержка / Support: Комментарии к скрипту / Script comments section
Indicatore Pine Script®
di cryptokazancev
3
TZtraderTZtrader This is a TrendZones version with features to set stoploss and targets in short and long positions meant for use in intraday charts. It aims to provide signals for opening and closing long and short positions. In the comments under the TrendZones publication several people expressed a need for features for a short position similar to those for a long position as implemented in TrendZones, some want to use it for scalping, some asked for alerts. When I proposed to create a version for day trading with target lines based on ATR, several people liked the idea. Full disclosure: I don’t do day trading, because, after I lost a lot of money, I had to promise my wife to stay away from it. I restrict myself to long term investing in stocks which are in uptrend. However I understand what a day trader needs. I gather from my experience that day trading or scalping is an attempt to earn something by opening a position in the morning and close, reopen and close it again during the day with a profit. It is usually done with leveraged instruments like CFD’s, futures, options, and what have you. Opening and closing positions is done within minutes, so the trader needs a quick and efficient way to set proper stoploss and target. TZtrader supports this by showing only three or four numbers on the price bar: The price of the instrument, The logical stop level (gray or green or maroon dots), and the target level (navy). All other numbers are suppressed to prevent mistakes. Also a clear feedback for current settings at the top-center of the pane and an alert feedback at bottom that flashes alerts during the development of the current bar and gives suppression status. The script First I made a bare bones version of TrendZones to which I added code for long and short trading setups and a bare setup for no position. The code for the logical stops in long setup had to be reviewed, after which this became the basis for stops in short setup. Then I added code for 10 alert messages, which was a hassle, because this is the first time I coded alerts and the first time I used an array as a stack to avoid a complicated if-then construction. During testing the array caused a runtime error which I solved by adding ‘array.clear’ to the code, also I discovered that in TradingView separate alerts have to be created for all three setups - short, long and bare. Flipping setups is done in the inputs with a dropdown menu because Pine Script has no function for a clickable button. One visual with three setups. The visual has the TrendZones structure: Three near parallel very smooth curves, which border the moderate uptrend (green) and downtrend (orange) zone over and under the curve in the middle, the COG (Center Of Gravity). Where the price breaks out of these curves, strong trend zones show up over and under the curves, respectively strong uptrend (blue) and strong downtrend (red). Three setups were made clearly different to avoid confusion and to provide oversight in case of multiple trades going on simultaneously which I imagine are monitored in one screen. You have to see which one is long, which short and which have no position. The long setup should not trigger short signals, nor should the short trigger long signals nor the bare setup exclusive long or short signals. The Long setup is default, shown on the example chart. In this setup the Stoploss suggestions (green, gray and maroon dots) are under the price bars and the target line (navy) at a set distance above the High Border. A zone with a width of 1 ATR is drawn under the Low Border. In this setup 5 specific alerts are provided The Short setup has the Stoploss suggestions over the price bars, the target line at a set distance under the Low Border. A zone with a width of 1 ATR is drawn above the High Border. This setup also has 5 specific alerts. The Bare setup has no Stoploss suggestions, no target line and supports 4 alerts, 2 in common with the Long setup and 2 with Short. The table below gives a summary of scripted alerts: Setup = Where = When = Purpose Long, Bare = Green Zone = Bars come from lower zones = Uptrend starts Long, Bare = Green Zone = Sideways ends in uptrend = Uptrend resumes Long = COG = First crossing = Uptrend might end warning Long = Orange Zone = Bars come from higher zones = Uptrend ended take care Long = Red Zone = Bars come from higher zones = Strong downtrend->close Long Short, Bare = Orange Zone = Bars come from higher zones = Downtrend starts Short, Bare = Orange Zone = Sideways ends in downtrend = Downtrend resumes Short = COG = First crossing = Downtrend might end warning Short = Green Zone = Bars come from lower zones = Downtrend ended take care Short = Blue Zone = Bars come from lower zones = Strong uptrend -> close short You can use script alerts in TradingView by clicking the clock in the sidebar, then ‘create alert’ or plus, as condition you choose ‘Tztrader’ in the dialog box, then the “Any alert() function call” option (the first item in the list). The script lets the valid alert trigger by TradingView after the bar is completed, this can differ from the flashed messages during its formation. When you create alerts in Tradingview, I advice to do that for each setup, then to make only the alert active which matches the current setup, pause the other ones. Suppressing false and annoying signals The script has two ways to suppress such signals, which have to do with the numbers in the alert feedback. The numbers left and right of the message with a colored background, depict the zones in which the previous (left) and current (right) bar move. 1 is the strong downtrend zone (red), 2 the moderate downtrend zone (orange), 3 the sideways zones (gray), 4 the COG (gray), 5 the moderate uptrend zone (green), 6 the strong uptrend zone (blue), 7 something went wrong with assigning a zone (black). In extensive testing the number 7 never occurs, because I catch that error in the code. The idea is that an alert is only triggered if the previous bar was in a different zone. When the bars are in the same zone, no alert is possible. This way all annoying signals are suppressed and long, short and bare get the appropriate alerts. The third number is a counter. It counts how often the COG is crossed without touching the outer curves. The counter will reset to zero when the upper or lower curve is touched. When the count is 1 you have zone situation 4 and appropriate alerts are flashed. When the count is 2 or higher, a sideways situation (3) is called and while the recrossings are going on, no alerts can be flashed. This suppresses false signals. The ATR zone and curves are brownish-gray where sideways happens(ed). When the channel is narrowed down to just the three curves, some false signals still might occur. Inputs “Setup”, default is long, drop down menu provides long, short and bare. “Target ATR”, default is 2, sets the amount of ATR for the target line. In 1 minute charts 4 seems an appropriate setting, you have to learn by experience which setting works. “show feedback …” default is on, This creates two feedback labels, a Setup feedback on top of the pane, which shows charted instrument, Setup type, Trend and timeframe of the chart. Background color of Trend feedback is green when it matches the setup, red when mismatches and gray when no match. The alert feedback at the bottom of the pane shows a number, a message and two numbers. The numbers will be explained in the chapter about false and annoying signals below. During formation of the bar, valid alerts are flashed with a blue background, otherwise the message ‘alerts for current bar suppressed’. Logical Stops The curves are the logical place to put stops, because, as these are averages of the high and low border of a Donchian channel, they signify the ‘natural’ current highest, lowest and main level in the lookback period that fit the monitored trend setup. A downtrend turns into an uptrend when a breakout of the upper curve occurs. If you are short, that is where you want to close position, so the logical place for the stoploss is the upper curve. Vice versa, when you are long, the logical stop is on the lower curve. The stops show up as green or gray dots on the curves, the green dots signify a nice entry level, the gray stops are there to suggest levels where unrealized profits might be secured, the maroon dots indicate that the trend mismatches the setup. COG versus other lines Any line used to identify a trend, be it some MA or some other line, is interpreted the same way: When the bars move above the line there is an uptrend and when below, a downtrend. COG is not different in that sense. If you put such a line in the same chart as TZtrader, you can see situations in which the other line shows uptrend or downtrend earlier than COG, also some other lines, e.g. Hull MA, are very good at showing tops and bottoms, while COG ignores these. On the other hand the other lines are usually a little nervous and let you shake out of position too soon. Just like the other lines, COG gives false signals when it is near horizontal. The advantage of the placement COG is the tolerance for pull backs. This way TZtrader keeps you longer in the trend. Such pull backs are often ‘flags’ which are interpreted in TA as confirming the trend. Tztrader aims to get you in position reasonably soon when a trend begins and out of position as soon as the trend turns against you. The placement of COG is done with a fundamentally different algorithm than other lines as it is not an average of prices, but the middle of two averages of borders of a Donchian channel. This gives the two zones between the curves the same quality as the two zones above and below the middle line of a standard Donchian Channel. A multi timeframe application. In this scenario you put a 5 minutes and 1 minute chart with Tztrader side by side. If the 5 minutes shows uptrend, set the 1 minute on long trading and open positions when the trend matches uptrend en close when it mismatches. Don’t open short positions. Once the 5 minute changes to downtrend, set Tztrader in the 1 minute to short trading and open positions when the trend matches downtrend and close when it mismatches. The idea is that in a long ‘context’, provided by the 5 minutes, the uptrends in the 1 minute will last longer and go further, vice versa for the short ‘context’. This way you do swing trading in the 5 minute in a smart way, maximizing profits. You can do this with any timeframe pairs with a proportion of around 5:1, 4:1, 6:1, like e.g. 60 minutes and 15 minutes or weeks and days (5 trading days in a week). Dear day-traders, may this tool be helpful and may your days be blessed. Take care
Indicatore Pine Script®
di eykpunter
2
Range Filter Strategy [Real Backtest]Range Filter Strategy - Real Backtesting # Overview Advanced Range Filter strategy designed for realistic backtesting with precise execution timing and comprehensive risk management. Built specifically for cryptocurrency markets with customizable parameters for different assets and timeframes. Core Algorithm Range Filter Technology: - Smooth Average Range calculation using dual EMA filtering - Dynamic range-based price filtering to identify trend direction - Anti-noise filtering system to reduce false signals - Directional momentum tracking with upward/downward counters Key Features Real-Time Execution (No Delay) - Process orders on tick: Immediate execution without waiting for bar close - Bar magnifier integration for intrabar precision - Calculate on every tick for maximum responsiveness - Standard OHLC bypass for enhanced accuracy Realistic Price Simulation - HL2 entry pricing (High+Low)/2 for realistic fills - Configurable spread buffer simulation - Random slippage generation (0 to max slippage) - Market liquidity validation before entry Advanced Signal Filtering - Volume-based filtering with customizable ratio - Optional signal confirmation system (1-3 bars) - Anti-repetition logic to prevent duplicate signals - Daily trade limit controls Risk Management - Fixed Risk:Reward ratios with precise point calculation - Automatic stop loss and take profit execution - Position size management - Maximum daily trades limitation Alert System - Real-time alerts synchronized with strategy execution - Multiple alert types: Setup, Entry, Exit, Status - Customizable message formatting with price/time inclusion - TradingView alert panel integration Default Parameters Optimized for BTC 5-minute charts: - Sampling Period: 100 - Range Multiplier: 3.0 - Risk: 50 points - Reward: 100 points (1:2 R:R) - Spread Buffer: 2.0 points - Max Slippage: 1.0 points Signal Logic Long Entry Conditions: - Price above Range Filter line - Upward momentum confirmed - Volume requirements met (if enabled) - Confirmation period completed (if enabled) - Daily trade limit not exceeded Short Entry Conditions: - Price below Range Filter line - Downward momentum confirmed - Volume requirements met (if enabled) - Confirmation period completed (if enabled) - Daily trade limit not exceeded Visual Elements - Range Filter line with directional coloring - Upper and lower target bands - Entry signal markers - Risk/Reward ratio boxes - Real-time settings dashboard Customization Options Market Adaptation: - Adjust Sampling Period for different timeframes - Modify Range Multiplier for various volatility levels - Configure spread/slippage for different brokers - Set appropriate R:R ratios for trading style Filtering Controls: - Enable/disable volume filtering - Adjust confirmation requirements - Set daily trade limits - Customize alert preferences Performance Features - Realistic backtesting results aligned with live trading - Elimination of look-ahead bias - Proper order execution simulation - Comprehensive trade statistics Alert Configuration Alert Types Available: - Entry signals with complete trade information - Setup alerts for early preparation - Exit notifications for position management - Filter direction changes for market context Message Format: Symbol - Action | Price: XX.XX | Stop: XX.XX | Target: XX.XX | Time: HH:MM Usage Recommendations Optimal Settings: - Bitcoin/Major Crypto: Default parameters - Forex: Reduce sampling period to 50-70, multiplier to 2.0-2.5 - Stocks: Reduce sampling period to 30-50, multiplier to 1.0-1.8 - Gold: Sampling period 60-80, multiplier 1.5-2.0 TradingView Configuration: - Recalculate: "On every tick" - Orders: "Use bar magnifier" - Data: Real-time feed recommended Risk Disclaimer This strategy is designed for educational and analytical purposes. Past performance does not guarantee future results. Always test thoroughly on paper trading before live implementation. Consider market conditions, broker execution, and personal risk tolerance when using any automated trading system. Best Settings Found for Gold 15-Minute Timeframe After extensive testing and optimization, these are the most effective settings I've discovered for trading Gold (XAUUSD) on the 15-minute timeframe: Core Filter Settings: Sampling Period: 100 Range Multiplier: 3.0 Professional Execution Engine: Realistic Entry: Enabled (HL2) Spread Buffer: 2 points Dynamic Slippage: Enabled with max 1 point Volume Filter: Enabled at 1.7x ratio Signal Confirmation: Enabled with 1 bar confirmation Risk Management: Stop Loss: 50 points Take Profit: 100 points (2:1 Risk-Reward) Max Trades Per Day: 5 These settings provide an excellent balance between signal accuracy and realistic market execution. The volume filter at 1.7x ensures we only trade during periods of sufficient market activity, while the 1-bar confirmation helps filter out false signals. The spread buffer and slippage settings account for real trading costs, making backtest results more realistic and achievable in live trading.
Strategia Pine Script®
di mfsz2015
Range Filter Strategy [Arabic Real Backtest]استراتيجية مرشح النطاق - اختبار واقعي نظرة عامة استراتيجية مرشح النطاق المتقدمة مصممة للاختبار الواقعي مع توقيت تنفيذ دقيق وإدارة مخاطر شاملة. تم بناؤها خصيصًا لأسواق العملات الرقمية مع معلمات قابلة للتخصيص لأصول وفترات زمنية مختلفة. الخوارزمية الأساسية تقنية مرشح النطاق: * حساب متوسط النطاق السلس باستخدام فلترة مزدوجة للـ EMA * فلترة أسعار استنادًا إلى النطاق الديناميكي لتحديد اتجاه الاتجاه * نظام فلترة ضد الضوضاء لتقليل الإشارات الخاطئة * تتبع الزخم الاتجاهي مع عدادات للأعلى/للأسفل الميزات الرئيسية **التنفيذ الفوري (بدون تأخير)** * معالجة الأوامر عند كل نقطة: تنفيذ فوري دون انتظار إغلاق الشمعة * تكامل مكبر الشمعة للحصول على دقة داخل الشمعة * الحساب في كل نقطة لضمان الاستجابة القصوى * تجاوز OHLC القياسي لزيادة الدقة **محاكاة الأسعار الواقعية** * تسعير الدخول باستخدام HL2 (High+Low)/2 لملء واقعي * محاكاة للبُعد العازل للسعر القابل للتخصيص * إنشاء انزلاق عشوائي (من 0 إلى الحد الأقصى للانزلاق) * التحقق من سيولة السوق قبل الدخول **فلترة الإشارات المتقدمة** * فلترة استنادًا إلى الحجم مع نسبة قابلة للتخصيص * نظام تأكيد الإشارة اختياري (من 1 إلى 3 شموع) * منطق مضاد للتكرار لمنع الإشارات المكررة * التحكم في حد التداول اليومي **إدارة المخاطر** * نسب ثابتة للمخاطرة: العائد مع حساب دقيق للنقاط * تنفيذ وقف الخسارة وجني الأرباح تلقائيًا * إدارة حجم المركز * تحديد الحد الأقصى للصفقات اليومية **نظام التنبيهات** * تنبيهات فورية متزامنة مع تنفيذ الاستراتيجية * أنواع متعددة من التنبيهات: إعداد، دخول، خروج، حالة * تخصيص تنسيق الرسائل مع تضمين السعر/الوقت * تكامل مع لوحة تنبيهات TradingView المعلمات الافتراضية محسن لرسوم بيانية لفترة 5 دقائق لبيتكوين: * فترة العينة: 100 * معامل النطاق: 3.0 * المخاطرة: 50 نقطة * المكافأة: 100 نقطة (نسبة 1:2) * بُعد الانتشار: 2.0 نقطة * الحد الأقصى للانزلاق: 1.0 نقطة منطق الإشارة **شروط الدخول الطويل:** * السعر فوق خط مرشح النطاق * تأكيد الزخم الصاعد * تلبية متطلبات الحجم (إذا تم تمكينها) * اكتمال فترة التأكيد (إذا تم تمكينها) * لم يتم تجاوز حد الصفقات اليومية **شروط الدخول القصير:** * السعر تحت خط مرشح النطاق * تأكيد الزخم الهابط * تلبية متطلبات الحجم (إذا تم تمكينها) * اكتمال فترة التأكيد (إذا تم تمكينها) * لم يتم تجاوز حد الصفقات اليومية العناصر البصرية * خط مرشح النطاق مع تلوين الاتجاه * الأشرطة العليا والسفلى المستهدفة * علامات إشارات الدخول * صناديق نسبة المخاطرة/العائد * لوحة إعدادات حية خيارات التخصيص **التكيف مع السوق:** * تعديل فترة العينة لبيانات الزمن المختلفة * تعديل معامل النطاق لمستويات التقلب المختلفة * تكوين الانتشار/الانزلاق لوسطاء مختلفين * تحديد النسب المناسبة للمخاطرة/العائد حسب أسلوب التداول **ضوابط الفلترة:** * تمكين/تعطيل فلترة الحجم * تعديل متطلبات التأكيد * تعيين حدود الصفقات اليومية * تخصيص تفضيلات التنبيه الميزات المتعلقة بالأداء * نتائج اختبار واقعية متوافقة مع التداول المباشر * القضاء على تحيز المستقبل * محاكاة تنفيذ الأوامر بشكل صحيح * إحصائيات تداول شاملة تكوين التنبيه **أنواع التنبيهات المتاحة:** * إشارات الدخول مع معلومات التداول الكاملة * تنبيهات الإعداد للتحضير المبكر * إشعارات الخروج لإدارة المراكز * فلترة التغيرات في الاتجاه لظروف السوق **تنسيق الرسائل:** رمز - الإجراء | السعر: XX.XX | الوقف: XX.XX | الهدف: XX.XX | الوقت: HH\:MM التوصيات لاستخدام الاستراتيجية **الإعدادات المثلى:** * بيتكوين/العملات الرقمية الرئيسية: المعلمات الافتراضية * الفوركس: تقليل فترة العينة إلى 50-70، المعامل إلى 2.0-2.5 * الأسهم: تقليل فترة العينة إلى 30-50، المعامل إلى 1.0-1.8 * الذهب: فترة العينة 60-80، المعامل 1.5-2.0 **تكوين TradingView:** * إعادة الحساب: "على كل نقطة" * الأوامر: "استخدام مكبر الشمعة" * البيانات: يوصى باستخدام التغذية الحية إخلاء المسؤولية تم تصميم هذه الاستراتيجية لأغراض تعليمية وتحليلية. الأداء السابق لا يضمن النتائج المستقبلية. يجب دائمًا إجراء اختبارات شاملة على التداول الورقي قبل التنفيذ المباشر. يجب أخذ ظروف السوق، تنفيذ الوسيط، والتحمل الشخصي للمخاطر في الاعتبار عند استخدام أي نظام تداول آلي. Range Filter Strategy - Real Backtesting # Overview Advanced Range Filter strategy designed for realistic backtesting with precise execution timing and comprehensive risk management. Built specifically for cryptocurrency markets with customizable parameters for different assets and timeframes. Core Algorithm Range Filter Technology: - Smooth Average Range calculation using dual EMA filtering - Dynamic range-based price filtering to identify trend direction - Anti-noise filtering system to reduce false signals - Directional momentum tracking with upward/downward counters Key Features Real-Time Execution (No Delay) - Process orders on tick: Immediate execution without waiting for bar close - Bar magnifier integration for intrabar precision - Calculate on every tick for maximum responsiveness - Standard OHLC bypass for enhanced accuracy Realistic Price Simulation - HL2 entry pricing (High+Low)/2 for realistic fills - Configurable spread buffer simulation - Random slippage generation (0 to max slippage) - Market liquidity validation before entry Advanced Signal Filtering - Volume-based filtering with customizable ratio - Optional signal confirmation system (1-3 bars) - Anti-repetition logic to prevent duplicate signals - Daily trade limit controls Risk Management - Fixed Risk:Reward ratios with precise point calculation - Automatic stop loss and take profit execution - Position size management - Maximum daily trades limitation Alert System - Real-time alerts synchronized with strategy execution - Multiple alert types: Setup, Entry, Exit, Status - Customizable message formatting with price/time inclusion - TradingView alert panel integration Default Parameters Optimized for BTC 5-minute charts: - Sampling Period: 100 - Range Multiplier: 3.0 - Risk: 50 points - Reward: 100 points (1:2 R:R) - Spread Buffer: 2.0 points - Max Slippage: 1.0 points Signal Logic Long Entry Conditions: - Price above Range Filter line - Upward momentum confirmed - Volume requirements met (if enabled) - Confirmation period completed (if enabled) - Daily trade limit not exceeded Short Entry Conditions: - Price below Range Filter line - Downward momentum confirmed - Volume requirements met (if enabled) - Confirmation period completed (if enabled) - Daily trade limit not exceeded Visual Elements - Range Filter line with directional coloring - Upper and lower target bands - Entry signal markers - Risk/Reward ratio boxes - Real-time settings dashboard Customization Options Market Adaptation: - Adjust Sampling Period for different timeframes - Modify Range Multiplier for various volatility levels - Configure spread/slippage for different brokers - Set appropriate R:R ratios for trading style Filtering Controls: - Enable/disable volume filtering - Adjust confirmation requirements - Set daily trade limits - Customize alert preferences Performance Features - Realistic backtesting results aligned with live trading - Elimination of look-ahead bias - Proper order execution simulation - Comprehensive trade statistics Alert Configuration Alert Types Available: - Entry signals with complete trade information - Setup alerts for early preparation - Exit notifications for position management - Filter direction changes for market context Message Format: Symbol - Action | Price: XX.XX | Stop: XX.XX | Target: XX.XX | Time: HH:MM Usage Recommendations Optimal Settings: - Bitcoin/Major Crypto: Default parameters - Forex: Reduce sampling period to 50-70, multiplier to 2.0-2.5 - Stocks: Reduce sampling period to 30-50, multiplier to 1.0-1.8 - Gold: Sampling period 60-80, multiplier 1.5-2.0 TradingView Configuration: - Recalculate: "On every tick" - Orders: "Use bar magnifier" - Data: Real-time feed recommended Risk Disclaimer This strategy is designed for educational and analytical purposes. Past performance does not guarantee future results. Always test thoroughly on paper trading before live implementation. Consider market conditions, broker execution, and personal risk tolerance when using any automated trading system.
Strategia Pine Script®
di mfsz2015
GCM Volatility-Adaptive Trend ChannelScript Description Name: GCM Volatility-Adaptive Trend Channel (GCM VATC) Overview The GCM Volatility-Adaptive Trend Channel (VATC) is a comprehensive trading tool that merges the low-lag, smooth-trending capabilities of the Jurik Moving Average (JMA) with the classic volatility analysis of Bollinger Bands (BB). By displaying both trend and volatility in a single, intuitive interface, this indicator aims to help traders see when a trend is stable versus when it's becoming volatile and might be poised for a change. Core Components: JMA Trend System: At its core are three dynamically colored JMA lines (Baseline, Fast, and Slow) that provide a clear view of trend direction. The lines change color based on their slope, offering immediate visual feedback on momentum. A colored ribbon between the Baseline and Fast JMA visualizes shorter-term momentum shifts. Standard Bollinger Bands: Layered on top are standard Bollinger Bands. Calculated from the price, these bands serve as a classic measure of market volatility. They help identify periods where the market is expanding (high volatility) or contracting (low volatility). How to Use It By combining these two powerful concepts, this indicator provides a unified view of both trend and volatility. It can help traders to: Identify the primary trend direction using the smooth JMA lines. Gauge the strength and stability of that trend. See when the market is becoming volatile (bands widening) or consolidating (bands contracting), which can often precede a significant price move or a change in trend. A Note on Originality & House Rules Compliance This indicator does not introduce a new mathematical formula. Instead, its strength lies in the thoughtful combination of two well-respected, publicly available concepts: the Jurik Moving Average and Bollinger Bands. The JMA implementation is a standard public version. The goal was to create a practical, all-in-one tool for trend and volatility analysis. This script is published as fully open-source in compliance with TradingView's House Rules. It utilizes standard, publicly available algorithms and does not contain any protected or hidden code. Settings All lengths, sources, and colors for the JMA lines and Bollinger Bands are fully customizable in the settings menu, allowing you to tailor the indicator to your specific trading style and asset. I hope with this indicator Traders even Beginner can can control their emotions which increase the probabilities of the winning rates and cutting the losing strength Purposely I Didn't plant the High low or Buy Sell signals in the chart. Because everything is in the chart where volatility Signal with the Bollinger Band and Buy Sell Signal in the JMA Dynamic colors. and that's enough to decide when to take trade and when not to. Thank You and Happy Trading
Indicatore Pine Script®
di uniGram
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