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VG 1.0This script is an enhanced version of SMC Structures and FVG with an advanced JSON-based alert system designed for seamless integration with webhooks and external applications (such as a Swift iOS app). What it does It detects and plots on the chart: Fair Value Gaps (FVG) — bullish and bearish. Break of Structure (BOS) and Change of Character (CHOCH). Key Fibonacci levels (0.786, 0.705, 0.618, 0.5, 0.382) based on the current structure. Additionally, it generates custom alerts: FVG Alerts: When a new FVG is created (bullish or bearish). When an existing FVG gets mitigated. BOS & CHOCH Alerts: Includes breakout direction (bullish or bearish). Fibonacci Alerts: When price touches a configured level, with adjustable tick tolerance. Alerts can be: Declarative (alertcondition) for manual setup inside TradingView. Programmatic (alert() JSON) for automated webhook delivery to your system or mobile app. Key Features Optional close confirmation to filter out false signals. Standardized JSON format for direct API or mobile app integration. Webhook-ready for automated push notifications. Full visual control with lines, boxes, and labels. Configurable tick tolerance for Fibonacci “touch” detection.
Pine Script® indicator
by Victorgallotrade4life
Ai buy and sell fundamental the Gk fundamental is a precision built market analysis tool designed yto help traders identify high probability it uses a combination of market structure analysis, volatility tracking, and multi time frame confirmation to highlight possible trade opportunities HOW IT WORKS analyses momentum shift and structure breaks on the 2h chart for clearer direction confirms potential entries by filtering market noise and using volatility directional filters HOW TO USE apply 2h chart for primary direction when signal appears allow 1 candle to close for confirmation drop to lower time frame to lower time frame to refine entry if desired always use proper risk management - no tool guarantees results
Pine Script® indicator
by hgavin780
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.
Pine Script® indicator
by EdgeTools
QUANTUM MARKET ANALYZER X7QUANTUM MARKET ANALYZER X7 — Study Material (Learning & Teaching Guide) What this tool is (and isn’t) QUANTUM MARKET ANALYZER X7 is a multi-factor TradingView indicator that summarizes many classic signals into one dashboard. It does not predict the future or guarantee profits. It simply scores what is happening now using oscillators, moving averages, order-block behavior, trendline/channel context, Supertrend bias, and volume/flow clues—so you can make structured, risk-aware decisions. ________________________________________ Quick start (for brand-new traders) 1. Add the indicator to a chart. 2. Pick an Analysis Timeframe (e.g., 60-min for day trading, 4-hour for swing). 3. Read the Summary tile first; then check Oscillators → MAs → OB/Trendline/Supertrend → Volume. 4. Take trades only when multiple sections agree, and always plan stop loss and size before entry. ________________________________________ How the dashboard is built (section by section) Below you’ll learn what each section measures, how the numbers are produced, and how to interpret them. The script converts each sub-signal into a small integer (e.g., +2, +1, 0, −1, −2). These are summed into section totals and then into a Summary score. 1) Summary (the combined score) • What it is: The grand total of all sections (Oscillators + Moving Averages + Advanced: OB, Trendline/Channel, Supertrend, Volume). • How it’s labeled: o Large positive total → BUY / STRONG BUY o Around zero → NEUTRAL o Large negative total → SELL / STRONG SELL • How to use: Treat it as a headline, not a trigger. Confirm with the sections below and price action. ________________________________________ 2) Oscillators (momentum / overbought–oversold) Inputs used on your chosen timeframe: • RSI(14): o 70 → bearish pressure (−) o <30 → bullish pressure (+) • Stochastic (14): o 80 overbought (−), <20 oversold (+) • CCI(20): o +100 (−), <−100 (+) • Williams %R(14): o −20 overbought (−), <−80 oversold (+) • MACD(12,26,9): o MACD line > Signal → (+), below → (−) • Momentum(10): >0 → (+), <0 → (−) • ROC(9): >+2% → (+), <−2% → (−) • Bollinger Bands(20,2): o Price > Upper band → (−), < Lower band → (+) How it scores: Each item contributes between −2 and +2 (or −1/+1 for some). The Oscillator total is their sum. How to use: Oscillators excel for timing. Favor longs when the total is clearly positive and exiting or avoiding when clearly negative. ________________________________________ 3) Moving Averages (trend/structure) MAs used: SMA(10/20/50/100/200) and EMA(10/20/50). Scoring logic: Compares price vs each MA: • Price > MA by >2% → +2 (strongly bullish) • Price > MA by 0–2% → +1 • Price < MA by 0–2% → −1 • Price < MA by >2% → −2 How to use: A clearly positive MA total suggests trend alignment for longs; clearly negative favors shorts or flat. Mixed readings → treat as range/transition. ________________________________________ 4) Order-Block (OB) breakout analysis (support/resistance from clustered reactions) What it approximates: The script searches a lookback window for pivot-like candles and counts repeated “touches” near that level (within ±0.2%) to infer support (bullish OB) or resistance (bearish OB). Settings you can tune • OB Lookback Period: how far back to search. • Min OB Touches: more touches = stronger level. Signals produced • BULLISH BRK: Price crosses above the most recent bearish OB (resistance → breakout). • BEARISH BRK: Price crosses below the most recent bullish OB (support → breakdown). • ABOVE SUP / BELOW RES: Price position relative to the latest OB levels. How to use: Use OB with MAs and Volume. Best when a breakout comes with trend alignment and volume expansion. ________________________________________ 5) Trendline / Channel analysis (context envelope) Rather than a single diagonal line, this module forms a dynamic channel: • Finds highest high and lowest low over your Trendline Lookback. • Builds a midline = (highest + lowest)/2. • Creates an upper/lower channel by multiplying the range with Channel Width Multiplier. Signals produced • UPPER BRK: Price > upper channel (bullish expansion) • LOWER BRK: Price < lower channel (bearish expansion) • ABOVE MID / BELOW MID: Bias zone inside channel How to use: Treat UPPER/LOWER breaks as momentum context. Confirm with MAs and Volume before acting. ________________________________________ 6) Supertrend (ATR-based bias) • Uses ta.supertrend(ATR Multiplier, ATR Period) on your analysis timeframe. • Signal: o BULLISH when Supertrend flips to trend-up state o BEARISH when it flips to trend-down Tuning tips: • Higher ATR Multiplier (e.g., 6) → fewer, higher-quality flips. • Lower multiplier → more responsive, more noise. How to use: Use Supertrend as a trend filter. Avoid fighting it unless higher-timeframe context disagrees and you have strong confluence. ________________________________________ 7) Volume/Flow analysis (participation & pressure) This section combines several volume-based tools: 1. Volume Spike vs MA o Volume MA Period (default 20) o Volume Spike Threshold (e.g., 1.5×) o If current volume / MA > threshold → spike. 2. OBV vs OBV-MA → Accumulation (+) / Distribution (−) 3. VPT vs VPT-MA → Price-volume trend alignment (+/−) 4. MFI(14): >70 (−), <30 (+) 5. Accumulation/Distribution vs its MA → (+/−) Scoring: • Big spike with up bar → +2; with down bar → −2 • Each of OBV, VPT, MFI, A/D adds +1 or −1 Interpretation labels: • HIGH ACC / ACCUM → constructive flow • HIGH DIST / DISTRIB → selling pressure • NEUTRAL → no edge How to use: Favor setups where directional signals + trend + volume point the same way. ________________________________________ Putting it together — a repeatable reading order 1. Summary: What’s the combined bias? 2. Oscillators: Is momentum supportive or stretched? 3. MAs: Is price aligned with the trend structure? 4. OB & Trendline/Channel: Are we breaking key levels/zones? 5. Supertrend: Is the higher-level bias with you or against you? 6. Volume: Is there participation to confirm the move? Only act when at least 3–4 sections agree and you can define a logical stop and position size. ________________________________________ Parameter tuning (step-by-step) 1. Choose timeframe: o 15–60m for active trading; 4h–1D for swing. 2. Oscillators: o Keep defaults first; later tighten or loosen thresholds only if you’ve tested. 3. Moving Averages: o The script’s built-in 0–2% bands around each MA are sensible. o If your market is very volatile, you can consider widening the 2% threshold to reduce whipsaws (requires code edit). 4. Order Blocks: o Start with OB Lookback ~50 and Min Touches = 2. o Increase touches for fewer, stronger zones. 5. Trendline/Channel: o Longer Trendline Lookback and smaller Channel Width → tighter channel (more breaks). o Shorter lookback and larger width → fewer breaks. 6. Supertrend: o If you get too many flips, raise ATR Multiplier. o If it’s lagging, lower it slightly. 7. Volume: o For quieter instruments, reduce the Threshold (e.g., 1.2×). o For very liquid/active markets, 1.5–2.0× works well. ________________________________________ Example playbooks (for practice) A) Pro-trend long continuation • Summary: BUY or STRONG BUY • MAs: clearly positive • Supertrend: BULLISH • OB/Trendline: ABOVE MID or UPPER BRK • Volume: ACCUM or HIGH ACC Plan: Enter on a minor pullback; stop below recent structure; scale out at logical resistance. B) Mean-reversion short (cautious) • Oscillators: multiple overbought readings (RSI>70, price > BB upper) • MAs: still positive (trend up), so this is countertrend • Volume: no spike Plan: If you must, take smaller size, tighter stop, faster targets. Prefer waiting for alignment instead. C) Breakout with confirmation • OB: BULLISH BRK of a known resistance • Trendline/Channel: UPPER BRK • Volume: spike with up bar • Supertrend: recently flipped up Plan: Enter on retest or structured continuation; define stop under breakout level. ________________________________________ Common pitfalls to avoid • Acting on one section alone. Confluence matters. • Chasing after long candles without volume follow-through. • Ignoring timeframe alignment. Check the next higher timeframe. • Oversizing trades just because “Summary = Strong Buy/Sell.” • Moving stops farther instead of accepting a planned loss. ________________________________________ Practice & evaluation routine 1. Replay mode (TradingView Bar Replay) to practice reading the tiles in order. 2. Journal each trade: which sections agreed, where stop/target were, outcome. 3. Weekly review: Were losing trades missing confirmation? Did you respect size rules? 4. Iterate cautiously: Change one setting at a time and observe for a week. ________________________________________ Frequently asked questions Q: Is the Summary score weighted? A: Each sub-signal contributes small integers; totals from Oscillators, MAs, and Advanced sections are added without fancy weighting, keeping it transparent. Q: Can I use this as a standalone system? A: It’s best used as a decision support layer with your own risk rules, not as a mechanical “buy/sell” machine. Q: Which timeframe is best? A: The one that matches your holding period. Always confirm with at least one higher timeframe. ________________________________________ Suggested classroom flow (for teaching) 1. Session 1: Oscillators only → identify good vs stretched momentum. 2. Session 2: Moving Averages → trend structure and bias. 3. Session 3: OB + Trendline/Channel → location and breakouts. 4. Session 4: Supertrend + Volume → confirmation and participation. 5. Session 5: Confluence building → case studies and journaling. 6. Session 6: Risk management, sizing, and review habits. ________________________________________ Disclaimer aiTrendview (please read) This indicator and study material are provided for educational and research purposes only. They do not constitute financial advice, investment recommendations, or a promise of performance. Trading involves substantial risk and may result in losses. Past performance of any method or indicator does not guarantee future results. You are solely responsible for your trading decisions, including risk management, position sizing, and due diligence. Always test ideas in a demo environment before using real capital, and consider consulting a licensed financial advisor.
Pine Script® indicator
by aiTrendview-Charting-System
Fractal Suite: MTF Fractals + BOS/CHOCH + OB + FVG + Targets Kese Way Fractals (Multi-Timeframe): Automatically detects both current-timeframe and higher-timeframe Bill Williams fractals, with customizable left/right bar settings. Break of Structure (BOS) & CHoCH: Marks structural breaks and changes of character in real time. Liquidity Sweeps: Identifies sweep patterns where price takes out a previous swing high/low but closes back within range. Order Blocks (OB): Highlights the last opposite candle before a BOS, with customizable extension bars. Fair Value Gaps (FVG): Finds 3-bar inefficiencies with a minimum size filter. Confluence Zones: Optionally require OB–FVG overlap for high-probability setups. Entry, Stop, and Targets: Automatically calculates entry price, stop loss, and up to three take-profit targets based on risk-reward ratios. Visual Dashboard: Mini on-chart table summarizing structure, last swing points, and settings. Alerts: Set alerts for new fractals, BOS events, and confluence-based trade setups.
Pine Script® indicator
by Shukese
Volume/Price Movement Indicator## Volume/Price Movement Indicator (VPM) The **Volume/Price Movement Indicator (VPM)** is a technical analysis tool designed to identify the strength and potential direction of a trend by combining price momentum with volume analysis. Unlike indicators that only look at price, VPM uses volume as a confirming factor to gauge the conviction behind a price move. This helps traders distinguish between strong, high-conviction trends and weak, low-conviction movements that may be prone to reversal. *** ### Key Concepts * **Price Trend**: The indicator smooths out daily price changes to determine the underlying trend direction. A positive price trend suggests upward momentum, while a negative trend suggests downward momentum. * **Volume Analysis**: The VPM calculates a **Volume Ratio**, which compares the current bar's volume to its moving average. A high volume ratio indicates that the current volume is significantly higher than recent average volume, suggesting strong market participation. The **Volume Threshold Multiplier** is used to define what constitutes "high volume." * **Net Pressure**: This component measures the difference between buying pressure and selling pressure, providing an additional layer of confirmation. Positive net pressure indicates that buying activity is outpacing selling, and vice versa. *** ### How to Use the Indicator The VPM plots its findings on a histogram below the main chart, using colors to clearly signal the market's state. * **🟢 Strong Bull (Green)**: This is the most powerful bullish signal. It indicates a clear upward price trend that is confirmed by both high volume and positive net pressure. This is a strong signal of conviction and potential continuation of the uptrend. * **🔵 Weak Bull (Lime)**: This signal indicates a clear upward price trend, but with low volume. The positive net pressure suggests buying is still dominant, but the lack of high volume means there may not be strong market conviction. This signal suggests caution and may precede a consolidation or reversal. * **🔴 Strong Bear (Red)**: The strongest bearish signal. It indicates a clear downward price trend confirmed by high volume and negative net pressure. This suggests strong selling conviction and a high probability of the downtrend continuing. * **🟠 Weak Bear (Orange)**: This indicates a clear downward price trend but with low volume. Negative net pressure confirms selling dominance, but the low volume suggests a lack of strong conviction. Like the "Weak Bull" signal, this suggests caution. * **⚫ Neutral (Gray)**: This signal is displayed when there is no clear trend or when price and volume are diverging. It's a signal of market indecision and suggests waiting for a clearer signal. *** ### Indicator Settings * **Trend Length**: This input controls the sensitivity of the price trend calculation. A smaller value will make the indicator more responsive to short-term price changes, while a larger value will filter out noise and focus on longer-term trends. * **Volume MA Length**: This determines the length of the moving average used as a baseline for volume. A longer length will make the "high volume" condition harder to meet. * **Volume Threshold Multiplier**: This is a key setting for tuning the indicator. It determines how much higher the current volume must be than its moving average to be considered "high volume." For example, a value of `1.2` means volume must be at least 20% higher than the moving average to trigger a high-volume signal.
Pine Script® indicator
by HabibiBudo
S/R Clouds Overview The S/R Clouds Indicator is a sophisticated TradingView tool designed to visualize support and resistance levels through dynamic cloud formations. Built on the principles of Keltner Channels, it employs a central moving average enveloped by volatility-based bands to highlight potential price reversal zones. This indicator enhances chart analysis with customizable aesthetics and practical alerts, making it suitable for traders across various strategies and timeframes. Key Features Dynamic Bands: Calculates upper and lower bands using a configurable moving average (SMA or EMA) offset by multiples of the average true range (derived from high-low ranges), capturing volatility deviations for precise S/R identification. Cloud Visualization: Renders semi-transparent clouds between primary and extended bands, providing a clear, layered view of support (lower) and resistance (upper) areas. Trend Detection: Incorporates a trend state logic based on price position relative to bands and moving average direction, aiding in bullish/bearish market assessments. Customization Options: Select from multiple color themes (e.g., Neon, Grayscale) or use custom colors for bands. Enable glow effects for enhanced visual depth and adjust opacity for chart clarity. Volatility Insights: Monitors band width to detect squeezes (low volatility) and expansions (high volatility), signaling potential breakouts. Alerts System: Triggers notifications for price crossings of bands, trend changes, and other key events to support timely decision-making. How It Works At its core, the indicator centers on a user-defined period moving average. Volatility is measured via an exponential moving average of the high-low range, multiplied by adjustable factors to form the bands. This setup creates adaptive clouds that expand/contract with market volatility, offering a more responsive alternative to static S/R lines. The result is a clean, professional overlay that integrates seamlessly with other technical tools. This high-quality indicator prioritizes usability and visual appeal, ensuring traders can focus on analysis without distraction.
Pine Script® indicator
by AlchimistOfCrypto
WaveRider Momentum OscillatorWaveRider Momentum Oscillator The WaveRider Momentum Oscillator applies principles inspired by fluid dynamics to model price momentum as a flowing system, rather than relying on traditional static calculations. By interpreting market movement through the lens of velocity, viscosity, and turbulence—core concepts in fluid mechanics—this indicator offers a more adaptive and nuanced view of momentum that adjusts dynamically to changing market conditions. Conceptual Foundation Velocity: Just as fluid velocity measures the speed of flow at a point, WaveRider calculates momentum velocity by measuring the rate of price change over a specified period, smoothed to reduce noise. Viscosity: In fluid dynamics, viscosity represents internal friction that resists flow. Here, viscosity is modeled based on volatility, modulating momentum signals to account for the “thickness” or noise level of the market. High volatility increases viscosity’s damping effect, reducing false signals during turbulent price action. Turbulence: Turbulence characterizes sudden, chaotic changes in fluid flow. WaveRider detects rapid acceleration bursts in momentum analogous to turbulence, highlighting moments when momentum is shifting sharply and potentially signaling strong upcoming price moves. Technical Features and Interpretation Adaptive Momentum Calculation: Momentum is scaled by volatility-adjusted viscosity, making the oscillator less prone to whipsaws and more responsive during stable trends. Turbulence Burst Detection: The oscillator incorporates a turbulence factor, identifying abrupt momentum accelerations that traditional oscillators often miss. This feature provides early warning signals of potential breakout or reversal points. HSV Gradient Color Mapping: The oscillator visualizes acceleration using a continuous hue gradient—ranging from red (deceleration) through yellow (neutral) to green (acceleration). This continuous color transition provides intuitive, real-time insight into momentum dynamics beyond mere numeric values. Pivot Point Identification: WaveRider automatically marks momentum pivots, signaling local maxima and minima in momentum flow. These points serve as critical confirmation markers for potential entry and exit decisions. How to Interpret WaveRider Colors: Green hues indicate positive acceleration — momentum is increasing, favoring bullish positions. Yellow hues represent neutral momentum — the market is consolidating or pausing. Red hues signal negative acceleration — momentum is weakening, suggesting caution or bearish bias. Oscillator Direction: An upward sloping oscillator line reflects strengthening momentum. A downward slope indicates weakening momentum or a potential reversal. Pivot Labels: ▲ (Pivot Low): Denotes local momentum troughs; potential points to consider initiating long positions. ▼ (Pivot High): Marks local momentum peaks; useful for identifying possible short entries or profit-taking zones. Summary By grounding momentum analysis in fluid dynamics, WaveRider transcends the limitations of traditional oscillators. It accounts for the market’s inherent volatility and captures real-time acceleration changes, enabling traders to detect meaningful momentum shifts with greater accuracy and clarity. WaveRider is designed for traders seeking a scientifically informed tool that adapts fluidly with market conditions—offering deeper insight into momentum flow and better timing for entries and exits.
Pine Script® indicator
by BOSWaves
Pivot Points HL DetailedThis indicator marks important turning points in the market, showing you the most recent swing high and swing low as horizontal lines across the chart. Each pivot line has a price label where it formed and a small counter that updates whenever the market touches that level again. The line’s color reflects the prevailing trend, determined by an EMA filter, so you can quickly see if the level is likely acting as support or resistance in the current market environment. It works by scanning recent bars for points where price made a local high higher than several bars to its left and right, or a local low lower than several bars to its left and right. These pivots are calculated directly from price action using the ta.pivothigh and ta.pivotlow functions. Once identified, the level is tracked in real time, counting every time price crosses it. The EMA provides context: if price is above the EMA, the market is considered in an uptrend and the pivots are colored to match; if price is below, they’re marked as part of a downtrend. For traders, this offers a clean way to see where the market has turned before and whether those levels are still relevant. Strong levels often show multiple touches, which can be used for entries, exits, or risk management. The built-in alert system can notify you when price approaches either the most recent swing high or swing low, so you can react quickly. This tool can be applied in almost any market — forex, stocks, indices, commodities, or crypto — because price tends to respect recent swing points regardless of the asset class. It tends to be most effective in liquid markets, where many traders see and react to the same key levels, and it’s valuable in both trending and ranging conditions, though the EMA trend filter adds extra clarity when the market is moving directionally.
Pine Script® indicator
by SupertradeOfficial
糖哥专属MA均线Custom MA 30-60-90-120-180-250 is a versatile Moving Average (MA) indicator designed for TradingView, supporting the simultaneous display of six moving averages (default periods: 30, 60, 90, 120, 180, 250). This indicator is ideal for trend analysis, support and resistance identification, and generating trading signals. Optimized for free plan users, it bypasses the 3-indicator limit by combining multiple MAs into a single script.Key FeaturesMultiple Moving Averages: Displays six MAs by default (MA30, MA60, MA90, MA120, MA180, MA250) with fully adjustable periods. Flexible MA Types: Supports Simple Moving Average (SMA), Exponential Moving Average (EMA), and Weighted Moving Average (WMA), switchable via the settings panel. Custom Price Source: Allows selection of price data such as close, open, high, low, and more for MA calculations. Display Control: Each MA can be individually enabled or disabled to reduce chart clutter. Customizable Styles: Supports custom colors and line thickness for each MA, enhancing visual clarity. Free Plan Friendly: Combines all MAs into a single indicator, perfect for TradingView’s free plan users. Use CasesTrend Analysis: Identify potential buy/sell signals through MA crossovers (e.g., MA30 crossing above MA60). Support and Resistance: MAs serve as dynamic support or resistance levels to aid price analysis. Multi-Timeframe: Suitable for daily, hourly, or other timeframes, with adjustable periods to match your strategy. SettingsMA Periods: Customize the period for each MA (default: 30, 60, 90, 120, 180, 250). MA Type: Choose between SMA, EMA, or WMA to suit different trading styles. Price Source: Select the price data for MA calculations (e.g., close, open, etc.). Display Toggle: Enable or disable specific MAs to optimize chart clarity. Color Settings: Customize the color and thickness of each MA line. How to UseAdd the indicator to your chart. Adjust periods, MA type, price source, and colors in the settings panel. Develop trading strategies based on MA crossovers, trends, or support/resistance levels. Save your chart layout to retain personalized settings. NotesAdjust MA periods based on your timeframe (e.g., shorter periods for intraday trading, longer periods for long-term trends). Too many MAs may clutter the chart; use the display toggle to streamline the view. Test different MA types (SMA, EMA, WMA) to find the best fit for your strategy. Release NotesVersion: Pine Script v5 Target Audience: Suitable for technical analysts in stocks, forex, cryptocurrencies, and other markets. Feedback: Share your experience or suggestions in the comments to help improve the indicator!
Pine Script® indicator
by OxZephyr
Ethereum Logarithmic Regression BandsOverview This indicator displays logarithmic regression bands for Ethereum. Logarithmic regression is a statistical method used to model data where growth slows down over time. I initially created these bands in 2021 using a spreadsheet, and later coded them in TradingView in 2022. Over time, the bands proved effective at capturing bull market peaks and bear market lows. In 2025, I decided to share this indicator because I believe these logarithmic regression bands offer the best fit for the Ethereum chart. How It Works The logarithmic regression lines are fitted to the Ethereum (ETHUSD) chart using two key factors: the 'a' factor (slope) and the 'b' factor (intercept). The formula for logarithmic regression is 10^((a * ln) - b). How to Use the Logarithmic Regression Bands 1. Lower Band: The lower (blue) band forms a potential support area for Ethereum’s price. Historically, Ethereum has found its lows within this band during past market cycles. When the price is within the lower band, it suggests that Ethereum is undervalued. 2. Upper Band: The upper (red) band forms a potential resistance area for Ethereum’s price. The logarithmic band is fitted to the past two market cycle peaks; therefore, there is not enough historical data to be sure it will reach the upper band again. However, the chance is certainly there! If the price is within the upper band, it indicates that Ethereum is overvalued and that a potential price correction may be imminent.
Pine Script® indicator
by CryptoRiskAlert
ANAND RSI&HAHow to Set Up Alerts in TradingView: Apply the indicator to your chart Right-click on the chart → "Add Alert" Choose your preferred alert condition: "HA-RSI Buy/Sell Alerts" (combined) "HA-RSI Buy Alert" (buy only) "HA-RSI Sell Alert" (sell only) Set your notification preferences (popup, email, webhook, etc.) Alert Messages Include: Clear BUY/SELL indication with colored emojis (🟢/🔴) Ticker symbol Current price Descriptive message about the signal
Pine Script® indicator
by ramrajenterprises
Multi-Layer Volume Profile [Mark804]Multi-Layer Volume Profile – Advanced Volume-by-Price Analysis for Trading Precision Multi-Layer Volume Profile is a powerful and free TradingView® Pine Script® indicator that offers a multi-horizon view of market volume dynamics. By stacking up to four distinct volume profiles—Full Period, Half-Length, Quarter-Length, and One-Eighth-Length—it enables traders to detect structural confluence across timeframes with ease and clarity Key Features: Layered Volume Breakdown: Each profile represents a different lookback duration. This layered approach helps identify overlapping patterns like POCs (Points of Control) across timescales—critical for spotting strong support/resistance levels. Custom Bin Resolution: Offers adjustable bin granularity—from highly detailed (many bins) to smoother overview (fewer bins)—tailoring visual clarity to your strategy. Precise POC Highlighting: The Point of Control—where trading volume peaks—is displayed as a thick blue line, serving as a focal anchor for trade decisions Volume Labels & Delta: Each profile shows: Total Volume: Cumulative trade volume for the profile range. Delta Volume: Buyers minus sellers, indicating directional bias (positive = bullish, negative = bearish) Range Boundaries: Clearly defined high and low price lines for each layer mark zones of potential price reaction, acting as dynamic support/resistance levels Suggested Use Cases: Identify Acceptance Zones: Dense, “thick” volume areas where the market reached consensus—ideal for building positions or entries Spot Rejection Areas: Sparse volume bands that often signal price will be rejected—excellent for stop placements or breakout entries Delta Confirmation: Use volume delta to confirm the strength and direction of potential breakouts or reversals Multi-Timeframe Confluence: Overlapping POC levels across layers highlight robust zones of support/resistance, enhancing confidence in trade setups
Pine Script® indicator
by Mark804
Global Bond Yields Monitor [MarktQuant]Global Bond Yields Monitor The Global Bond Yields Monitor is designed to help users track and compare government bond yields across major economies. It provides an at-a-glance view of short- and long-term interest rates for multiple countries, enabling users to observe shifts in global fixed-income markets. Key Features: Multi-Country Coverage: Includes major advanced and emerging economies such as the United States, China, Japan, Germany, United Kingdom, Canada, Australia, and more. Multiple Maturities: Displays yields for the 2-year, 5-year, 10-year, and 30-year maturities (20-year for Russia). Dynamic Yield Data: Plots real-time yields for the selected country directly from TradingView’s data sources. Weekly Change Tracking: Calculates and displays the yield change from one week ago ( ) for each maturity. Table Visualization: Option to display a compact data table showing current yields and weekly changes, color-coded for easier interpretation. Visual Yield Curve Comparison: Plots yield lines for short- and long-term maturities, with shaded areas between curves for visual clarity. Customizable Display: Choose table placement and whether to show or hide the weekly change table. Use Cases This script is intended for analysts, traders, and investors who want to monitor shifts in sovereign bond markets. Changes in yields can reflect adjustments in monetary policy expectations, inflation outlook, or broader macroeconomic trends. ❗Important Note❗ This indicator is for market monitoring and educational purposes only. It does not generate trading signals, and it should not be interpreted as financial advice. All data is sourced from TradingView’s available market feeds, and accuracy may depend on the source data.
Pine Script® indicator
by MarktQuant
Breakout Squeeze – Early Detector (BRK-SQZ) What it does Squeeze — price goes quiet (Bollinger Band Width compresses vs its recent average). Fuel — volume expands vs its 20-bar average. Level — price takes out a recent high. Quality — the close is near the top of the candle’s range. When those stack up you get a signal. You can choose Strict (safer, later) or Early (faster, noisier). What you’ll see on the chart Blue background → in a squeeze (coiled). Orange dots (bottom) → volume currently above threshold. Green tiny caret (above bar) → price is testing/clearing the breakout level. Aqua diamond labeled “PRE” (above bar) → Pre-Signal (any 3 of 4 checks are true). Early heads-up. Lime triangle “BRK” (below bar) → Confirmed Long breakout (all 4 checks pass). Tip: PRE can fire intrabar for early notice. The BRK triangle is your confirmation. Inputs (the only knobs that matter) Early (default): high or close can break the level; looser volume/close filters. Strict: close must break the level; stronger volume/close placement. Core BB Length (20), BB Mult (2.0) Squeeze Lookback (40) — moving average window for BB Width. Squeeze Threshold (sqzFactor) (0.60) — lower = tighter squeeze requirement. Breakout Breakout Lookback (brkLen) (20) — new high must clear the prior N bars. Volume Volume SMA Length (20) Volume Spike ≥ (Early/Strict) (1.5 / 2.0) — multiplier vs avg volume. Candle Quality Close-in-Range (Early/Strict) (0.65 / 0.80) — 0.80 = close in top 20% of bar. Options Fire intrabar (ON = earlier PRE/BRK; OFF = bar-close only). Plot Signal Labels (on/off). Debug paints (show/hide squeeze tint, volume dots, breakout carets, PRE). Alerts (set these, you’re done) Create two alerts from the indicator’s Condition dropdown: BRK-SQZ Pre-Signal Trigger: Once per bar (for early pings). Purpose: tells you the coil is heating up before the rip. BRK-SQZ Long Trigger: Once per bar close (clean confirmation) or Once per bar if you want it faster. Purpose: confirms the breakout when all checks align. How to trade it (framework, not rules) First touch after a long squeeze is the highest-odds signal. On Daily, manage risk with ATR or a structure stop under the base. Scale out into strength; let a runner ride if the squeeze was multi-week. Installation (60 seconds) Add indicator. Keep Mode = Early, Fire intrabar = ON. Set alerts for Pre-Signal (Once per bar) and Long (Once per bar close). Save inputs as a Template and apply across your watchlist. FAQ Q: Why did PRE fire but no BRK? A: One of the four checks failed at close (often volume or close-placement). That’s the filter doing its job. Q: I want even earlier signals. A: Lower volMult_early, reduce brkLen, or enable intrabar signals. Expect more noise. Q: Can I get bearish signals? A: Not yet. I can ship a mirrored Breakdown version on request. Q: Can I screen a whole watchlist? A: This version is chart-based. I can add a mini screener panel with a consolidated alert if you want. Changelog v6.1 — Early/Strict modes, PRE (3-of-4), squeeze tint, volume dots, breakout carets, BRK triangle, intrabar option, two alert conditions. Disclaimer This is a tool, not advice. Markets slip, wick, and change regime. Size responsibly and test your settings on your market/timeframe.
Pine Script® indicator
by ictc3d
1
Range Trends Enhanced (eleven11)This indicator automatically draws your Range Trend lines based upon your timeframe. When you select a timeframe, in the options, those lines will be locked in, whenever you switch timeframes on the chart. This allows you to "lock in" a timeframe's trendlines and then view it on different timeframes. But if you want to view the current trendlines for a timeframe then you need to select that "lockdown" timeframe in the settings. The original code was created by eleven11
Pine Script® indicator
by walkerg1973
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.
Pine Script® indicator
by Master-Jedi-Trader
EMA Deviation with Min/Max Levelshis indicator visualizes the percentage deviation of the closing price from its Exponential Moving Average (EMA), helping traders identify overbought and oversold conditions. It dynamically tracks the minimum and maximum deviation levels over a user-defined lookback period, highlighting extreme zones with color-coded signals: • 🔵 Normal deviation range • 🔴 Near historical maximum — potential sell zone • 🟢 Near historical minimum — potential buy zone Use it to spot price extremes relative to trend and anticipate possible reversals or mean reversion setups.
Pine Script® indicator
by Trade_Hive_Signals