Position Sizing Calculator with ADR%, Account %, and RSILET ME KNOW IN COMMENTS IF YOU HAVE ANY ISSUES!
Overview
The Position Sizing Calculator with ADR% + RSI is a indicator that helps traders calculate position sizes based on risk management parameters (stop loss at low of day). It uses a fixed percentage of the account size, risk per trade, and stop loss distance (current price minus daily low) to determine the number of shares or contracts to trade. Additionally, it displays the Average Daily Range (ADR) as a percentage, the Relative Strength Index (RSI), and the price’s percentage distance from the daily low in a real-time table.
Features
Position Sizing: Calculates position size based on a fixed account percentage, risk per trade, and stop loss distance, ensuring the position value stays within the allocated capital.
ADR% Display: Shows the ADR as a percentage of the daily low, colored green if >5% or red if ≤5%.
RSI Display: Shows the RSI, colored green if oversold (<30), red if overbought (>70), or gray otherwise.
Distance from Low: Displays the current price’s percentage distance from the daily low for context.
Real-Time Table: Presents all metrics in a top-right table, updating in real-time.
Position Value Cap: Ensures the position value doesn’t exceed the allocated capital.
Minimum Stop Loss: Prevents oversized positions due to very small stop loss distances.
Customizable Parameters
Account Size ($): Set the total account balance (default: $1,000, min: $100, step: $100).
Risk Per Trade (%): The percentage of allocated capital to risk per trade (default: 1%, range: 0.1% to 10%, step: 0.1%).
Max % of Account: The fixed percentage of the account to allocate for the trade (default: 50%, range: 10% to 100%, step: 1%).
ADR Period: The number of days to calculate the ADR (default: 14, min: 1, step: 1).
RSI Length: The period for RSI calculation (default: 14, min: 1, step: 1).
Min Stop Loss Distance ($): The minimum stop loss distance to prevent oversized positions (default: $0.01, min: $0.001, step: $0.001).
Calculations
Stop Loss Distance: Current price minus daily low, with a minimum value set by the user.
Position Size: (Account Size * Max % of Account * Risk Per Trade %) / Stop Loss Distance, capped so the position value doesn’t exceed the allocated capital.
ADR%: 100 * (SMA(daily high / daily low, ADR Period) - 1), reflecting the average daily range relative to the low.
RSI: Calculated using the smoothed average of gains and losses over the RSI period, with special handling for zero gains or losses.
Distance from Low: (Current Price - Daily Low) / Daily Low * 100.
Table Display
Account Size: The input account balance.
Risk Per Trade: The risk percentage.
Stop Loss Distance: The price difference between the current price and daily low.
Distance from Low: The percentage distance from the daily low.
Account % Used: The fixed percentage of the account allocated.
Position Size: The calculated number of shares or contracts.
Position Value: The position size multiplied by the current price.
ADR %: The ADR percentage, colored green (>5%) or red (≤5%).
RSI: The RSI value, colored green (<30), red (>70), or gray (30–70).
Usage
Ideal for traders managing risk by allocating a fixed portion of their account and sizing positions based on stop loss distance.
The ADR% and RSI provide market context, with color coding to highlight high volatility or overbought/oversold conditions.
Adjust the customizable parameters to fit your trading style, such as increasing the risk percentage for aggressive trades or adjusting the ADR/RSI periods for different time horizons.
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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.
Breakouts with Trailing Stops V6 + AlertsBreakouts with Trailing Stops in Trading
Breakout trading is a strategy where traders aim to profit from an asset's price moving outside a defined support or resistance level, signaling a potential new trend. Trailing stops are a key risk management tool often used with breakouts to protect profits and limit potential losses.
What is a breakout?
A breakout occurs when an asset's price moves decisively above a resistance level (for a bullish breakout) or below a support level (for a bearish breakdown). This often signals increased momentum and potential for a significant price movement in the direction of the breakout.
Why use trailing stops with breakouts?
Trailing stops are particularly useful in breakout trading because they allow traders to capture potential profits as the price moves in their favor, while automatically adjusting to protect against sudden reversals.
How do trailing stops work with breakouts?
Initial Stop-Loss: When entering a breakout trade, a traditional stop-loss order is placed at a predetermined level to limit potential losses if the price reverses. For example, in a long position after a resistance breakout, the initial stop-loss might be placed below the former resistance level (which can now act as support).
Trailing Stop Activation: Once the price moves a favorable distance beyond the entry point, the trailing stop loss is activated. As highlighted by StoneX, it is a dynamic order that follows the price as it continues to move in the desired direction, maintaining a set distance below (for a long position) or above (for a short position) the current market price.
Profit Locking: If the price continues to rise (or fall for a short position), the trailing stop will move with it, "locking in" profits by raising the stop-loss level.
Exit Strategy: If the price reverses and hits the trailing stop, the position is automatically closed, ensuring that the trader retains a portion of the gains made while in the trade.
Advantages of using trailing stops with breakouts:
Locks in profits: Trailing stops help protect profits generated from successful breakout trades.
Automates exits: They automate the exit process, helping traders avoid emotional decision-making when the price reverses.
Allows for potential gains: They allow traders to stay in profitable trades as long as the trend continues.
Disadvantages of using trailing stops with breakouts:
Whipsaw risk: In volatile markets, the trailing stop may be triggered prematurely by minor price fluctuations.
Potential for missed gains: If the trailing stop is set too tightly, it may prevent the trader from capturing the maximum potential gains if the price experiences a minor pullback before continuing in the desired direction.
Tips for using trailing stops with breakouts:
Consider the asset's volatility: Adjust the trailing stop distance based on the asset's volatility to minimize the risk of premature stops.
Test different trailing stop methods: Experiment with different trailing stop methods to find what works best for your trading style and the specific asset you are trading.
Backtest your strategy: Before applying a trailing stop strategy to live trading, backtest it on historical data to evaluate its performance under different market conditions.
Combine with other indicators: Use other technical indicators, such as volume or momentum oscillators, to confirm the validity of breakouts and improve the effectiveness of your trailing stop strategy.
By carefully considering the market dynamics, using appropriate indicators, and implementing proper risk management techniques, traders can effectively utilize trailing stops with breakouts to capture potential profits while minimizing risk.
Have a good trade.
Canuck Trading Trader StrategyCanuck Trading Trader Strategy
Overview
The Canuck Trading Trader Strategy is a high-performance, trend-following trading system designed for NASDAQ:TSLA on a 15-minute timeframe. Optimized for precision and profitability, this strategy leverages short-term price trends to capture consistent gains while maintaining robust risk management. Ideal for traders seeking an automated, data-driven approach to trading Tesla’s volatile market, it delivers strong returns with controlled drawdowns.
Key Features
Trend-Based Entries: Identifies short-term trends using a 2-candle lookback period and a minimum trend strength of 0.2%, ensuring responsive trade signals.
Risk Management: Includes a configurable 3.0% stop-loss to cap losses and a 2.0% take-profit to lock in gains, balancing risk and reward.
High Precision: Utilizes bar magnification for accurate backtesting, reflecting realistic trade execution with 1-tick slippage and 0.1 commission.
Clean Interface: No on-chart indicators, providing a distraction-free trading experience focused on performance.
Flexible Sizing: Allocates 10% of equity per trade with support for up to 2 simultaneous positions (pyramiding).
Performance Highlights
Backtested from March 1, 2024, to June 20, 2025, on NASDAQ:TSLA (15-minute timeframe) with $1,000,000 initial capital:
Net Profit: $2,279,888.08 (227.99%)
Win Rate: 52.94% (3,039 winning trades out of 5,741)
Profit Factor: 3.495
Max Drawdown: 2.20%
Average Winning Trade: $1,050.91 (0.55%)
Average Losing Trade: $338.20 (0.18%)
Sharpe Ratio: 2.468
Note: Past performance is not indicative of future results. Always validate with your own backtesting and forward testing.
Usage Instructions
Setup:
Apply the strategy to a NASDAQ:TSLA 15-minute chart.
Ensure your TradingView account supports bar magnification for accurate results.
Configuration:
Lookback Candles: Default is 2 (recommended).
Min Trend Strength: Set to 0.2% for optimal trade frequency.
Stop Loss: Default 3.0% to cap losses.
Take Profit: Default 2.0% to secure gains.
Order Size: 10% of equity per trade.
Pyramiding: Allows up to 2 orders.
Commission: Set to 0.1.
Slippage: Set to 1 tick.
Enable "Recalculate After Order is Filled" and "Recalculate on Every Tick" in backtest settings.
Backtesting:
Run backtests over March 1, 2024, to June 20, 2025, to verify performance.
Adjust stop-loss (e.g., 2.5%) or take-profit (e.g., 1–3%) to suit your risk tolerance.
Live Trading:
Use with a compatible broker or TradingView alerts for automated execution.
Monitor execution for slippage or latency, especially given the high trade frequency (5,741 trades).
Validate in a demo account before deploying with real capital.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
LotSize CalculatorLotSize Calculator Documentation
Overview
The LotSize Calculator is a powerful TradingView indicator designed to help traders calculate optimal position sizes based on risk management principles. It provides a visual representation of trade setups, including entry points, stop losses, and take profits, while calculating the appropriate lot size based on your risk preferences.
Key Features
Automatic lot size calculation based on risk amount
Support for multiple asset classes (forex, commodities, indices, etc.)
Visual R-multiple levels (1R to 5R)
Real-time position tracking with drawdown and run-up statistics
Customizable visual elements and display options
Input Parameters
Risk Management Settings
Risk Amount Type: Choose between risking a fixed amount in dollars ($) or a specific lot size.
Risk Amount: The amount you want to risk on the trade (in dollars if Risk Amount Type is set to $, or in lots if set to Lots).
Overwrite TP: Optional setting to automatically set take profit at a specific R-multiple (1R, 2R, 3R, 4R, or 5R).
Table Comments: Optional field to add personal notes to the position table.
Trade Setup Levels
Trigger Price: The price at which your trade will be entered.
Stop Loss: Your predetermined exit price to limit losses.
Take Profit: Your target price to secure profits.
Time Of Setup Start Bar: The starting time for your trade setup window.
Display Settings
Plot Position Labels: Toggle to show/hide position information labels on the chart.
Plot Position Table: Toggle to show/hide the position information table.
Show Money: Toggle to display monetary values ($) in the labels and table.
Show Points: Toggle to display point values in the labels and table.
Show Ticks: Toggle to display tick values in the labels and table.
Visual Appearance
Entry Color: Color for entry level line and labels.
Take Profit Color: Color for take profit level line and labels.
Stop Loss Color: Color for stop loss level line and labels.
Label Text Color: Color for text in the position labels.
Table Background: Background color for the position information table.
Table Text: Text color for the position information table.
R Labels: Color for the R-multiple level labels.
Table Position: Position of the information table on the chart (options: Bottom Right, Bottom Left, Bottom Middle, Top Right, Top Middle).
How to Use
Basic Setup
Set your entry price in the "Trigger Price" field.
Set your stop loss level in the "Stop Loss" field.
Set your take profit level in the "Take Profit" field.
Choose your risk amount type ($ or Lots) and enter the risk amount.
Optionally, select an R-multiple for automatic take profit calculation.
Understanding the Display
The indicator will show:
Horizontal lines for entry, stop loss, and take profit levels
Colored zones between entry and take profit (potential profit zone) and between entry and stop loss (potential loss zone)
R-multiple levels based on your risk (1R, 2R, 3R, 4R, 5R)
A table displaying:
Position type (long/short) and size
Original risk and reward figures
Maximum run-up and drawdown during the trade
Trade Monitoring
Once a trade is triggered (either by price crossing a stop entry or reaching a limit entry), the indicator tracks:
Current position value
Maximum run-up (highest profit seen)
Maximum drawdown (largest loss seen)
Trade outcome when take profit or stop loss is hit
Advanced Features
Asset Type Detection
The LotSize Calculator automatically detects the type of asset being traded (forex, commodity, index, etc.) and adjusts calculations accordingly to ensure accurate position sizing.
R-Multiple Visualization
R-multiples help visualize potential reward relative to risk. For example, 2R means the potential reward is twice the amount risked. The indicator displays these levels directly on your chart for easy reference.
Adaptive Position Labels
Position labels adjust their display based on trade direction (long or short) and include relevant information about risk, reward, and current position status.
Best Practices
Always confirm your risk is appropriate for your account size (typically 1-2% of account per trade).
Use the R-multiple visualization to ensure your trades offer favorable risk-to-reward ratios.
The indicator works best when used alongside your existing strategy for entry and exit signals.
Customize the visual appearance to match your chart theme for better visibility.
Troubleshooting
If position calculations seem incorrect, verify that the indicator is detecting the correct instrument type.
For forex pairs, ensure your broker's lot size conventions match those used by the indicator.
The indicator may need adjustment for certain exotic instruments or markets with unusual tick sizes.
PRO Strategy 3TP (v2.1.1)
English Version
PRO Strategy 3TP (v2.1.1) — Comprehensive Guide for TradingView
Strategy Concept & Uniqueness
The PRO Strategy 3TP is a trading system designed to follow market trends using a combination of tools that check trends across different timeframes, measure momentum, and manage risks smartly. Its standout feature is a three-step profit-taking system (hence "3TP") and its ability to adjust to market ups and downs, helping traders make the most of strong trends while keeping losses low in choppy markets.
Why It’s Special:
✅ Three Profit Levels: Takes profit in stages—33% at the first target (TP1), 33% at the second (TP2), and 34% at the third (TP3)—so you lock in gains gradually.
✅ Risk-Free After TP1: Once the first profit target is hit, the stop-loss moves to your entry price, meaning no more risk on the trade.
✅ Smarter Signals: Uses data from a higher timeframe (like 1-hour) to filter out false moves on your chart (like 15-minutes).
How It Works
The strategy uses four main tools to decide when to enter and exit trades. Here’s what they do in simple terms:
Trend Tools (EMA, HMA, SMA)
EMA (Exponential Moving Average): A line that tracks the price trend, reacting quickly to recent changes. Think of it as a fast guide to where the market’s heading.
Default: EMA 100 (looks at the last 100 bars).
HMA (Hull Moving Average): A smoother, faster-moving line that spots trend shifts earlier than most averages.
Default: HMA 50 (looks at the last 50 bars).
SMA (Simple Moving Average): A basic average of prices over time, great for seeing the big picture (bull or bear market).
Default: SMA 200 (looks at the last 200 bars).
How It Helps: These lines work together to make sure the trend is real across short, medium, and long terms.
Momentum Tool (CCI)
CCI (Commodity Channel Index): Tells you if the market is “overbought” (too high, ready to drop) or “oversold” (too low, ready to rise).
Buy when CCI < -100 (oversold).
Sell when CCI > +100 (overbought).
How It Helps: It picks the best moments to jump into a trade when prices are at extremes.
Trend Strength Tool (ADX)
ADX (Average Directional Index): Measures how strong a trend is. Higher numbers mean a stronger trend.
Default: ADX > 26 (only trades when the trend is strong enough).
How It Helps: Keeps you out of flat, boring markets where prices don’t move much.
Volatility Tool (ATR)
ATR (Average True Range): Shows how much the price typically moves up or down. It’s like a ruler for market “wiggle room.”
Default: ATR over 19 bars, used to set stop-loss (5x ATR) and profit targets (1x, 1.3x, 1.7x ATR).
How It Helps: Adjusts your trade exits based on how wild or calm the market is.
Entry Rules
Buy (Long): Price is above EMA, HMA, and SMA (checked on a higher timeframe) + CCI < -100 + ADX > 26.
Sell (Short): Price is below EMA, HMA, and SMA + CCI > +100 + ADX > 26.
Exit Rules
Stop-Loss: Set at 5x ATR away from your entry (e.g., if ATR is 10 points, stop-loss is 50 points away).
Breakeven: After TP1 is hit, stop-loss moves to your entry price—no more risk!
Profit Targets:
TP1: 1x ATR (closes 33% of your position).
TP2: 1.3x ATR (closes 33%).
TP3: 1.7x ATR (closes 34%).
Why This Mix Works
Fewer Mistakes: Checking trends on multiple timeframes cuts out 60-70% of bad signals (based on tests).
Adapts to the Market: ATR adjusts your stops and targets as the market changes—super useful for volatile assets like crypto.
Balanced Wins: The three-step profit system locks in gains early but lets you ride big trends too.
Setup Guide
Settings for Different Styles
Parameter Scalping (1-15M) Swing (1H-4H) Position (Daily)
EMA/HMA/SMA 50/20/Off 100/50/200 Off/Off/200
ADX Threshold 20 26 25
ATR Multipliers SL=3x, TP3=2x SL=5x SL=6x
Position Size
Formula: Contracts = Risk Amount / (Stop-Loss Distance × Value per Point)
Example: Risking $100, stop-loss is 50 points, each point = $2 → Trade 1 contract.
Multi-Timeframe Tip
Chart: 15-minute
Indicators: 1-hour
Rule: Only trade if the 15-minute price matches the 1-hour trend.
Why Use It?
Proven Results: 58-62% win rate on assets like Bitcoin, Ethereum, and S&P 500 (tested 2020-2023). Risk-to-reward ratio of 1.8-2.3.
Saves Time: Alerts tell you when to enter or exit—no need to watch the screen all day.
Flexible: Works for fast scalping, medium swing trades, or long-term positions.
FAQ
Why no trailing stop?
Trailing stops cut profits by 15-20% in tests because they exit too early. The breakeven stop protects your money better.
What about news events?
Use a bigger ATR (e.g., 50) and wider stop-loss (6x ATR) when markets get crazy.
Can I trade forex?
Yes! Try EMA=50, HMA=20, ATR=14 on EUR/USD 15-minute charts.
Risk Management
Risk per Trade: Stick to 1-2% of your account.
Weekly Check: Adjust ATR and stop-loss every Friday to match market conditions.
Emergency Plan: Manually move your stop-loss if something wild (like a “black swan” event) happens.
⚠️ Warning: Trading is risky. This strategy doesn’t promise profits. Always use a stop-loss.
Русская версия
Стратегия PRO 3TP (v2.1.1) — Полное руководство для TradingView
Концепция и уникальность
PRO Strategy 3TP — это система, которая следует за трендами на рынке, используя проверку трендов на разных таймфреймах, измерение импульса и умное управление рисками. Главная фишка — трехступенчатая фиксация прибыли (поэтому "3TP") и адаптация к изменениям на рынке, чтобы зарабатывать больше в сильных трендах и терять меньше в нестабильные времена.
Почему она особенная:
✅ Три уровня прибыли: Закрывает 33% на первом уровне (TP1), 33% на втором (TP2) и 34% на третьем (TP3) — прибыль фиксируется постепенно.
✅ Без риска после TP1: После первого уровня стоп-лосс сдвигается на точку входа — дальше риска нет.
✅ Умные сигналы: Использует данные с более старшего таймфрейма (например, 1 час) для фильтрации шума на вашем графике (например, 15 минут).
Как это работает
Стратегия использует четыре основных инструмента для входа и выхода из сделок. Вот что они значат простыми словами:
Инструменты тренда (EMA, HMA, SMA)
EMA (Экспоненциальная скользящая средняя) : Линия, которая следит за трендом и быстро реагирует на последние цены. Это как быстрый указатель направления рынка.
По умолчанию: EMA 100 (смотрит на последние 100 баров).
HMA (Скользящая средняя Халла): Более плавная и быстрая линия, которая раньше замечает смену тренда.
По умолчанию: HMA 50 (смотрит на последние 50 баров).
SMA (Простая скользящая средняя) : Просто средняя цена за период, показывает общую картину (быки или медведи).
По умолчанию: SMA 200 (смотрит на последние 200 баров).
Зачем это нужно: Эти линии вместе проверяют, что тренд настоящий на коротких, средних и длинных периодах.
Инструмент импульса (CCI)
CCI (Индекс товарного канала): Показывает, когда рынок “перекуплен” (слишком высоко, готов упасть) или “перепродан” (слишком низко, готов расти).
Покупка: CCI < -100 (перепродан).
Продажа: CCI > +100 (перекуплен).
Зачем это нужно: Помогает выбрать лучшее время для входа, когда цены на крайних значениях.
Инструмент силы тренда (ADX)
ADX (Индекс среднего направленного движения): Измеряет, насколько силен тренд. Чем выше число, тем сильнее движение.
По умолчанию: ADX > 26 (торгуем, только если тренд сильный).
Зачем это нужно: Не дает торговать, когда рынок стоит на месте и скучный.
Инструмент волатильности (ATR)
ATR (Средний истинный диапазон): Показывает, насколько сильно цена обычно “гуляет” вверх-вниз. Это как линейка для рыночных колебаний.
По умолчанию: ATR за 19 баров, стоп-лосс = 5x ATR, цели прибыли = 1x, 1.3x, 1.7x ATR.
Зачем это нужно: Настраивает выход из сделки в зависимости от того, насколько рынок спокоен или хаотичен.
Правила входа
Покупка (Лонг): Цена выше EMA, HMA и SMA (проверяется на старшем таймфрейме) + CCI < -100 + ADX > 26.
Продажа (Шорт): Цена ниже EMA, HMA и SMA + CCI > +100 + ADX > 26.
Правила выхода
Стоп-лосс: Устанавливается на 5x ATR от входа (например, если ATR = 10 пунктов, стоп = 50 пунктов).
Безубыток: После TP1 стоп-лосс сдвигается на цену входа — риска больше нет!
Цели прибыли:
TP1: 1x ATR (закрывает 33% позиции).
TP2: 1.3x ATR (закрывает 33%).
TP3: 1.7x ATR (закрывает 34%).
Почему эта комбинация работает
Меньше ошибок: Проверка тренда на разных таймфреймах убирает 60-70% ложных сигналов (по тестам).
Подстраивается под рынок: ATR меняет стопы и цели в зависимости от условий — важно для активов вроде крипты.
Умная прибыль: Трехступенчатая система фиксирует выгоду рано, но оставляет шанс заработать на большом тренде.
Как настроить
Настройки для разных стилей
Параметр Скальпинг (1-15М) Свинг (1H-4H) Долгосрок (Daily)
EMA/HMA/SMA 50/20/Выкл 100/50/200 Выкл/Выкл/200
Порог ADX 20 26 25
Множители ATR SL=3x, TP3=2x SL=5x SL=6x
Размер позиции
Формула: Контракты = Риск / (Расстояние до стоп-лосса × Стоимость пункта)
Пример: Риск $100, стоп-лосс 50 пунктов, 1 пункт = $2 → 1 контракт.
Совет по таймфреймам
График: 15 минут
Индикаторы: 1 час
Правило: Торгуй, только если тренд на 15 минутах совпадает с 1 часом.
Зачем это использовать?
Проверено: 58-62% успешных сделок на BTC, ETH, S&P 500 (тесты 2020-2023). Соотношение риск/прибыль 1.8-2.3.
Экономит время: Оповещения скажут, когда входить и выходить — не надо сидеть у экрана.
Гибкость: Подходит для быстрой торговли, среднесрочной и долгосрочной.
Часто задаваемые вопросы
Почему нет трейлинг-стопа?
Тесты показали, что он снижает прибыль на 15-20%, потому что выходит слишком рано. Безубыток лучше защищает деньги.
Что делать с новостями?
Увеличьте ATR (например, до 50) и стоп-лосс (6x ATR), когда рынок штормит.
Можно торговать форекс?
Да! Используйте EMA=50, HMA=20, ATR=14 для EUR/USD на 15 минутах.
Управление рисками
Риск на сделку: Не больше 1-2% от депозита.
Проверка раз в неделю: Обновляйте ATR и стоп-лосс каждую пятницу под рынок.
План на экстрим: Если происходит что-то необычное (например, “черный лебедь”), вручную двигайте стоп-лосс.
⚠️ Предупреждение: Торговля — это риск. Стратегия не гарантирует прибыль. Всегда ставьте стоп-лосс.
Flux Charts - SFX Screener💎 GENERAL OVERVIEW
The SFX Screener by Flux Charts is a multi-timeframe market scanner that extracts and visually organizes key conditions detected by the SFX Algo indicator across multiple assets in real-time. It does not perform independent analysis or generate new signals—instead, it pulls data directly from the SFX Algo’s calculations to ensure full alignment across different timeframes and tickers.
The SFX Algo is a multi-factor trading indicator that integrates trend analysis, signal generation, market overlays, and take-profit/stop-loss levels into a single system. It evaluates multiple trend components, including EMA direction, momentum shifts, and volatility cycles, to determine market conditions. Signal generation is based on an Adjusted Weighted Majority Algorithm, filtering out weaker signals by prioritizing the most reliable market indicators. Market overlays, such as Volatility Bands and the Retracement Wave, provide dynamic support, resistance, exit points, and entry points. Its adaptable structure allows traders to customize settings based on strategy preferences, making it effective for scalping, swing trading, and long-term trend analysis.
The SFX Screener’s purpose is to give traders a dashboard view of these SFX Algo signals across multiple tickers and timeframes in real-time.
📌 HOW DOES IT WORK ?
The SFX Algo indicator employs an Adjusted Weighted Majority algorithm to generate "buy" and "sell" signals. It evaluates multiple market indicators ("experts"), including momentum, ATR trends, and EMA trends, and assigns weights based on their recent performance. The "Time Weighting" setting allows users to balance between using more historical data or prioritizing recent trends. Unlike traditional weighted majority methods, SFX also dynamically penalizes larger losses. Signals are confirmed based on the consensus of the most successful indicators within the selected time period, filtering out weaker signals during underperforming phases.
The SFX Screener extracts these calculated outputs and visually organizes them into a real-time dashboard. Each signal, status, and volatility condition displayed in the screener is a direct output from the SFX Algo indicator.
🚩 UNIQUENESS
Unlike traditional screeners that rely on preset filters or static conditions, the SFX Screener dynamically updates its dashboard based on live outputs from the SFX Algo’s adaptive algorithm.
Traditional Screeners → Use predefined filters like “price above EMA” or “RSI overbought.” They do not adjust to market dynamics.
SFX Screener → Displays outputs directly from an adaptive algorithm that continuously evaluates trends, volatility, and momentum changes.
The SFX Screener can show SFX Algo's status on 8 different tickers on different timeframes. Key factors that make it unique include:
✅ Real-time sync with SFX Algo → Displays live conditions, not static filters.
✅ Comprehensive Dashboard – This screener provides a complete and customizable dashboard designed to enhance traders' decision-making by consolidating crucial SFX Algo insights into one user-friendly interface.
✅ Multi-Ticker & Multi-Timeframe Analysis – With support for up to 8 tickers and timeframes, traders can effortlessly analyze the bigger market picture, identifying trends and opportunities across different assets and timeframes.
By combining multiple analytical elements in a single view, this screener empowers traders with the insights needed to navigate the market more effectively.
🎯 SFX SCREENER FEATURES:
SFX Algo Signals : This tool can detect SFX Algo signals across different tickers & timeframes.
Volatility Bands : Detection of Volatility Bands Status & Retests.
Retracement Wave : Detection of Retracement Wave Status & Retests.
Highly Configurable : Offers multiple parameters for fine-tuning detection settings.
Up to 8 Tickers : Allows traders to analyze multiple tickers & timeframes simultaneously for enhanced accuracy.
📊 SFX SCREENER DATA BREAKDOWN
Signal ->
Buy -> The latest signal is a buy signal.
Sell -> The latest signal is a sell signal.
The rating of the signal is shown after the signal type.
Δ⭐ ->
Shows the rating change (delta) after the signal is triggered. Positive values mean that the rating is increased after the signal is given, negative values mean that it's decreased.
Status ->
Displays the amount of time passed after the signal is given.
TP Targets ->
Shows the Take-Profit targets of the signal, if a target was achieved, there is a ✅ symbol near it and the next target it displayed.
V. Bands ->
The Volatility Bands dynamically adjust to market conditions, expanding during high volatility and contracting during low volatility. When the volatility bands are tight, or the upper and lower bands are close to each other, the market is not volatile. During periods of low volatility, it’s common for price to consolidate or move sideways. An early indication of a large price move can occur when the bands widen or open up after being tight. When the volatility bands are wide, it reflects a period of increased volatility, typically during strong price trends or after a breakout. The volatility bands can also act as support and resistance areas. The upper band acts as resistance while the lower band acts as support. These mark out good areas for potential reversals. Breakouts can also occur when price moves beyond the bands, signaling a potential trend in the breakout direction.
Outside -> The price is currently outside of the Volatility Bands.
Inside | Upper -> The price is currently inside the Upper Volatility Band.
Inside | Lower -> The price is currently inside the Lower Volatility Band.
R. Wave ->
The Retracement Wave is used to identify entry points during pullbacks in trending markets. It can also be used to find exit points for open trades. The wave is bullish when price is above it and bearish when the price is below it. The retracement wave can be used as an area to enter during a pullback in a trending market. The wave can also be helpful for managing risk and closing out positions.
Outside | Bullish -> The Retracement Wave is currently Bullish, and the price is outside of it.
Outside | Bearish -> The Retracement Wave is currently Bearish, and the price is outside of it.
Inside | Bullish -> The Retracement Wave is currently Bullish, and the price is inside of it.
Inside | Bearish -> The Retracement Wave is currently Bearish, and the price is inside of it.
Profit & Loss (P&L) ->
Shows the amount of profit or loss the position is currently in. All values are shown in terms of percentage, and positive values mean the position is in profit while negative values mean that the position is in loss.
⚠ Timeframe Restriction : The selected timeframes for analysis cannot be lower than the chart’s current timeframe to ensure proper data alignment.
⏰ ALERTS
This screener supports alerts, so you never miss a key market move. You can choose to receive alerts when a buy or sell signal is given, helping you spot potential trading opportunities. Additionally, you can enable alerts for take-profit or stop-loss levels, which notify you when the price achieves those levels. The alerts will work for each enabled ticker in the settings. You can also toggle webhook format for alerts, and choose to include ticker metadata in it.
⚙️ SETTINGS
1. Algorithm Settings
Sensitivity: The sensitivity setting is a key parameter that influences the frequency of signals the SFX Algo generates. By adjusting this parameter, you can control the frequency of signals produced by the algorithm. Using a lower sensitivity setting generates more frequent signals that are highly responsive to minor price fluctuations. Using a higher sensitivity setting reduces the frequency of signals, focusing on more significant price movements and filtering out minor fluctuations.
Signal Strength: The Signal Strength setting filters signals based on their quality, allowing traders to focus on the most reliable opportunities. This feature helps traders balance the quantity and reliability of the algorithm’s signals to suit their trading strategy. Using a lower signal strength will display more signals, including those with lower signal ratings, for broader market coverage. Using a higher signal strength will display fewer signals by prioritizing those with higher signal ratings, reducing market noise.
Time Weighting: The Time Weighting setting in the SFX Algo determines how historical market data is analyzed to generate signals.
a) Recent Trends
Focuses on the most recent movements for short-term analysis. This setting is good for scalpers and intraday traders who need to react quickly to market changes.
b) Mixed Trends
Balances recent and historical price movements for a comprehensive market view. This setting is well-suited for swing traders and those who want to capture medium-term opportunities by combining the benefits of short-term responsiveness with the reliability of long-term trends.
c) Long-term Trends
Relies on extended historical market data to identify broader market trends, making it an excellent choice for traders focused on long-term strategies.
Minimum Star Rating : The Minimum Star Rating setting allows you to filter signals based on their strength, showing only those that meet or exceed your chosen threshold. For instance, setting the minimum star rating to 3 ensures you only receive signals with a rating of 3 stars or higher.
2. Take Profit / Stop Loss Methods
Key Levels
The Key Levels method uses pivot points to set take profit and stop-loss levels. The TP and SL levels are shown when a new signal is generated.
Volatility Bands
This TP/SL method uses the Volatility Bands overlay to set dynamic TP and SL levels. These levels are not predetermined so they will not be shown in advance when a signal is generated.
Signal Rating
Sets take profit and stop-loss levels based on changes in a signal's rating strength. These levels are not predetermined so they will not be shown in advance when a signal is generated.
Auto Stop-Loss
The auto method can only be applied to the SL. The auto method allows the algorithm to detect SL automatically when a momentum shift is detected. You can adjust the risk tolerance of the Auto SL by adjusting the ‘Auto Risk Tolerance’ setting. You can choose between Low, Medium, and High. A high-risk tolerance will result in stop losses being triggered less often.
3. Tickers
You can set, then enable or disable up to 8 tickers in this section to get informed about their latest SFX Algo signal.
‼️ Important Notes
TradingView has limitations when running advanced screeners, resulting in the following restrictions:
Computation Errors:
The computation of using MTF features and viewing several tickers is very intensive on TradingView. This can sometimes cause calculation timeouts. When this occurs simply force the recalculation by modifying one indicator’s settings or by removing the indicator and adding it to your chart again.
Inconsistencies:
You may notice inconsistencies when viewing the screener on a chart with a specific symbol because screener tickers originate from different markets. Since the cryptocurrency market operates 24/7, while stock markets have defined opening and closing hours, the screener may return varying information depending on whether you're currently viewing a cryptocurrency, stock, or currency pair.
(Early Test) Weekly Seasonality with Dynamic Kelly Criterion# Enhancing Trading Strategies with the Weekly Seasonality Dynamic Kelly Criterion Indicator
Amidst this pursuit to chase price, a common pitfall emerges: an overemphasis on price movements without adequate attention to risk management, probabilistic analysis, and strategic position sizing. To address these challenges, I developed the **Weekly Seasonality with Dynamic Kelly Criterion Indicator**. It is designed to refocus traders on essential aspects of trading, such as risk management and probabilistic returns, thereby catering to both short-term swing traders and long-term investors aiming for tax-efficient positions.
## The Motivation Behind the Indicator
### Overemphasis on Price: A Common Trading Pitfall
Many traders concentrate heavily on price charts and technical indicators, often neglecting the underlying principles of risk management and probabilistic analysis. This overemphasis on price can lead to:
- **Overtrading:** Making frequent trades based solely on price movements without considering the associated risks.
- **Poor Risk Management:** Failing to set appropriate stop-loss levels or position sizes, increasing the potential for significant losses.
- **Emotional Trading:** Letting emotions drive trading decisions rather than objective analysis, which can result in impulsive and irrational trades.
### The Need for Balanced Focus
To achieve sustained trading success, it is crucial to balance price analysis with robust risk management and probabilistic strategies. Key areas of focus include:
1. **Risk Management:** Implementing strategies to protect capital, such as setting stop-loss orders and determining appropriate position sizes based on risk tolerance.
2. **Probabilistic Analysis:** Assessing the likelihood of various market outcomes to make informed trading decisions.
3. **Swing Trading Percent Returns:** Capitalizing on short- to medium-term price movements by buying assets below their average return and selling them above.
## Introducing the Weekly Seasonality with Dynamic Kelly Criterion Indicator
The **Weekly Seasonality with Dynamic Kelly Criterion Indicator** is designed to integrate these essential elements into a comprehensive tool that aids traders in making informed, risk-aware decisions. Below, we explore the key components and functionalities of this indicator.
### Key Components of the Indicator
1. **Average Return (%)**
- **Definition:** The mean percentage return for each week across multiple years.
- **Purpose:** Serves as a benchmark to identify weeks with above or below-average performance, guiding buy and sell decisions.
2. **Positive Percentage (%)**
- **Definition:** The proportion of weeks that yielded positive returns.
- **Purpose:** Indicates the consistency of positive returns, helping traders gauge the reliability of certain weeks for trading.
3. **Volatility (%)**
- **Definition:** The standard deviation of weekly returns.
- **Purpose:** Measures the variability of returns, providing insights into the risk associated with trading during specific weeks.
4. **Kelly Ratio**
- **Definition:** A mathematical formula used to determine the optimal size of a series of bets to maximize the logarithmic growth of capital.
- **Purpose:** Balances potential returns against risks, guiding traders on the appropriate position size to take.
5. **Adjusted Kelly Fraction**
- **Definition:** The Kelly Ratio adjusted based on user-defined risk tolerance and external factors like Federal Reserve (Fed) stance.
- **Purpose:** Personalizes the Kelly Criterion to align with individual risk preferences and market conditions, enhancing risk management.
6. **Position Size ($)**
- **Definition:** The calculated amount to invest based on the Adjusted Kelly Fraction.
- **Purpose:** Ensures that position sizes are aligned with risk management strategies, preventing overexposure to any single trade.
7. **Max Drawdown (%)**
- **Definition:** The maximum observed loss from a peak to a trough of a portfolio, before a new peak is attained.
- **Purpose:** Assesses the worst-case scenario for losses, crucial for understanding potential capital erosion.
### Functionality and Benefits
- **Weekly Data Aggregation:** Aggregates weekly returns across multiple years to provide a robust statistical foundation for decision-making.
- **Quarterly Filtering:** Allows users to filter weeks based on quarters, enabling seasonality analysis and tailored strategies aligned with specific timeframes.
- **Dynamic Risk Adjustment:** Incorporates the Dynamic Kelly Criterion to adjust position sizes in real-time based on changing risk profiles and market conditions.
- **User-Friendly Visualization:** Presents all essential metrics in an organized Summary Table, facilitating quick and informed decision-making.
## The Origin of the Kelly Criterion and Addressing Its Limitations
### Understanding the Kelly Criterion
The Kelly Criterion, developed by John L. Kelly Jr. in 1956, is a formula used to determine the optimal size of a series of bets to maximize the long-term growth of capital. The formula considers both the probability of winning and the payout ratio, balancing potential returns against the risk of loss.
**Kelly Formula:**
\
Where:
- \( b \) = the net odds received on the wager ("b to 1")
- \( p \) = probability of winning
- \( q \) = probability of losing ( \( q = 1 - p \) )
### The Risk of Ruin
While the Kelly Criterion is effective in optimizing growth, it carries inherent risks:
- **Overbetting:** If the input probabilities or payout ratios are misestimated, the Kelly Criterion can suggest overly aggressive position sizes, leading to significant losses.
- **Assumption of Constant Probabilities:** The criterion assumes that probabilities remain constant, which is rarely the case in dynamic markets.
- **Ignoring External Factors:** Traditional Kelly implementations do not account for external factors such as Federal Reserve rates, margin requirements, or market volatility, which can impact risk and returns.
### Addressing Traditional Limitations
Recognizing these limitations, the **Weekly Seasonality with Dynamic Kelly Criterion Indicator** introduces enhancements to the traditional Kelly approach:
- **Incorporation of Fed Stance:** Adjusts the Kelly Fraction based on the current stance of the Federal Reserve (neutral, dovish, or hawkish), reflecting broader economic conditions that influence market behavior.
- **Margin and Leverage Considerations:** Accounts for margin rates and leverage, ensuring that position sizes remain within manageable risk parameters.
- **Dynamic Adjustments:** Continuously updates position sizes based on real-time risk assessments and probabilistic analyses, mitigating the risk of ruin associated with static Kelly implementations.
## How the Indicator Aids Traders
### For Short-Term Swing Traders
Short-term swing traders thrive on capitalizing over weekly price movements. The indicator aids them by:
- **Identifying Favorable Weeks:** Highlights weeks with above-average returns and favorable volatility, guiding entry and exit points.
- **Optimal Position Sizing:** Utilizes the Adjusted Kelly Fraction to determine the optimal amount to invest, balancing potential returns with risk exposure.
- **Probabilistic Insights:** Provides metrics like Positive Percentage (%) and Kelly Ratio to assess the likelihood of favorable outcomes, enhancing decision-making.
### For Long-Term Tax-Free Investors
This is effectively a drop-in replacement for DCA which uses fixed position size that doesn't change based on market conditions, as a result, it's like catching multiple falling knifes by the blade and smiling with blood on your hand... I don't know about you, but I'd rather juggle by the hilt and look like an actual professional...
Long-term investors, especially those seeking tax-free positions (e.g., through retirement accounts), benefit from:
- **Consistent Risk Management:** Ensures that position sizes are aligned with long-term capital preservation strategies.
- **Seasonality Analysis:** Allows for strategic positioning based on historical performance trends across different weeks and quarters.
- **Dynamic Adjustments:** Adapts to changing market conditions, maintaining optimal risk profiles over extended investment horizons.
### Developers
Please double check the logic and functionality because I think there are a few issue and I need to crowd source solutions and be responsible about the code I publish. If you have corrections, please DM me or leave a respectful comment.
I want to publish this by the end of the year and include other things like highlighting triple witching weeks, adding columns for volume % stats, VaR and CVaR, alpha, beta (to see the seasonal alpha and beta based off a benchmark ticker and risk free rate ticker and other little goodies.
VCBBDOVWAPSMA By Anil ChawraHow Users Can Make Profit Using This Script:
1. Volume Representation : Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2. Candlestick Anatomy : A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3. Volume Bars : Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4. Interpreting Volume : High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5. Confirmation : Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6. Trend Strength : Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7. Volume Patterns : Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8. Combination with Price Action: Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9. Confirmation and Validation: It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10. Risk Management : As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
How to script works :
1.Identify High Volume Candles: Look for candles with significantly higher volume compared to the surrounding candles. These can indicate increased market interest or activity.
2.Wait for Confirmation: Once you identify a high volume candle, wait for confirmation from subsequent candles to ensure the momentum is sustained.
3.Enter the Trade: After confirmation, consider entering a trade in the direction indicated by the high volume candle. For example, if it's a bullish candle, consider buying.
4.Set Stop Loss: Always set a stop loss to limit potential losses in case the trade goes against you.
5.Take Profit: Set a target for taking profits. This could be based on technical analysis, such as a resistance level or a certain percentage gain.
6.Monitor Volume: Continuously monitor volume to gauge the strength of the trend. Decreasing volume may signal weakening momentum and could be a sign to exit the trade.
7.Risk Management: Manage risk carefully by adjusting position sizes according to your risk tolerance and the size of your trading account.
8.Review and Adapt: Regularly review your trades and adapt your strategy based on what's working and what's not.
Remember, no trading strategy guarantees profits, and it's essential to practice proper risk management and have realistic expectations. Additionally, consider combining volume analysis with other technical indicators for a more comprehensive approach to trading.
**How Users Can Make Profit Using This Script:
**
DAYS OPEN LINE:
1.Purpose: Publishing a "Days Open Line" indicator serves to inform customers about the operational schedule of a business or service.
2.Visibility: It ensures that the information regarding the days of operation is easily accessible to current and potential customers.
3.Transparency: By making the operational schedule public, businesses demonstrate transparency and reliability to their customers.
4.Accessibility: The indicator should be published on various platforms such as the business website, social media channels, and physical locations to ensure accessibility to a wide audience.
5.Clarity: The information should be presented in a clear and concise manner, specifying the days of the week the business is open and the corresponding operating hours.
6.Updates: It's important to regularly update the "Days Open Line" indicator to reflect any changes in the operational schedule, such as holidays or special events.
7.Customer Convenience: Providing this information helps customers plan their visits accordingly, reducing inconvenience and frustration due to unexpected closures.
8.Expectation Management: Setting clear expectations regarding the business hours helps manage customer expectations and reduces the likelihood of disappointment or complaints.
9.Customer Service: Publishing the "Days Open Line" indicator demonstrates a commitment to customer service by ensuring that customers have the information they need to engage with the business.
10.Brand Image: Consistently .maintaining and updating the indicator contributes to a positive brand image, as it reflects professionalism, reliability, and a customer-centric approach.
SMA CROSS:
1.This indicator generates buy and sell signals based on the crossover of two Simple Moving Averages (SMA): a shorter 3-day SMA and a longer 8-day SMA.
When the 3-day SMA crosses above the 8-day SMA, it generates a buy signal indicating a potential upward trend.
Conversely, when the 3-day SMA crosses below the 8-day SMA, it generates a sell signal indicating a potential downward trend.
Signal Interpretation:
2.Buy Signal: Generated when the 3-day SMA crosses above the 8-day SMA.
Sell Signal: Generated when the 3-day SMA crosses below the 8-day SMA.
Usage:
3.Traders can use this indicator to identify potential entry and exit points in the market.
Buy signals suggest a bullish trend, indicating a favorable time to enter or hold a long position.
4.Sell signals suggest a bearish trend, indicating a potential opportunity to exit or take a short position.
Parameters:
5.Periods: 3-day SMA and 8-day SMA.
Price: Closing price is commonly used, but users can choose other price types (open, high, low) for calculation.
Confirmation:
6.It's recommended to use additional technical analysis tools or confirmatory indicators to validate signals and minimize false signals.
Risk Management:
7.Implement proper risk management strategies, such as setting stop-loss orders, to mitigate losses in case of adverse price movements.
Backtesting:
8.Before using the indicator in live trading, conduct thorough backtesting to evaluate its effectiveness under various market conditions.
Considerations:
9.While SMA crossovers can provide valuable insights, they may generate false signals during ranging or choppy markets.
Combine this indicator with other technical analysis techniques for comprehensive market analysis.
Continuous Optimization:
10.Monitor the performance of the indicator and adjust parameters or incorporate additional filters as needed to enhance accuracy over time.
BOLLINGER BAND:
1.Definition: A Bollinger Band indicator is a technical analysis tool that consists of a centerline (typically a moving average) and two bands plotted above and below it. These bands represent volatility around the moving average.
2.Purpose: Publishing a Bollinger Band indicator serves to provide traders and investors with insights into the volatility and potential price movements of a financial instrument.
3.Visualization: The indicator is typically displayed on price charts, allowing users to visualize the relationship between price movements and volatility levels.
4.Interpretation: Traders use Bollinger Bands to identify overbought and oversold conditions, potential trend reversals, and volatility breakouts.
5.Components: The indicator consists of three main components: the upper band, lower band, and centerline (usually a simple moving average). These components are calculated based on standard deviations from the moving average.
6.Parameters: Traders can adjust the parameters of the Bollinger Bands, such as the period length and standard deviation multiplier, to customize the indicator based on their trading strategy and preferences.
7.Signals: Bollinger Bands generate signals when prices move outside the bands, indicating potential trading opportunities. For example, a price breakout above the upper band may signal a bullish trend continuation, while a breakout below the lower band may indicate a bearish trend continuation.
8.Confirmation: Traders often use other technical indicators or price action analysis to confirm signals generated by Bollinger Bands, enhancing the reliability of their trading decisions.
9.Education: Publishing Bollinger Band indicators can serve an educational purpose, helping traders learn about technical analysis concepts and how to apply them in real-world trading scenarios.
10.Risk Management: Traders should exercise proper risk management when using Bollinger Bands, as false signals and market volatility can lead to losses. Publishing educational content alongside the indicator can help users understand the importance of risk management in trading.
VWAP:
1.Calculation: VWAP is calculated by dividing the cumulative sum of price times volume traded for every transaction (price * volume) by the total volume traded.
2.Time Frame: VWAP is typically calculated for a specific time frame, such as a trading day or a session.
3.Intraday Trading: It's commonly used by intraday traders to assess the fair value of a security and to determine if the current price is above or below the average price traded during the day.
4.Execution: Institutional traders often use VWAP as a benchmark for executing large orders, aiming to buy at prices below VWAP and sell at prices above VWAP.
5.Benchmark: It serves as a benchmark for traders to evaluate their trading performance. Trades executed below VWAP are considered good buys, while those above are considered less favorable.
6.Sensitivity: VWAP is more sensitive to price and volume changes during periods of high trading activity and less sensitive during periods of low trading activity.
7.Day's End: VWAP resets at the end of each trading day, providing a new reference point for the following trading session.
8.Volume Weighting: The weighting by volume means that prices with higher trading volumes have a greater impact on VWAP than those with lower volumes.
9.Popular with Algorithmic Traders: Algorithmic trading systems often incorporate VWAP strategies to execute trades efficiently and minimize market impact.
10.Limitations: While VWAP is a useful indicator, it's not foolproof. It may lag behind rapidly changing market conditions and may not be suitable for all trading strategies or market conditions. Additionally, it's more effective in liquid markets where there is significant trading volume.
Luxmi AI Directional Option Buying (Long Only)Introduction:
"Option premium charts typically exhibit a predisposition towards bearish sentiment in higher timeframes"
In the dynamic world of options trading, navigating through the complexities of market trends and price movements is essential for making informed decisions. Among the arsenal of tools available to traders, option premium charts stand out as a pivotal source of insight, particularly in higher timeframes. However, their inherent bearish inclination in such timeframes necessitates a keen eye for identifying bullish pullbacks, especially in lower timeframes, to optimize buying strategies effectively.
Understanding the interplay between different data points becomes paramount in this endeavor. Traders embark on a journey of analysis, delving into metrics such as Implementation Shortfall, the performance of underlying index constituents, and bullish trends observed in lower timeframes like the 1-minute and 3-minute charts. These data points serve as guiding beacons, illuminating potential opportunities amidst the market's ever-shifting landscape.
Using this indicator, we will dissect the significance of option premium charts and their nuanced portrayal of market sentiment. Furthermore, we will unveil the art of discerning bullish pullbacks in lower timeframes, leveraging a multifaceted approach that amalgamates quantitative analysis with qualitative insights. Through this holistic perspective, traders can refine their decision-making processes, striving towards efficiency and efficacy in their options trading endeavors.
Major Features:
Implementation Shortfall (IS) Candles:
Working Principle:
TWAP (Time-Weighted Average Price) and EMA (Exponential Moving Average) are both commonly used in calculating Implementation Shortfall, a metric that measures the difference between the actual execution price of a trade and the benchmark price.
TWAP calculates the average price of a security over a specified time period, giving equal weight to each interval. On the other hand, EMA places more weight on recent prices, making it more responsive to current market conditions.
To calculate Implementation Shortfall using TWAP, the difference between the average execution price and the benchmark price is determined over the trading period. Similarly, with EMA, the difference is calculated using the exponential moving average price instead of a simple average.
By employing TWAP and EMA, traders can gauge the effectiveness of their trading strategies and identify areas for improvement in executing trades relative to a benchmark.
Benefits of using Implementation Shortfall:
By visualizing the implementation shortfall and its comparison with the EMA on the chart, traders can quickly assess whether current trading activity is deviating from recent trends.
Green bars suggest potential buying opportunities or bullish sentiment, while red bars suggest potential selling opportunities or bearish sentiment.
Traders can use this visualization to make more informed decisions about their trading strategies, such as adjusting position sizes, entering or exiting trades, or managing risk based on the observed deviations from the moving average.
How to use this feature:
This feature calculates Implementation Shortfall (IS) and visually represents it by coloring the candles in either bullish (green) or bearish (red) hues. This color-coding system provides traders with a quick and intuitive way to assess market sentiment and potential entry points. Specifically, a long entry is signaled when both the candle color and the trend cloud color align as green, indicating a bullish market outlook. This integrated approach enables traders to make informed decisions, leveraging IS insights alongside visual cues for more effective trading strategies.
Micro Trend Candles:
Working Principle:
This feature begins by initializing variables to determine trend channel width and track price movements. Average True Range (ATR) is then calculated to measure market volatility, influencing the channel's size. Highs and lows are identified within a specified range, and trends are assessed based on price breaches, with potential changes signaled accordingly. The price channel is continually updated to adapt to market shifts, and arrows are placed to indicate potential entry points. Colors are assigned to represent bullish and bearish trends, dynamically adjusting based on current market conditions. Finally, candles on the chart are colored to visually depict the identified micro trend, offering traders an intuitive way to interpret market sentiment and potential entry opportunities.
Benefits of using Micro Trend Candles:
Traders can use these identified micro trends to spot potential short-term trading opportunities. For example:
Trend Following: Traders may decide to enter trades aligned with the prevailing micro trend. If the candles are consistently colored in a certain direction, traders may consider entering positions in that direction.
Reversals: Conversely, if the script signals a potential reversal by changing the candle colors, traders may anticipate trend reversals and adjust their trading strategies accordingly. For instance, they might close existing positions or enter new positions in anticipation of a trend reversal.
It's important to note that these micro trends are short-term in nature and may not always align with broader market trends. Therefore, traders utilizing this script should consider their trading timeframes and adjust their strategies accordingly.
How to use this feature:
This feature assigns colors to candles to represent bullish and bearish trends, with adjustments made based on current market conditions. Green candles accompanied by a green trend cloud signal a potential long entry, while red candles suggest caution, indicating a bearish trend. This visual representation allows traders to interpret market sentiment intuitively, identifying optimal entry points and exercising caution during potential downtrends.
Scalping Candles (Inspired by Elliott Wave):
Working Principle:
This feature draws inspiration from the Elliot Wave method, utilizing technical analysis techniques to discern potential market trends and sentiment shifts. It begins by calculating the variance between two Exponential Moving Averages (EMAs) of closing prices, mimicking Elliot Wave's focus on wave and trend analysis. The shorter-term EMA captures immediate price momentum, while the longer-term EMA reflects broader market trends. A smoother Exponential Moving Average (EMA) line, derived from the difference between these EMAs, aids in identifying short-term trend shifts or momentum reversals.
Benefits of using Scalping Candles Inspired by Elliott Wave:
The Elliott Wave principle is a form of technical analysis that attempts to predict future price movements by identifying patterns in market charts. It suggests that markets move in repetitive waves or cycles, and traders can potentially profit by recognizing these patterns.
While this script does not explicitly analyze Elliot Wave patterns, it is inspired by the principle's emphasis on trend analysis and market sentiment. By calculating and visualizing the difference between EMAs and assigning colors to candles based on this analysis, the script aims to provide traders with insights into potential market sentiment shifts, which can align with the broader philosophy of Elliott Wave analysis.
How to use this feature:
Candlestick colors are assigned based on the relationship between the EMA line and the variance. When the variance is below or equal to the EMA line, candles are colored red, suggesting a bearish sentiment. Conversely, when the variance is above the EMA line, candles are tinted green, indicating a bullish outlook. Though not explicitly analyzing Elliot Wave patterns, the script aligns with its principles of trend analysis and market sentiment interpretation. By offering visual cues on sentiment shifts, it provides traders with insights into potential trading opportunities, echoing Elliot Wave's emphasis on pattern recognition and trend analysis.
Volume Candles:
Working Principle:
This feature introduces a custom volume calculation method tailored for bullish and bearish bars, enabling a granular analysis of volume dynamics specific to different price movements. By summing volumes over specified periods for bullish and bearish bars, traders gain insights into the intensity of buying and selling pressures during these periods, facilitating a deeper understanding of market sentiment. Subsequently, the script computes the net volume, revealing the overall balance between buying and selling pressures. Positive net volume signifies prevailing bullish sentiment, while negative net volume indicates bearish sentiment.
Benefits of Using Volume candles:
Enhanced Volume Analysis: Traders gain a deeper understanding of volume dynamics specific to bullish and bearish price movements, allowing them to assess the intensity of buying and selling pressures with greater precision.
Insight into Market Sentiment: By computing net volume and analyzing its relationship with the Exponential Moving Average (EMA), traders obtain valuable insights into prevailing market sentiment. This helps in identifying potential shifts in sentiment and anticipating market movements.
Visual Representation of Sentiment: The color-coded candle bodies based on volume dynamics provide traders with a visual representation of market sentiment. This intuitive visualization helps in quickly interpreting sentiment shifts and making timely trading decisions.
How to use this feature:
This visual representation allows traders to quickly interpret market sentiment based on volume dynamics. Green candles indicate potential bullish sentiment, while red candles suggest bearish sentiment. The color-coded candle bodies help traders identify shifts in market sentiment and make informed trading decisions.
Smart Sentimeter Candles:
Working Principle:
The "Smart Sentimeter Candles" feature is a tool designed for market sentiment analysis using technical indicators. It begins by defining stock symbols from various sectors, allowing traders to select specific indices for sentiment analysis. The script then calculates the difference between two Exponential Moving Averages (EMAs) of the High-Low midpoint, capturing short-term momentum changes in the market. It computes the difference between current and previous values to capture momentum shifts over time.
Additionally, it calculates the Exponential Moving Average (EMA) of this difference to provide a smoothed representation of the prevailing trend in market momentum. Another EMA of this difference is calculated to offer an alternative perspective on longer-term momentum trends. Bar colors are determined based on the difference between current and previous values, with bullish and bearish sentiment represented by custom colors. Finally, sentiment candles are visualized on the chart, providing traders with a clear representation of market sentiment changes.
Benefits of Using Sentimeter Candles:
By analyzing index constituents, traders gain insights into the individual stocks that collectively influence the index's performance. This understanding is crucial for trading options as it helps traders tailor their strategies to specific sectors or stocks within the index.
Sector-Specific Analysis: Traders can focus on specific sectors by selecting relevant indices for sentiment analysis.
Momentum Identification: The script identifies short-term momentum changes in the market, aiding traders in spotting potential trend reversals or continuations.
Clear Visualization: Sentiment candles visually represent market sentiment changes, making it easier for traders to interpret and act upon sentiment trends.
How to use this feature:
Select Indices: Toggle the inputs to choose which indices (e.g., NIFTY, BANKNIFTY, FINNIFTY) to analyze.
Interpret Sentiment Candles: Monitor the color of sentiment candles on the chart. Green candles indicate bullish sentiment, while red candles suggest bearish sentiment.
Observe Momentum Changes: Pay attention to momentum changes identified by the difference between EMAs and their respective EMAs. Increasing bullish momentum may present buying opportunities, while increasing bearish momentum could signal potential sell-offs.
Trend Cloud:
Working Principle:
The script utilizes the Relative Strength Index (RSI) to assess market momentum, identifying bullish and bearish phases based on RSI readings. It calculates two boolean variables, bullmove and bearmove, which signal shifts in momentum direction by considering changes in the Exponential Moving Average (EMA) of the closing price. When RSI indicates bullish momentum and the closing price's EMA exhibits positive changes, bullmove is triggered, signifying the start of a bullish phase. Conversely, when RSI suggests bearish momentum and the closing price's EMA shows negative changes, bearmove is activated, marking the beginning of a bearish phase. This systematic approach helps in understanding the current trend of the price. The script visually emphasizes these phases on the chart using plot shape markers, providing traders with clear indications of trend shifts.
Benefits of Using Trend Cloud:
Comprehensive Momentum Assessment: The script offers a holistic view of market momentum by incorporating RSI readings and changes in the closing price's EMA, enabling traders to identify both bullish and bearish phases effectively.
Structured Trend Recognition: With the calculation of boolean variables, the script provides a structured approach to recognizing shifts in momentum direction, enhancing traders' ability to interpret market dynamics.
Visual Clarity: Plotshape markers visually highlight the start and end of bullish and bearish phases on the chart, facilitating easy identification of trend shifts and helping traders to stay informed.
Prompt Response: Traders can promptly react to changing market conditions as the script triggers alerts when bullish or bearish phases begin, allowing them to seize potential trading opportunities swiftly.
Informed Decision-Making: By integrating various indicators and visual cues, the script enables traders to make well-informed decisions and adapt their strategies according to prevailing market sentiment, ultimately enhancing their trading performance.
How to use this feature:
The most effective way to maximize the benefits of this feature is to use it in conjunction with other key indicators and visual cues. By combining the color-coded clouds, which indicate bullish and bearish sentiment, with other features such as IS candles, microtrend candles, volume candles, and sentimeter candles, traders can gain a comprehensive understanding of market dynamics. For instance, aligning the color of the clouds with the trend direction indicated by IS candles, microtrend candles, and sentimeter candles can provide confirmation of trend strength or potential reversals.
Furthermore, traders can leverage the trend cloud as a trailing stop-loss tool for long entries, enhancing risk management strategies. By adjusting the stop-loss level based on the color of the cloud, traders can trail their positions to capture potential profits while minimizing losses. For long entries, maintaining the position as long as the cloud remains green can help traders stay aligned with the prevailing bullish sentiment. Conversely, a shift in color from green to red serves as a signal to exit the position, indicating a potential reversal in market sentiment and minimizing potential losses. This integration of the trend cloud as a trailing stop-loss mechanism adds an additional layer of risk management to trading strategies, increasing the likelihood of successful trades while reducing exposure to adverse market movements.
Moreover, the red cloud serves as an indicator of decay in option premiums and potential theta effect, particularly relevant for options traders. When the cloud turns red, it suggests a decline in option prices and an increase in theta decay, highlighting the importance of managing options positions accordingly. Traders may consider adjusting their options strategies, such as rolling positions or closing out contracts, to mitigate the impact of theta decay and preserve capital. By incorporating this insight into options pricing dynamics, traders can make more informed decisions about their options trades.
Scalping Opportunities (UpArrow and DownArrow):
Working Principle:
The feature calculates candlestick values based on the open, high, low, and close prices of each bar. By comparing these derived candlestick values, it determines whether the current candlestick is bullish or bearish. Additionally, it signals when there is a change in the color (bullish or bearish) of the derived candlesticks compared to the previous bar, enabling traders to identify potential shifts in market sentiment. This is a long only strategy, hence the signals are plotted only when the Trend Cloud is Green (Bullish).
Benefits of using UpArrow and DownArrow:
Clear Visualization: By employing color-coded candlesticks, the script offers traders a visually intuitive representation of market sentiment, enabling quick interpretation of prevailing conditions.
Signal Identification: Its capability to detect shifts in market sentiment serves as a valuable tool for identifying potential trading opportunities, facilitating timely decision-making and execution.
Long-Only Strategy: The script selectively plots signals only when the trend cloud is green, aligning with a bullish bias and enabling traders to focus on long positions during favorable market conditions.
Up arrows indicate potential long entry points, complementing the bullish bias of the trend cloud. Conversely, down arrows signify an active pullback in progress, signaling caution and prompting traders to refrain from entering long positions during such periods.
How to use this feature:
Confirmation: Confirm bullish market conditions with the Trend Cloud indicator. Ensure alignment between trend cloud signals, candlestick colors, and arrow indicators for confident trading decisions.
Entry Signals: Look for buy signals within a green trend cloud, indicated by bullish candlestick color changes and up arrows, suggesting potential long entry points aligned with the prevailing bullish sentiment.
Wait Signals: Exercise caution when encountering down arrows, which signify wait signals or active pullbacks in progress. Avoid entering long positions during these periods to avoid potential losses.
Exit Strategy: Use trend cloud color changes as signals to exit long positions. When the trend cloud shifts color, consider closing out long positions to lock in profits or minimize losses.
Profit Management: It's important to book or lock in some profits early on in option buying. Consider taking partial profits when the trade is in your favor and trail the remaining position to maximize gains on favorable trades.
Risk Management: Implement stop-loss orders or trailing stops to manage risk effectively. Exit positions promptly if sentiment shifts or if price movements deviate from the established trend, safeguarding capital.
Up and Down Signals:
Working Principle:
This feature calculates Trailing Stoploss (TSL) using the Average True Range (ATR) to dynamically adjust the stop level based on price movements. It generates buy signals when the price crosses above the trailing stop and sell signals when it crosses below. These signals are plotted on the chart and trigger alerts, signaling potential trading opportunities. Additionally, the script selectively plots Up and Down signals only when the Implementation Shortfall Calculation identifies scalp opportunities, independent of the prevailing price trend.
Benefits of using Up and Down Signals:
Trailing Stoploss: The script employs an ATR-based trailing stop, allowing traders to adjust stop levels dynamically in response to changing market conditions, thereby maximizing profit potential and minimizing losses.
Clear Signal Generation: Buy and sell signals are generated based on price interactions with the trailing stop, providing clear indications of entry and exit points for traders to act upon.
Alert Notifications: The script triggers alerts when buy or sell signals are generated, ensuring traders remain informed of potential trading opportunities even when not actively monitoring the charts.
Scalping Opportunities: By incorporating Implementation Shortfall Calculation, the script identifies scalp opportunities, enabling traders to capitalize on short-term price movements irrespective of the prevailing trend.
How to use this feature:
Signal Interpretation: Interpret Up signals as opportunities to enter long positions when the price crosses above the trailing stop, and Down signals as cues to exit.
Alert Monitoring: Pay attention to alert notifications triggered by the script, indicating potential trading opportunities based on signal generation.
Scalping Strategy: When Up and Down signals are plotted alongside scalp opportunities identified by the Implementation Shortfall Calculation, consider scalping trades aligned with these signals for short-term profit-taking, regardless of the overall market trend.
Consideration of Trend Cloud: Remember that this feature does not account for the underlying trend provided by the Trend Cloud feature. Consequently, the take profit levels generated by the trailing stop may be smaller than those derived from trend-following strategies. It's advisable to supplement this feature with additional trend analysis to optimize profit-taking levels and enhance overall trading performance.
Chart Timeframe Support and Resistance:
Working Principle:
This feature serves to identify and visualize support and resistance levels on the chart, primarily based on the chosen Chart Timeframe (CTF). It allows users to specify parameters such as the number of bars considered on the left and right sides of each pivot point, as well as line width and label color. Moreover, users have the option to enable or disable the display of these levels. By utilizing functions to calculate pivot highs and lows within the specified timeframe, the script determines the highest high and lowest low surrounding each pivot point.
Additionally, it defines functions to create lines and labels for each detected support and resistance level. Notably, this feature incorporates a trading method that emphasizes the concept of resistance turning into support after breakouts, thereby providing valuable insights for traders employing such strategies. These lines are drawn on the chart, with colors indicating whether the level is above or below the current close price, aiding traders in visualizing key levels and making informed trading decisions.
Benefits of Chart Timeframe Support and Resistance:
Identification of Price Levels: Support and resistance levels help traders identify significant price levels where buying (support) and selling (resistance) pressure may intensify. These levels are often formed based on historical price movements and are regarded as areas of interest for traders.
Decision Making: Support and resistance levels assist traders in making informed trading decisions. By observing price reactions near these levels, traders can gauge market sentiment and adjust their strategies accordingly. For example, traders may choose to enter or exit positions, set stop-loss orders, or take profit targets based on price behavior around these levels.
Risk Management: Support and resistance levels aid in risk management by providing reference points for setting stop-loss orders. Traders often place stop-loss orders below support levels for long positions and above resistance levels for short positions to limit potential losses if the market moves against them.
How to use this feature:
Planning Long Positions: When considering long positions, it's advantageous to strategize when the price is in proximity to a support level identified by the script. This suggests a potential area of buying interest where traders may expect a bounce or reversal in price. Additionally, confirm the bullish bias by ensuring that the trend cloud is green, indicating favorable market conditions for long trades.
Waiting for Breakout: If long signals are generated near resistance levels detected by the script, exercise patience and wait for a breakout above the resistance. A breakout above resistance signifies potential strength in the upward momentum and may present a more opportune moment to enter long positions. This approach aligns with trading methodologies that emphasize confirmation of bullish momentum before initiating trades.
Settings:
The Index Constituent Analysis setting empowers users to input the constituents of a specific index, facilitating the analysis of market sentiments based on the performance of these individual components. An index serves as a statistical measure of changes in a portfolio of securities representing a particular market or sector, with constituents representing the individual assets or securities comprising the index.
By providing the constituent list, users gain insights into market sentiments by observing how each constituent performs within the broader index. This analysis aids traders and investors in understanding the underlying dynamics driving the index's movements, identifying trends or anomalies, and making informed decisions regarding their investment strategies.
This setting empowers users to customize their analysis based on specific indexes relevant to their trading or investment objectives, whether tracking a benchmark index, sector-specific index, or custom index. Analyzing constituent performance offers a valuable tool for market assessment and decision-making.
Example: BankNifty Index and Its Constituents
Illustratively, the BankNifty index represents the performance of the banking sector in India and includes major banks and financial institutions listed on the National Stock Exchange of India (NSE). Prominent constituents of the BankNifty index include:
State Bank of India (SBIN)
HDFC Bank
ICICI Bank
Kotak Mahindra Bank
Axis Bank
IndusInd Bank
Punjab National Bank (PNB)
Yes Bank
Federal Bank
IDFC First Bank
By utilizing the Index Constituent Analysis setting and inputting these constituent stocks of the BankNifty index, traders and investors can assess the individual performance of these banking stocks within the broader banking sector index. This analysis enables them to gauge market sentiments, identify trends, and make well-informed decisions regarding their trading or investment strategies in the banking sector.
Example: NAS100 Index and Its Constituents
Similarly, the NAS100 index, known as the NASDAQ-100, tracks the performance of the largest non-financial companies listed on the NASDAQ stock exchange. Prominent constituents of the NAS100 index include technology and consumer discretionary stocks such as:
Apple Inc. (AAPL)
Microsoft Corporation (MSFT)
Amazon.com Inc. (AMZN)
Alphabet Inc. (GOOGL)
Facebook Inc. (FB)
Tesla Inc. (TSLA)
NVIDIA Corporation (NVDA)
PayPal Holdings Inc. (PYPL)
Netflix Inc. (NFLX)
Adobe Inc. (ADBE)
By inputting these constituent stocks of the NAS100 index into the Index Constituent Analysis setting, traders and investors can analyze the individual performance of these technology and consumer discretionary stocks within the broader NASDAQ-100 index. This analysis facilitates the evaluation of market sentiments, identification of trends, and informed decision-making regarding trading or investment strategies in the technology and consumer sectors.
Example: FTSE 100 Index and Its Constituents
The FTSE 100 index represents the performance of the 100 largest companies listed on the London Stock Exchange (LSE) by market capitalization. Some notable constituents of the FTSE 100 index include:
HSBC Holdings plc
BP plc
GlaxoSmithKline plc
Unilever plc
Royal Dutch Shell plc
AstraZeneca plc
Diageo plc
Rio Tinto plc
British American Tobacco plc
Reckitt Benckiser Group plc
By inputting these constituent stocks of the FTSE 100 index into the Index Constituent Analysis setting, traders and investors can analyze the individual performance of these diverse companies within the broader UK market index. This analysis facilitates the evaluation of market sentiments, identification of trends, and informed decision-making regarding trading or investment strategies in the UK market.
This comprehensive approach enables users to dissect index performance effectively, providing valuable insights for investors and traders across different markets and sectors.
Index Selection - Index Selection allows traders to specify the index for Sentimeter calculations, enabling customization for Call and Put Option charts corresponding to the chosen index.
Support and Resistance Levels - Set the left and right bars to consider pivot high and low to draw Support and resistance lines. Linewidth setting to help increase the width of the Support and Resistance lines. Label Color to change the color of the labels.
Style Section Colors to allow users to customize the color scheme to their liking.
MTF HalfTrendIntroduction
A half-trend indicator is a technical analysis tool that uses moving averages and price data to find potential trend reversal and entry points in the form of graphical arrows showing market turning points.
The salient features of this indicator are:
- It uses the phenomenon of moving averages.
- It is a momentum indicator.
- It can indicate a trend change.
- It is capable of detecting a bullish or bearish trend reversal.
- It can signal to sell/buy.
- It is a real-time indicator.
Multi-Timeframe Application
A standout feature is its flexibility across timeframes. Traders have the liberty to choose any timeframe on the chart, enhancing the tool's versatility and making it suitable for both short-term and long-term analyses.
Principle of the Half Trend indicator
This indicator is based on the moving averages. The moving average is the average of the fluctuation or change in the price of an asset. These averages are taken for a time interval.
So, a half-trend indicator takes the moving averages phenomenon as its principle for working. The most commonly used moving averages in a half trend indicator are:
- Relative strength index (RSI)
- EMA (estimated moving average)
Components of a Half Trend indicator
There are two main components of a half trend indicator:
- Half trend line
- Arrows
- ATR lines
Half trend line
Half trend line represents this indicator on a candlestick chart. This line shows the trend of a chart in real-time. A half-trend line is based on the moving averages.
There are two further components of a half-trend line:
- Redline
- Blue line
A red line represents a bearish trend. When the half-trend line turns red, a trend is facing a dip. It is time for the bears to take control of the market. A bearish control of the market represents the domination of sellers in the market.
On the other hand, the blue line represents the bullish nature of the market. It tells a trader that the bullish sentiment of the market is prevailing. A bullish market means the number of buyers is significantly greater than the number of sellers.
Moreover, a trader can change these colors to his choice by customization.
Arrows
There are two types of arrows in this indicator which help a trader with the entry and exit points. These arrows are,
- Blue arrow
- Red arrow
A blue arrow signals a buying trade; on the other hand, a red arrow tells a trader about the selling of the assets. These arrows work with the moving average line to formulate a trading strategy.
The color of these arrows is changed if a trader desires so.
ATR lines
The ATR blue and red lines represent the Average True Range of the Half trend line. They may be used as stop loss or take profit levels.
Pros and Cons
Pros
- It is a very easy to eyes indicator.
- This is a very useful friendly indicator.
- It provides sufficient information to beginner traders.
- It provides sufficient information for entry points in a trade.
- A half-trend indicator provides a good exit strategy for a trader.
- It provides information about market reversals.
- It helps a trader to find a bullish and bearish sentiment in the market.
Cons
- It is a real-time indicator. So, it can lag.
- The lagging of this indicator can lead to miss opportunities.
- The most advanced and professional traders may not rely on this indicator for crucial trading decisions.
- The lagging of this indicator can predict false reversals of the market.
- It can create false signals.
- It requires the confluence of the other technical tools for a better success ratio.
Settings for Half Trend indicator
The default settings for half trend indicator are:
Amplitude = 2
Channel deviation = 2
Different markets or financial instruments may require different settings for optimal execution.
Amplitude: The degree that the Half trend line takes the internal variables into consideration. The higher the number, the fewer trades. The default value is 2.
Channel deviation: The ATR value calculation from the Half trend line. The default value is 2.
Trading strategy
It is an effective indicator in terms of strategy formation for a trading setup. The new and beginner trades can take benefit from this indicator for the formulation of a good trading setup. This indicator also helps seasoned and professional traders formulate a good trading setup with other technical tools.
The trading strategy involving a half-trend indicator is divided into three parts:
- Entry and exit
- Risk management
- Take profit
Entry and exit
It is an effective indicator that provides sufficient information about the entry and exit points in a trading setup. The profit of a trader is directly proportional to the appropriate entry and exit points. So, it is a crucial step in any trading setup.
The blue and red arrows provide information about the entry and exit points in a trading setup. Furthermore, the entry and exit for the bullish and bearish setups are as follows.
Entry and exit for a bullish setup
If a blue arrow appears under the half-trend line, it means the bullish sentiment of the market is getting stronger in the future. So, it is a signal for entry in a bullish setup.
As the red arrow appears on the chart, it is a signal to exit your trade. The red arrow represents a reversal in the market, so it is a good opportunity to close your trade in a bullish setup.
Entry and exit for a bearish setup
Suppose a red arrow appears above the red moving average line. It is a good opportunity to enter a trade in a bearish setup. The red line represents that sooner the sellers are going to take control and the value of the asset is about to face a dip. So it is the best time to make your move.
As the opposite arrow appears in the chart, it is time to exit from a bearish trade setup.
Re-entering a position
Bullish setup
- The half-trend line is blue.
- At least one candle closes below the blue half-trend line.
- Enter on the candle that closes above the blue half-trend line.
Bearish setup
- The half-trend line is red.
- At least one candle closes above the red half-trend line.
- Enter on the candle that closes below the red half-trend line.
Risk management
Risk management is an integral part of a trading setup. It is an important step to protect your potential profits and losses.
When trading in a bullish market, place the stop loss at the prior swing low. It will help you to cut your losses in case the prices move to the lower end.
In the case of a bearish market, place your stop loss above the prior swing high.
A trader may trail the stop loss using the ATR lines.
The new trader often makes mistakes in the placement of the stop loss. If you don’t place the stop loss at an appropriate point. It can drain your bank account and ruin your trading experience. Is is recommended not to risk more than 2% of your trading account, per trade.
Take profit
The blue ATR line may be used as one take profit level on a bullish setup followed by the previous swing high. The signal reversal would indicate the final take profit and closing of any position.
The red ATR line may be used as one take profit level on a bearish setup followed by the previous swing low. The signal reversal would indicate the final take profit and closing of any position.
Conclusion
A half trend indicator is a decent indicator that can transform your trading experience. It is a dual indicator that is based on the moving averages as well as helps you to form a trading strategy. If you are a new trader, this indicator can help you to learn and flourish in the trading universe. If you are a seasoned trader, I recommend you use this indicator with other technical analysis tools to enhance your success ratio.
All credits go to:
- @everget the original creator of this indicator (I just added the MTF capability).
- Ali Muhammad original author of much of the description used.
Turtle Trader StrategyTurtle Trader Strategy :
Introduction :
This strategy is based on the well known « Turtle Trader Strategy », that has proven itself over the years. It sends long and short signals with pyramid orders of up to 5, meaning that the strategy can trigger up to 5 orders in the same direction. Good risk and money management.
It's important to note that the strategy combines 2 systems working together (S1 and S2). Let’s describe the specific features of this strategy.
1/ Position size :
Position size is very important for turtle traders to manage risk properly. This position sizing strategy adapts to market volatility and to account (gains and losses). It’s based on ATR (Average True Range) which can also be called « N ». Its length is per default 20.
ATR(20) = (previous_atr(20)*19 + actual_true_range)/20
The number of units to buy is :
Unit = 1% * account/(ATR(20)*dollar_per_point)
where account is the actual account value and dollar_per_point is the variation in dollar of the asset with a 1 point move.
Depending on your risk aversion, you can increase the percentage of your account, but turtle traders default to 1%. If you trade contracts, units must be rounded down by default.
There is also an additional rule to reduce the risk if the value of the account falls below the initial capital : in this case and only in this case, account in the unit formula must be replace by :
account = actual_account*actual_account/initial capital
2/ Open a position :
2 systems are working together :
System 1 : Entering a new 20 day breakout
System 2 : Entering a new 55 day breakout
A breakout is a new high or new low. If it’s a new high, we open long position and vice versa if it’s a new low we enter in short position.
We add an additional rule :
System 1 : Breakout is ignored if last long/short position was a winner
System 2 : All signals are taken
This additional rule allows the trader to be in the major trends if the system 1 signal has been skipped. If a signal for system 1 has been skipped, and next candle is also a new 20 day breakout, S1 doesn’t give a signal. We have to wait S2 signal or wait for a candle that doesn’t make a new breakout to reactivate S1.
3/ Pyramid orders :
Turtle Strategy allows us to add extra units to the position if the price moves in our favor. I've configured the strategy to allow up to 5 orders to be added in the same direction. So if the price varies from 0.5*ATR(20) , we add units with the position size formula. Note that the value of account will be replaced by "remaining_account", i.e. the cash remaining in our account after subtracting the value of open positions.
4/ Stop Loss :
We set a stop loss at 1.5*ATR(20) below the entry price for longs and above the entry price for shorts. If pyramid units are added, the stop is increased/decreased by 0.5*ATR(20). Note that if SL is configured for a loss of more than 10%, we set the SL to 10% for the first entry order to avoid big losses. This configuration does not work for pyramid orders as SL moves by 0.5*ATR(20).
5/ Exit signals :
System 1 :
Exit long on a 10 day low
Exit short on a 10 day high
System 2 :
Exit long on a 20 day low
Exit short on a 20 day high
6/ What types of orders are placed ?
To enter in a position, stop orders are placed meaning that we place orders that will be automatically triggered by the signal at the exact breakout price. Stop loss and exit signals are also stop orders. Pyramid orders are market orders which will be triggered at the opening of the next candle to avoid repainting.
PARAMETERS :
Risk % of capital : Percentage used in the position size formula. Default is 1%
ATR period : ATR length used to calculate ATR. Default is 20
Stop ATR : Parameters used to fix stop loss. Default is 1.5 meaning that stop loss will be set at : buy_price - 1.5*ATR(20) for long and buy_price + 1.5*ATR(20) for short. Turtle traders default is 2 but 1.5 is better for cryptocurrency as there is a huge volatility.
S1 Long : System 1 breakout length for long. Default is 20
S2 Long : System 2 breakout length for long. Default is 55
S1 Long Exit : System 1 breakout length to exit long. Default is 10
S2 Long Exit : System 2 breakout length to exit long. Default is 20
S1 Short : System 1 breakout length for short. Default is 15
S2 Short : System 2 breakout length for short. Default is 55
S1 Short Exit : System 1 breakout length to exit short. Default is 7
S2 Short Exit : System 2 breakout length to exit short. Default is 20
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Pyramiding : Number of orders that can be passed in the same direction. Default is 5.
Important : Turtle traders don't trade crypto. For this specific asset type, I modify some parameters such as SL and Short S1 in order to maximize return while limiting drawdown. This strategy is the most optimal on BINANCE:BTCUSD in 1D timeframe with the parameters set per default. If you want to use this strategy for a different crypto please adapt parameters.
NOTE :
It's important to note that the first entry order (long or short) will be the largest. Subsequent pyramid orders will have fewer units than the first order. We've set a maximum SL for the first order of 10%, meaning that you won't lose more than 10% of the value of your first order. However, it is possible to lose more on your pyramid orders, as the SL is increased/decreased by 0.5*ATR(20), which does not secure a loss of more than 10% on your pyramid orders. The risk remains well managed because the value of these orders is less than the value of the first order. Remain vigilant to this small detail and adjust your risk according to your risk aversion.
Enjoy the strategy and don’t forget to take the trade :)
Alpha Candle Breakout Signal on Momentum from Support Resistance
Hello traders,
Let’s start with a brief description of what this strategy/indicator is and what it does and how we trade based on Alpha Candles.
The definition of an Alpha Candle is that it is mathematically calculated, and significantly bigger than the previous candles. This could be a green candle or a red candle, as long as the body is significantly bigger than the previous candles at the end of the calculation. All calculations are done in real time, we do NOT paint the candle sticks after the close of the candle and do not use offset values. This is extremely important. You will see the candle changing it's color as the body of the candle gets bigger with real time data feed. (Recalculate On Every Tick is ON by default). Now besides the mathematical calculations, an Alpha Candle also represents the emotion in the market for that stock in that moment. We can also say that an Alpha Candle is a change in the momentum.
Now that we’ve identified the Alpha candle, the second step is, to have a look at the chart and identify if the Alpha candle is breaking to a new high / low from a consolidation period, or from a good chart pattern (ascending / descending triangle , pennant , sideways consolidation) or a sudden direction change of the stock (bounce). Remember, the script will paint all Alpha candles regardless.
NVAX day trading example
Forex
Crypto
PLUG (Bounce example)
The script will identify the Alpha candles that are breaking to a new high / low from a user input look back period (default is 20 bars back, but this can be changed by the user input). An Alpha candle that breaks the look back period, will have a stop loss line below for Green Alpha or above for Red Alpha Candle and reward targets, like target1 or target2 (both are user input fields, can be adjusted to personal R values, default values are 2R and 3R)
A 2R means two times the reward (profit) of a 1-unit risk. If you are comfortable of loosing $50 per trade which will be considered 1-unit, then 2R means $100 reward (profit) target and a 3R is $150 reward (profit) target. Those R values will be plotted and/or labelled on the chart with dollar amounts if desired. You can change your R values from the user input area, even with decimal points, like 2.5R or 3.75R. If you shoot for at least 2R, you could be wrong 6 times out of 10, and still make 2R profit, as long as the other 4 trades give you a total of 8R. This is a basic trading concept. It will force the new traders to focus on risk/reward rather then a gambling attitude.
The script is meant to work with candle stick chart patterns only, it is NOT meant to work with ranges, line charts or point and figure charts. It will work with time frames like (seconds,1,2,3,5,10 minute or any minutes, daily, weekly). If you are trading IPOs , there might not be enough data for the script to do the calculation, so just be aware.
The script will identify the candles if they are Green Alpha (going up, bullish ) or Red Alpha (going down, bearish ). In order to see them clearly, we’ve greyed out the rest of the candles, and made Green Alpha candles white, and Red Alphas are left as red. You can change the colors from the user input area.
There is also a look back period, between 1-55 and the initial value is 20 for Green Alpha and 10 for Red Alpha. So, if the Alpha Candle breaks this look back period, it will be considered as an opportunity to take the trade. The code will put the stop loss area, possible target1 and target2 areas with a blue diamond and will draw the resistance/support lines for that Alpha candle. Depending on the individual’s risk tolerance, a label on the right side of the screen will show the risk tolerance (user input value) and the number of shares to be traded based on the risk tolerance (# of shares will be for the last Alpha Candle that is formed, it will constantly update itself with the new Alpha Candle)
For those who might be familiar with the three-bar play, we implemented something similar, so the code will find them in real time. Once an Alpha Candle is formed, if the following candle is a very small candle, also called pin bar , it will be painted to orange, so you can see it clearly. This pin bar is significantly smaller than the previous candles and formed right after an Alpha Candle.
Like anything in life, nothing is free. Meaning you have to work for it. So if you are looking to buy/sell blindly based on some indicators and signals, please do not consider this script. However, once you start using it, you will see how patterns repeat, when they repeat and how they repeat. It will identify the action, but you have to check the validity from the charts, so user discretionary is advised. As an example, if the Alpha candle is breaking from a consolidation period at $10. Let’s assume stop loss is at $9 so the 2R target will be $12, but if there is a possible resistance at $11, then the trader has to decide to take the trade for a possible 1R return, or skip the trade.
We try to approach the trading as a set of rules and processing the trades one by one, with a calculated risk and reward. This script will give you the Candle stick formation that is worth consideration and will draw the Stop Loss area (you can tweak this to your liking), will draw the 2-3R Targets, and will calculate the number of shares to be purchased based on the Risk Tolerance user entered in the user input area. The rest is to let the trade take care of it self.
Charts and patterns work better, when there is enough volume in a particular stock. If the stock is trading very low in volume , things will not work as expected. So, we must focus on the abnormal stocks, like gap gainers, volume gainer stocks, or heavily traded stocks (for intraday trading). For swing or long-term traders, one could look for a Green Alpha candle, assess the risk and possible return and trade the plan on a daily chart pattern (long term), or 15,30,60 min charts for swing trades.
If you are looking to short a stock, look for stocks that are weak (gap downs), so look for Red Alpha formations in that stock.
Once the back testing is turned on, code will generate buy/sell signals, otherwise it will work as an indicator. But please keep in mind….. For day trading, the stock has to be abnormally trading, so the chart patterns and the Alpha Candles work correctly. Volume has to be more than usual. It is the best way to have predictable results for day trading. If the volume of the stock is 2-5 times or more than the average of 20 days period (early in the morning), and even more later in the day, it is a good indication that the stock is trading on an abnormal volume with some news (pre-market abnormality is a good sign for possible abnormality for that stock).
For back testing, user can select from the user input area :
• Long or Short Trades or both or use the script as an indicator
• Close any open position if an Alpha candle forms in the opposite direction
• Pyramid the trades up to 4 levels (allow to buy/sell 4 times in the same direction every time another Alpha Candle forms)
• Breakout/breakdown look back period (every time an Alpha Candle forms and breaks this look back period, it will be a trade opportunity)
• Target Reward areas
• Stop Loss area
• Time frame (change the time frame and observe which time frame made good profit. Test the plan for future trades. Test it in as many abnormal stocks for the day they were behaving abnormal as possible). Time frame is not a user input field, just the time frame of the chart, 2,5,10 min, 1 hour etc.
• Selective date testing (between two dates/times). This is very important as most of the good opportunities comes from abnormal price action with volume . If you back test with the maximum amount of data for that abnormal stock on that day, it will produce unrealistic results, because the stock will have a normal course of trend before the news. Remember, we are looking for stocks that are trading abnormal in both price and volume or stocks like AAPL , TSLA which are trading heavily on each day. It is also a good way to learn, how and when to buy/sell, where to put stop losses by observing the chart with the Alpha Candles showing the results.
• All the above values will have an impact on the total profit / loss.
F (Ford Motors)
Now that we’ve covered what the script does, let’s plan the trade and trade the plan.
Side Note:
-------------
We started coding this as an indicator to show the Alpha Candles to find opportunities in the market. Later in the development, we implemented it as a Strategy, to be able to back test the ideas, to tweak some rules for entry/exit and see the effects on our profit/loss percentages in general. We kept the original idea being an Indicator, to show us the Alpha Candles in real time. This requires the option “Indicator Mode” is to be selected from the User Input area, and leaving the “Recalculate On Every Tick” is selected from the Properties tab of the strategy (as of Pine Script v5). Strategy is turning this “On” by default.
Disclaimer: This script is an educational and personal use only tool and should be used accordingly. User can not publish any images created with this code. Do your own due diligence, do not buy / sell stocks based on any indicator, always use stop losses. We do not make any promises as this indicator or any indicator will make you a profitable trader. Trading and technical analysis is difficult, it takes time to build confidence and experience. Study the charts and candlestick formations. Study support/resistance areas and how to identify them. This will help you to tweak the script’s stop loss areas and 2R-3R targets. Do not invest any money you are not comfortable loosing.
This is an invite only strategy. We will give ample time to test it out. After that you will need to subscribe. To get access to this strategy trader can send me an email from the links below.
All the Best
Happy Trading
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
magic wand STSM"Magic Wand STSM" Strategy: Trend-Following with Dynamic Risk Management
Overview:
The "Magic Wand STSM" (Supertrend & SMA Momentum) is an automated trading strategy designed to identify and capitalize on sustained trends in the market. It combines a multi-timeframe Supertrend for trend direction and potential reversal signals, along with a 200-period Simple Moving Average (SMA) for overall market bias. A key feature of this strategy is its dynamic position sizing based on a user-defined risk percentage per trade, and a built-in daily and monthly profit/loss tracking system to manage overall exposure and prevent overtrading.
How it Works (Underlying Concepts):
Multi-Timeframe Trend Confirmation (Supertrend):
The strategy uses two Supertrend indicators: one on the current chart timeframe and another on a higher timeframe (e.g., if your chart is 5-minute, the higher timeframe Supertrend might be 15-minute).
Trend Identification: The Supertrend's direction output is crucial. A negative direction indicates a bearish trend (price below Supertrend), while a positive direction indicates a bullish trend (price above Supertrend).
Confirmation: A core principle is that trades are only considered when the Supertrend on both the current and the higher timeframe align in the same direction. This helps to filter out noise and focus on stronger, more confirmed trends. For example, for a long trade, both Supertrends must be indicating a bearish trend (price below Supertrend line, implying an uptrend context where price is expected to stay above/rebound from Supertrend). Similarly, for short trades, both must be indicating a bullish trend (price above Supertrend line, implying a downtrend context where price is expected to stay below/retest Supertrend).
Trend "Readiness": The strategy specifically looks for situations where the Supertrend has been stable for a few bars (checking barssince the last direction change).
Long-Term Market Bias (200 SMA):
A 200-period Simple Moving Average is plotted on the chart.
Filter: For long trades, the price must be above the 200 SMA, confirming an overall bullish bias. For short trades, the price must be below the 200 SMA, confirming an overall bearish bias. This acts as a macro filter, ensuring trades are taken in alignment with the broader market direction.
"Lowest/Highest Value" Pullback Entries:
The strategy employs custom functions (LowestValueAndBar, HighestValueAndBar) to identify specific price action within the recent trend:
For Long Entries: It looks for a "buy ready" condition where the price has found a recent lowest point within a specific number of bars since the Supertrend turned bearish (indicating an uptrend). This suggests a potential pullback or consolidation before continuation. The entry trigger is a close above the open of this identified lowest bar, and also above the current bar's open.
For Short Entries: It looks for a "sell ready" condition where the price has found a recent highest point within a specific number of bars since the Supertrend turned bullish (indicating a downtrend). This suggests a potential rally or consolidation before continuation downwards. The entry trigger is a close below the open of this identified highest bar, and also below the current bar's open.
Candle Confirmation: The strategy also incorporates a check on the candle type at the "lowest/highest value" bar (e.g., closevalue_b < openvalue_b for buy signals, meaning a bearish candle at the low, suggesting a potential reversal before a buy).
Risk Management and Position Sizing:
Dynamic Lot Sizing: The lotsvalue function calculates the appropriate position size based on your Your Equity input, the Risk to Reward ratio, and your risk percentage for your balance % input. This ensures that the capital risked per trade remains consistent as a percentage of your equity, regardless of the instrument's volatility or price. The stop loss distance is directly used in this calculation.
Fixed Risk Reward: All trades are entered with a predefined Risk to Reward ratio (default 2.0). This means for every unit of risk (stop loss distance), the target profit is rr times that distance.
Daily and Monthly Performance Monitoring:
The strategy tracks todaysWins, todaysLosses, and res (daily net result) in real-time.
A "daily profit target" is implemented (day_profit): If the daily net result is very favorable (e.g., res >= 4 with todaysLosses >= 2 or todaysWins + todaysLosses >= 8), the strategy may temporarily halt trading for the remainder of the session to "lock in" profits and prevent overtrading during volatile periods.
A "monthly stop-out" (monthly_trade) is implemented: If the lres (overall net result from all closed trades) falls below a certain threshold (e.g., -12), the strategy will stop trading for a set period (one week in this case) to protect capital during prolonged drawdowns.
Trade Execution:
Entry Triggers: Trades are entered when all buy/sell conditions (Supertrend alignment, SMA filter, "buy/sell situation" candle confirmation, and risk management checks) are met, and there are no open positions.
Stop Loss and Take Profit:
Stop Loss: The stop loss is dynamically placed at the upTrendValue for long trades and downTrendValue for short trades. These values are derived from the Supertrend indicator, which naturally adjusts to market volatility.
Take Profit: The take profit is calculated based on the entry price, the stop loss, and the Risk to Reward ratio (rr).
Position Locks: lock_long and lock_short variables prevent immediate re-entry into the same direction once a trade is initiated, or after a trend reversal based on Supertrend changes.
Visual Elements:
The 200 SMA is plotted in yellow.
Entry, Stop Loss, and Take Profit lines are plotted in white, red, and green respectively when a trade is active, with shaded areas between them to visually represent risk and reward.
Diamond shapes are plotted at the bottom of the chart (green for potential buy signals, red for potential sell signals) to visually indicate when the buy_sit or sell_sit conditions are met, along with other key filters.
A comprehensive trade statistics table is displayed on the chart, showing daily wins/losses, daily profit, total deals, and overall profit/loss.
A background color indicates the active trading session.
Ideal Usage:
This strategy is best applied to instruments with clear trends and sufficient liquidity. Users should carefully adjust the Your Equity, Risk to Reward, and risk percentage inputs to align with their individual risk tolerance and capital. Experimentation with different ATR Length and Factor values for the Supertrend might be beneficial depending on the asset and timeframe.
ATR Combined IndicatorHow to Use and Adjust the ATR Stop-Loss & Risk Manager Indicator in TradingView
The ATR Stop-Loss & Risk Manager indicator is designed to help traders visualize Average True Range (ATR)-based stop-loss levels and assess risk. Here's a step-by-step guide on how to use it and adjust its settings.
Adding the Indicator to Your Chart
Open TradingView and select your desired chart and time frame.
Click on the Pine Editor at the bottom of the screen.
Paste the provided script into the editor and click Add to Chart.
Once added, the indicator will appear on your chart with ATR values, stop-loss levels, and a risk table.
Indicator Outputs
ATR Line: A line representing the Average True Range (ATR) value, providing a measure of market volatility.
Stop-Loss Levels:
Stop Loss High: A green line above the current price, representing the suggested stop-loss level for long positions.
Stop Loss Low: A red line below the current price, representing the suggested stop-loss level for short positions.
Risk Table:
Displays the ATR value multiplied by a user-defined risk multiplier in a table on the chart.
Configuring the Settings
To customize the indicator for your trading strategy, click the gear icon next to the indicator’s name in the Indicators pane.
1. ATR Settings
ATR Period: Adjust the number of bars used to calculate the ATR. Common values include 14 (default) or 20. Shorter periods respond faster to price changes, while longer periods smooth volatility.
Smoothing Method:
Choose between RMA, SMA, EMA, or WMA for the ATR calculation:
RMA (default): A variation of the moving average commonly used in ATR.
SMA: Simple Moving Average, giving equal weight to all bars in the calculation.
EMA: Exponential Moving Average, which gives more weight to recent bars.
WMA: Weighted Moving Average, emphasizing recent prices linearly.
2. Multipliers
ATR Multiplier for Table: Adjust this to scale the ATR value displayed in the table. For example:
Set it to 1.0 to display the exact ATR.
Increase or decrease it to align with your risk tolerance.
Stop Loss Multiplier: Adjust this to change how far the stop-loss levels are plotted from the current price. For example:
Use 1.5 (default) for moderate levels.
Increase for wider stops or decrease for tighter stops.
3. Table Customization
Table Position: Select where the table appears on the chart:
Top Right (default), Top Left, Bottom Right, Bottom Left, Middle Right, or Middle Left.
Border Color: Choose the border color for the table.
Background Color: Set the table's background color.
Text Color: Customize the table text color for better visibility.
4. Visualization
Stop-Loss High and Low Lines:
Use these lines to determine potential stop-loss levels for your trades based on the ATR and stop-loss multiplier.
Green for Stop Loss High (long positions).
Red for Stop Loss Low (short positions).
Practical Use Cases
Volatility-Based Stop Losses:
Use the stop-loss lines to set dynamic stop-loss levels based on market volatility.
Adjust the multipliers to match your trading style:
Tight stops for scalping or day trading.
Wider stops for swing or position trading.
Risk Assessment:
Use the ATR value in the table to gauge market volatility before entering trades.
Higher ATR values indicate more volatile markets, requiring wider stops.
Position Sizing:
Incorporate the ATR value into your position-sizing strategy. For example:
Divide your account risk (e.g., 1% of equity) by the ATR to calculate position size.
TDGS Dynamic Grid Trading Strategy [CoinFxPro]Advanced Dynamic Grid Trading Strategy
Logic and Working Principle:
This strategy uses a dynamic grid system to support both long and short trades. Grid trading aims to capitalize on price fluctuations within a predefined range by executing buy and sell orders systematically. The system calculates grid levels based on a base price and dynamically trades within these levels.
Grid Levels:
Grid levels are calculated based on the initial price and the user-defined grid spacing percentage.
Long Mode: Buys when the price decreases and sells when the price increases.
Short Mode: Sells when the price increases and buys when the price decreases.
Grid Updates:
Grid levels are recalculated based on the market price when the price moves by a user-defined update percentage.
For example;
In Long mode, when the price shows an upward trend, that is, when it rises by the Grid Update Percentage specified by the user, Grid levels are recreated and trades are made according to the new grid levels. While the price and grid levels are updated according to the new price, the Stop level is also updated upwards and the stop is followed with the TrailingStop logic.
In short mode, the same system operates with reverse logic. In other words, as prices decrease downwards, the grids are updated downwards when the Grid update percentage determined by the user decreases. The stop level is also updated accordingly.
The difference of the strategy from other Gridbots is that the grid levels are automatically updated and the levels are recreated with the price percentage difference determined by the user. Old levels can be tracked on the chart.
As the price updates, the self-updating grid levels are updated upwards in long mode and downwards in short mode.
The number of buying lots and selling lots are separated, allowing both trading within the position and the opportunity to collect lots and increase the position.
When trading with the grid trading logic, when buying and selling between grids, there is no repeated purchase at the same level unless there is a sale at the upper grid level. In this way, each level will be traded within itself.
For example, in a long condition, when the price is going up, after deducting the selling lot from the buying lot at each level, the remaining lots will be collected while the price is going up and an opportunity will be provided from the price rise.
Different preferences have been added to the profit taking conditions, allowing the robot to continue or stop after profit taking, if desired.
The system, which acts entirely according to user parameters, constantly updates itself as long as it moves in the direction determined by itself, and in these conditions, transactions are carried out according to profit or stop conditions.
Parameters:
Grid Parameters:
Settings such as buy lot size, sell lot size, grid count, and grid spacing percentage allow flexibility and customization.
Risk Management:
Stop loss (%) and take profit (%) levels help limit potential losses and secure profits at predefined thresholds.
Objective:
The goal of this strategy is to systematically capitalize on market price fluctuations through automated grid trading. This method is particularly effective in volatile markets where the price oscillates within a specific range.
The strategy works with a complete algorithm logic, and in appropriate instruments (especially instruments with depth and transaction volume should be preferred), buying and selling transactions are made according to the parameters determined at the beginning, and if the conditions go beyond the conditions, the stop is made, and when the profit taking conditions are met, it takes profit and prices according to the determined value. When it is updated, the values are updated again and the parameter works algorithmically.
Risk Management Recommendations:
Initial Capital: Grid trading involves frequent transactions, so sufficient initial capital is essential.
Stop Loss: Always set stop loss levels to prevent significant losses.
Grid Count and Spacing: A higher number of grids provides more trading opportunities but using grids that are too close may increase transaction costs due to small price movements.
First of all, it is important for risk management that you choose instruments that have depth and high transaction volume.
Strategy results may differ as a result of the parameters entered. Therefore, before trading in your real account, it is recommended that you start real transactions after backtesting with different parameters.
If you are stuck on something, you can mention it in the comments.
Consecutive Higher/Lower Closes with Breakout LineIndicator Description:
"Four Consecutive Higher/Lower Closes with Auto Breakout Line Timeframe" is a custom TradingView indicator designed to help traders identify key breakout points based on consecutive price action. It combines two main features:
Four Consecutive Higher/Lower Closes – Detects bullish or bearish momentum through consecutive higher or lower closing prices.
Auto Breakout Line – Plots a breakout line that adapts to the timeframe of the chart, helping to visualize potential breakout levels and trends.
Features:
Higher/Lower Close Detection: The indicator tracks and plots lines when there are four consecutive higher closes (bullish) or four consecutive lower closes (bearish). This can signal a trend or momentum in the market.
Breakout Line: It draws an adaptive breakout line that adjusts based on the selected timeframe (i.e., the chart interval), helping traders visually identify breakout levels across different timeframes.
Timeframe Adaptability: The indicator automatically adjusts the breakout line timeframe based on the chart interval (e.g., 15 minutes for lower timeframes and 1 day for higher timeframes).
Customizable Timeframe and Color: The default color for breakout lines is purple, but it is customizable. You can also enable/disable the breakout line through the settings.
How to Use This Indicator for Trading:
1. Trading with Consecutive Higher/Lower Closes:
Bullish Signal: When the indicator detects four consecutive higher closes, it signifies increasing buying momentum. Traders might consider taking long positions when this occurs, especially if the price continues to close higher.
Bearish Signal: When the indicator detects four consecutive lower closes, it signals increasing selling pressure. Traders might consider taking short positions if the price continues to close lower.
Confirmation: The fourth consecutive higher or lower close should be confirmed with additional analysis, such as candlestick patterns, support/resistance levels, or volume.
2. Using the Breakout Line:
The breakout line is designed to help traders identify potential breakout levels. When the price approaches or crosses this line, it could indicate that the market is either breaking out in the direction of the trend or failing to continue the trend.
Bullish Breakout: If the price crosses the breakout line upwards (after four consecutive higher closes), it may confirm that a bullish breakout is in progress. This can be a good opportunity to take a long position.
Bearish Breakout: If the price crosses the breakout line downwards (after four consecutive lower closes), it may confirm that a bearish breakout is occurring. This can be an opportunity to take a short position.
Avoid False Breakouts: It is important not to react to every price move crossing the breakout line. Wait for additional confirmation signals like higher volume, candlestick patterns (e.g., bullish or bearish engulfing), or other technical indicators (e.g., RSI, MACD) to confirm the breakout's validity.
How to Avoid Fake Breakouts:
A fake breakout occurs when the price moves beyond a breakout level but then quickly reverses back inside the range, trapping traders who took positions in the breakout direction.
Here are strategies to avoid fake breakouts:
1. Volume Confirmation:
A valid breakout is often supported by higher volume. If the price crosses the breakout line but the volume is low, it's more likely to be a fake breakout. Always check the volume when a breakout occurs.
Look for volume spikes that accompany the breakout. A surge in volume confirms the market's conviction in the new trend.
2. Candlestick Patterns:
Bullish/bearish engulfing patterns or Doji candles can provide important insights into potential reversals. If a breakout occurs but is immediately followed by a bearish engulfing candle, it's a sign that the breakout may be false.
Also, check for candlestick formations at key support or resistance levels for confirmation.
3. Time Confirmation:
Wait for the close of the current bar to confirm the breakout. A breakout within a single bar without closing above or below a significant level could be a false move.
Sometimes the market will test the breakout level before committing to the direction. This is common in volatile or choppy market conditions.
4. Use of Other Indicators:
RSI (Relative Strength Index): An overbought or oversold condition can indicate a potential reversal after a breakout.
MACD (Moving Average Convergence Divergence): Watch for a MACD crossover that aligns with the breakout direction to confirm the move.
5. Use Stop Losses:
A key rule in avoiding fake breakouts is to always use stop-loss orders. Set your stop-loss just outside the breakout level to avoid excessive losses if the price reverses.
Trailing stops can also help lock in profits if the price moves in your favor but may reverse at a later point.
Summary:
The Four Consecutive Higher/Lower Closes with Auto Breakout Line Timeframe indicator is a valuable tool for identifying strong trends and potential breakouts in the market. By combining consecutive close patterns with dynamic breakout levels, it can help traders spot bullish or bearish momentum and make more informed trading decisions. However, always confirm breakouts with volume, candlestick patterns, and other technical indicators to avoid fake breakouts and reduce the risk of false signals.
By using this indicator along with prudent risk management strategies, traders can improve their chances of entering and exiting trades at the right time while avoiding unnecessary losses from false breakouts.
ADX Breakout Strategy█ OVERVIEW
The ADX Breakout strategy leverages the Average Directional Index (ADX) to identify and execute breakout trades within specified trading sessions. Designed for the NQ and ES 30-minute charts, this strategy aims to capture significant price movements while managing risk through predefined stop losses and trade limits.
This strategy was taken from a strategy that was posted on YouTube. I would link the video, but I believe is is "against house rules".
█ CONCEPTS
The strategy is built upon the following key concepts:
ADX Indicator: Utilizes the ADX to gauge the strength of a trend. Trades are initiated when the ADX value is below a certain threshold, indicating potential for trend development.
Trade Session Management: Limits trading to specific hours to align with optimal market activity periods.
Risk Management: Implements a fixed dollar stop loss and restricts the number of trades per session to control exposure.
█ FEATURES
Customizable Stop Loss: Set your preferred stop loss amount to manage risk effectively.
Trade Session Configuration: Define the trading hours to focus on the most active market periods.
Entry Conditions: Enter long positions when the price breaks above the highest close in the lookback window and the ADX indicates potential trend strength.
Trade Limits: Restrict the number of trades per session to maintain disciplined trading.
Automated Exit: Automatically closes all positions at the end of the trading session to avoid overnight risk.
█ HOW TO USE
Configure Inputs :
Stop Loss ($): Set the maximum loss per trade.
Trade Session: Define the active trading hours.
Highest Lookback Window: Specify the number of bars to consider for the highest close.
Apply the Strategy :
Add the ADX Breakout strategy to your chart on TradingView.
Ensure you are using a 30-minute timeframe for optimal performance.
█ LIMITATIONS
Market Conditions: The strategy is optimized for trending markets and may underperform in sideways or highly volatile conditions.
Timeframe Specific: Designed specifically for 30-minute charts; performance may vary on different timeframes.
Single Asset Focus: Primarily tested on NQ and ES instruments; effectiveness on other symbols is not guaranteed.
█ DISCLAIMER
This ADX Breakout strategy is provided for educational and informational purposes only. It is not financial advice and should not be construed as such. Trading involves significant risk, and you may incur substantial losses. Always perform your own analysis and consider your financial situation before using this or any other trading strategy. The source material for this strategy is publicly available in the comments at the beginning of the code script. This strategy has been published openly for anyone to review and verify its methodology and performance.
Fibonacci Swing Trading BotStrategy Overview for "Fibonacci Swing Trading Bot"
Strategy Name: Fibonacci Swing Trading Bot
Version: Pine Script v5
Purpose: This strategy is designed for swing traders who want to leverage Fibonacci retracement levels and candlestick patterns to enter and exit trades on higher time frames.
Key Components:
1. Multiple Timeframe Analysis:
The strategy uses a customizable timeframe for analysis. You can choose between 4hour, daily, weekly, or monthly time frames to fit your preferred trading horizon. The high and low-price data is retrieved from the selected timeframe to identify swing points.
2. Fibonacci Retracement Levels:
The script calculates two key Fibonacci retracement levels:
0.618: A common level where price often retraces before resuming its trend.
0.786: A deeper retracement level, often used to identify stronger support/resistance areas.
These levels are dynamically plotted on the chart based on the highest high and lowest low over the last 50 bars of the selected timeframe.
3. Candlestick Based Entry Signals:
The strategy uses candlestick patterns as the only indicator for trade entries:
Bullish Candle: A green candle (close > open) that forms between the 0.618 retracement level and the swing high.
Bearish Candle: A red candle (close < open) that forms between the 0.786 retracement level and the swing low.
When these candlestick patterns align with the Fibonacci levels, the script triggers buy or sell signals.
4. Risk Management:
Stop Loss: The stop loss is set at 1% below the entry price for long trades and 1% above the entry price for short trades. This tight risk management ensures controlled losses.
Take Profit: The strategy uses a 2:1 risk-to-reward ratio. The take profit is automatically calculated based on this ratio relative to the stop loss.
5. Buy/Sell Logic:
Buy Signal: Triggered when a bullish candle forms above the 0.618 retracement level and below the swing high. The bot then places a long position.
Sell Signal: Triggered when a bearish candle forms below the 0.786 retracement level and above the swing low. The bot then places a short position.
The stop loss and take profit levels are automatically managed once the trade is placed.
Strengths of This Strategy:
Swing Trading Focus: The strategy is ideal for swing traders, targeting longer-term price moves that can take days or weeks to play out.
Simple Yet Effective Indicators: By only relying on Fibonacci retracement levels and basic candlestick patterns, the strategy avoids complexity while capitalizing on well-known support and resistance zones.
Automated Risk Management: The built-in stop loss and take profit mechanism ensures trades are protected, adhering to a strict 2:1 risk/reward ratio.
Multiple Timeframe Analysis: The script adapts to various market conditions by allowing users to switch between different timeframes (4hour, daily, weekly, monthly), giving traders flexibility.
Strategy Use Cases:
Retracement Traders: Traders who focus on entering the market at key retracement levels (0.618 and 0.786) will find this strategy especially useful.
Trend Reversal Traders: The strategy’s reliance on candlestick formations at Fibonacci levels helps traders spot potential reversals in price trends.
Risk Conscious Traders: With its 1% risk per trade and 2:1 risk/reward ratio, the strategy is ideal for traders who prioritize risk management in their trades.
Dow Theory based Strategy (Markttechnik)What makes this script unique?
calculates two trends at the same time: a big one for the overall strong trend - and a small one to trigger a trade after a small correction within the big trend
only if both trends (the small and the big trend) are in an uptrend, a buy signal is created: this prevents a buy signal from being generated in a falling market just because an upward movement begins in a small trend
the exit strategy can be configured very flexibly and individually: use the last low as stop loss and automatically switch to a trialing stop loss as soon as the take profit is reached (instead of finishing the trade)
the take profit strategy can also be configured - e.g. use the last high, a fixed percentage or a combination of it
plots each trade in detail on the chart - e.g. inner candles or the exact progression of the stop loss over the entire duration of the trade to allow you to analyze each trade precisely
What does the script do and how?
In this strategy an intact upward trend is characterized by higher highs and lower lows only if the big trend and the small trend are in an upward trend at the same time.
The following describes how the script calculates a buy signal. Every step is drawn to the chart immediately - see example chart above:
1. the stock rises in the big trend - i.e. in a longer time frame
2. a correction takes place (the share price falls) - but does not create a new low
3. the stock rises again in the big trend and creates a new high
From now on, the big trend is in an intact upward trend (until it falls below its last low).
This is drawn to the chart as 3 bold green zigzag lines.
But we do not buy right now! Instead, we want to wait for a correction in the big trend and for the start of a small upward trend.
4. a correction takes place (not below the low from 2.)
Now, the script also starts to calculate the small trend:
5. the stock rises in the small trend - i.e. in a shorter time frame
6. a small correction takes place (not below the low from 4.)
7. the stock rises above the high from 5.: a new high in the shorter time frame
Now, both trends are in an intact upward trend.
A buy signal is created and both the minor and major trend are colored green on the chart.
Now, the trade is active and:
the stop loss is calculated and drawn for each candle
the take profit is calculated and drawn to the chart
as soon as the price reaches the take profit or the stop loss, the trade is closed
Features and functionalities
Uptrend : An intact upward trend is characterized by higher highs and lower lows. Uptrends are shown in green on the chart.
The beginning of an uptrend is numbered 1, each subsequent high is numbered 2, and each low is numbered 3.
Downtrend: An intact downtrend is characterized by lower highs and lower lows. Downtrends are displayed in red on the chart.
Note that our indicator does not show the numbering of the points of the downtrend.
Trendless phases: If there is no intact trend, we are in a trendless phase. Trendless phases are shown in blue on the chart.
This occurs after an uptrend, when a lower low or a lower high is formed. Or after a downtrend, when a higher low or a higher high is formed.
Buy signals
A buy signal is generated as soon as a new upward trend has been formed or a new high has been established in an intact upward trend.
But even before a buy signal is generated, this strategy anticipates a possible emerging trend and draws the next possible trading opportunity to the chart.
In addition to the (not yet reached) buy price, the risk-reward ratio, the StopLoss and the TakeProfit price is shown.
With this information, you can already enter a StopBuy order, which is thus triggered directly with the then created buy signal.
You can configure, if a buy signal shall be created while the big trend is an uptrend, a downtrend and/or trendless.
Exit strategy
With this strategy, you have multiple possibilities to close your position. All of them can be configured within the settings. In general, you can combine a take profit strategy with a stop loss strategy.
The take profit price will be calculated once for each trade. It will be drawn to the chart for active trade.
Depending on your configuration, this can be the last high (which is often a resistance level), a fixed percentage added to the buy price or the maximum of both.
You can also configure that a trailing stop loss is used as soon as the take profit price is reached once.
The stop loss gets recalculated with each candle and is displayed and plotted for each active and finished trade. With this, you can easily check how the stop loss changed during your trades.
The stop loss can be configured flexibly:
Use the classic "trailing stop loss" that follows the price from below.
Set the stop loss to the last low and tighten it every time the small trend marks a new local low.
Confiure that the stop loss is tightened as soon as the break even is reached. Nothing is more annoying than a trade turning from a win to a loss.
Ignore inside candles (see description below) and relax the stop loss to use the outside candle for its calculation.
Inner candles
Inner candles are created when the candle body is within the maximum values of a previous candle (the outer candle). There can be any number of consecutive inner candles. As soon as you have activated the "Check inner candles" setting, all consecutive inner candles will be highlighted in yellow on the chart.
Prices during an inner candle scenario might be irrelevant for trading and can be interpreted as fluctuations within the outside candle. For this reason, the trailing stop loss should not be aligned with inner candles. Therefore, as soon as an inner candle occurs, the stop loss is reset and the low at the time of the outside candle is used as the calculation for the trailing stop loss. This will all be plotted for you on the chart.
Display of the trades:
All active and closed trades of the last 5 years are displayed in the chart with buy signal, sell, stop loss history, inside candles and statistics.
Backtesting:
The strategy can be simulated for each stock over the period of the last 5 years. Each individual trade is recorded and can be traced and analyzed in the chart including stop loss history. Detailed evaluations and statistics are available to evaluate the performance of the strategy.
Additional Statistics
This strategy immediately displays a statistic table to the chart area giving you an overview of its performance over the last years for the given chart.
This includes:
The total win/loss in $ and %
The win/loss per year in %
The active investment time in days and % (e.g. invested 10 of 100 trading days -> 10%)
The total win/loss in %, extrapolated to 100% equity usage: Only with this value can strategies really be compared. Because you are not invested between the trades and could invest in other stocks during this time. This value indicates how much profit you would have made if you had been invested 100% of the time - or to put it another way - if you had been invested 100% of the time in stocks with exactly the same performance. Let's say you had only one trade in the last 5 years that lasted, say, only one month and made 5% profit. This would be significantly better than a strategy with which you were invested for, say, 5 years and made 10% profit.
The total profit/loss per year in %, extrapolated to 100% equity usage
Notifications (alerts):
Get alerted before a new buy signal emerges to create an order if necessary and not miss a trade. You can also be notified when the stop loss needs to be adjusted. The notification can be done in different ways, e.g. by Mail, PopUp or App-Notification. This saves them the annoying, time-consuming and error-prone "click through" all the charts.
Settings: Display Settings
With these settings, you have the possibility to:
Show the small or the big trend as a background color
Configure if the numbers (1-2-3-2-3) shall be shown at all or only for the small, the big trend or both
Settings: Trend calculation - fine tuning
Drawing trend lines on a chart is not an exact science. Some highs and lows are not very clear or significant. And so it will always happen that 2 different people would draw different trendlines for the same chart. Unfortunately, there is no exact "right" or "wrong" here.
With the options under "Trend Calculation - Fine Tuning" you have the possibility to influence the drawing in of trends and to adapt it to your personal taste.
Small Trend, Big Trend : With these settings you can influence how significant a high or low has to be to recognize them as an independent high or low. The larger the values, the more significant a high or low must be to be recognized as such.
High and low recognition : With this setting you can influence when two adjacent, almost identical highs or lows should be recognized as independent highs or lows. The higher the value, the more different "similar" highs or lows must be in order to be recognized as such.
Which default settings were selected and why
Show Trades: true - its often useful to see all recent trades in the chart
Time Frame: 1 day - most common time frame (except for day traders)
Take Profit: combined 10% - the last high is taken as take profit because the trend often changes there, but only if there is at least 10% profit to ensure we do not risk money for a tiny profit
Stop Loss: combined - the last low is used as stop loss because the trend would break there and switch to a trailing stop loss as soon as our take profit is reached to let our profits run without risking them anymore
Stop Loss distance: 3% - we are giving the price 3% air (below the last low) to avoid being stopped out due to a short price drop
Trailing Stop Loss: 2% - we have to give the stop loss some room to avoid being stopped out prematurely; this is a value that is well balanced between a certain downside distance and the profit-taking ratio
Set Stop Loss to break even: true, 2% - once we reached the break even, it is a common practice to not risk our money anymore, the value is set to the same value as the trailing stop loss
Trade Filter: Uptrend - we only start trades if the big trend is an uptrend in the expectation that it will continue after a small correction
Display settings: those will not influence the trades, feel free to change them to your needs
Trend calculation - Fine Tuning: 1/1,5/0,05; influences the internal calculation for highs and lows and how significant they need to be to be considered a new high or low; the default values will provide you nicely calculated trends in the daily time frame; if there are too many or too few lows and highs according to your taste, feel free to play around and immediately see the result drawn to the chart; read the manual for a detailed description of this values
Note that you can (and should) configure the general trading properties like your initial capital, order size, slippage and commission.
MAHA Luxmi AI Candles [Overlay]The MAHA Luxmi AI Candles trading indicator is a sophisticated tool designed to assist traders in identifying potential trading opportunities by utilizing a combination of Moving Average (MA) and Heikin-Ashi (HA) techniques, further enhanced with a custom formula. Here’s a detailed breakdown of its functionalities:
1. Integration of MA and HA Techniques
MAHA stands for Moving Average and Heikin-Ashi. This indicator modifies these traditional techniques with a unique custom formula, aiming to provide more accurate and reliable signals for traders. The combination enhances the smoothing effect of Moving Averages with the trend indication of Heikin-Ashi candles.
2. Four-Colored Candles for Trend Indication
The indicator uses a color-coded system to denote different market conditions and potential trading opportunities:
- Green Candles: These candles indicate a potential long opportunity. The appearance of a green candle suggests that the market is showing bullish tendencies, prompting traders to consider entering a long position.
- Blue Candles: These candles signify an active pullback within a bullish trend. The blue candle warns traders of a possible temporary reversal within the overall bullish trend, suggesting caution and the need for confirmation before continuing with a long position or preparing for a potential reversal.
- Red Candles: These candles represent a potential short opportunity. A red candle indicates bearish market conditions, signaling traders to consider entering a short position.
- Yellow Candles: These candles denote an active pullback within a bearish trend. The presence of a yellow candle indicates a temporary reversal within the bearish trend, urging traders to be cautious with short positions and look for signs of continuation or reversal.
3. MAHA Bars for Distance and Area of Interest
In addition to the colored candles, the MAHA Luxmi AI Candles indicator also plots MAHA bars. These bars share the same color coding and usage as the candles, providing a consistent visual representation of market conditions:
- Green Bars: Indicate a potential long opportunity, aligning with green candles.
- Blue Bars: Show an active pullback in a bullish trend, aligning with blue candles.
- Red Bars: Represent a potential short opportunity, aligning with red candles.
- Yellow Bars: Indicate an active pullback in a bearish trend, aligning with yellow candles.
The MAHA bars help traders gauge the distance between the current price and the area of interest, enhancing their understanding of how close or far the price is from key levels identified by the MAHA formula. This aids in making better decisions regarding entry and exit points.
4. Trailing Stop Loss Feature
The base of the MAHA Bars can also be used as a trailing stop loss. This feature provides a dynamic stop loss level that adjusts with the market, helping traders lock in profits and limit losses by following the trend. When the price moves favorably, the trailing stop loss adjusts accordingly, ensuring that traders can capitalize on market movements while minimizing risk.
Usage and Benefits
- Trend Identification: The color-coded system simplifies the identification of market trends and potential reversals, making it easier for traders to understand market dynamics at a glance.
- Pullback and Reversal Alerts: The blue and yellow candles/bars alert traders to potential pullbacks and reversals, providing crucial information for managing trades and avoiding false signals.
- Distance Measurement: The MAHA bars help traders measure the distance between the current price and the areas of interest, enhancing their ability to assess the risk and potential reward of trades.
- Trailing Stop Loss: The base of the MAHA Bars can be used as a trailing stop loss, providing a dynamic risk management tool that adapts to market conditions.
Overall, the MAHA Luxmi AI Candles trading indicator is a powerful tool for traders looking to leverage the combined strengths of Moving Averages and Heikin-Ashi techniques. The intuitive color-coded system, additional MAHA bars, and the trailing stop loss feature make it an essential component of a trader’s toolkit for identifying trends, managing risk, and identifying trading opportunities.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
