Advanced Multi-Timeframe Trading System (Risk Managed)Description:
This strategy is an original approach that combines two main analytical components to identify potential trade opportunities while simulating realistic trading conditions:
1. Market Trend Analysis via an Approximate Hurst Exponent
• What It Does:
The strategy computes a rough measure of market trending using an approximate Hurst exponent. A value above 0.5 suggests persistent, trending behavior, while a value below 0.5 indicates a tendency toward mean-reversion.
• How It’s Used:
The Hurst exponent is calculated on both the chart’s current timeframe and a higher timeframe (default: Daily) to capture both local and broader market dynamics.
2. Fibonacci Retracement Levels
• What It Does:
Using daily high and low data from a selected timeframe (default: Daily), the script computes key Fibonacci retracement levels.
• How It’s Used:
• The 61.8% level (Golden Ratio) serves as a key threshold:
• A long entry is signaled when the price crosses above this level if the daily Hurst exponent confirms a trending market.
• The 38.2% level is used to identify short-entry opportunities when the price crosses below it and the daily Hurst indicates non-trending conditions.
Signal Logic:
• Long Entry:
When the price crosses above the 61.8% Fibonacci level (Golden Ratio) and the daily Hurst exponent is greater than 0.5, suggesting a trending market.
• Short Entry:
When the price crosses below the 38.2% Fibonacci level and the daily Hurst exponent is less than 0.5, indicating a less trending or potentially reversing market.
Risk Management & Trade Execution:
• Stop-Loss:
Each trade is risk-managed with a stop-loss set at 2% below (for longs) or above (for shorts) the entry price. This ensures that no single trade risks more than a small, sustainable portion of the account.
• Take Profit:
A take profit order targets a risk-reward ratio of 1:2 (i.e., the target profit is twice the amount risked).
• Position Sizing:
Trades are executed with a fixed position size equal to 10% of account equity.
• Trade Frequency Limits:
• Daily Limit: A maximum of 5 trades per day
• Overall Limit: No more than 510 trades during the backtesting period (e.g., since 2019)
These limits are imposed to simulate realistic trading frequency and to avoid overtrading in backtest results.
Backtesting Parameters:
• Initial Capital: $10,000
• Commission: 0.1% per trade
• Slippage: 1 tick per bar
These settings aim to reflect the conditions faced by the average trader and help ensure that the backtesting results are realistic and not misleading.
Chart Overlays & Visual Aids:
• Fibonacci Levels:
The key Fibonacci retracement levels are plotted on the chart, and the zone between the 61.8% and 38.2% levels is highlighted to show a key retracement area.
• Market Trend Background:
The chart background is tinted green when the daily Hurst exponent indicates a trending market (value > 0.5) and red otherwise.
• Information Table:
An on-chart table displays key parameters such as the current Hurst exponent, daily Hurst value, the number of trades executed today, and the global trade count.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential that you backtest and paper trade using your own settings before considering any live deployment. The Hurst exponent calculation is an approximation and should be interpreted as a rough gauge of market behavior. Adjust the parameters and risk management settings according to your personal risk tolerance and market conditions.
Additional Notes:
• Originality & Usefulness:
This script is an original mashup that combines trend analysis with Fibonacci retracement methods. The description above explains how these components work together to provide trading signals.
• Realistic Results:
The strategy uses realistic account sizes, commission rates, slippage, and risk management rules to generate backtesting results that are representative of real-world trading.
• Educational Purpose:
This script is intended to support the TradingView community by offering insights into combining multiple analysis techniques in one strategy. It is not a “get-rich-quick” system but rather an educational tool to help traders understand risk management and trade signal logic.
By using this script, you acknowledge that trading involves risk and that you are responsible for testing and adjusting the strategy to fit your own trading environment. This publication is fully open source, and any modifications should include proper attribution if significant portions of the code are reused.
Winning
DOGE Trend-Following Strategy – Balanced Risk & Trend (15m)This strategy is designed to capture trends in DOGE/USDT, using a combination of moving averages and momentum indicators to filter high-quality trades. It is optimized for balanced risk management with a focus on reducing drawdowns through conservative position sizing.
How the Strategy Works
Exponential Moving Averages (EMAs):
A fast EMA (default: 50) tracks short-term price momentum.
A slow EMA (default: 200) represents the broader trend.
Trades are executed when these EMAs cross, signaling shifts in market direction.
ADX (Average Directional Index):
ADX (default length: 14) confirms trend strength.
The strategy only enters trades when ADX is above 25, indicating a strong trend. This helps avoid low-confidence trades during sideways markets.
RSI (Relative Strength Index):
RSI (default: 14) helps avoid trades during overbought or oversold conditions.
Long trades are exited when RSI crosses above 70, while short trades are closed when RSI drops below 30.
Multi-Timeframe Filter:
To further validate trends, 4-hour EMAs are integrated into the strategy, keeping entries in sync with larger market movements.
Performance Highlights
Net Profit: +$2,438.85 USDT (0.24% return over testing period)
Profit Factor: 1.136 – indicating more profit than loss overall.
Closed Trades: 35
Winning Trades: 62.86%
Max Drawdown: 0.58% – representing the largest equity decrease during the test period.
Trade Duration: On average, trades last about 40 bars (10 hours on a 15-minute chart).
Trade Setup
Long Entry:
A long position is taken when:
The 50 EMA crosses above the 200 EMA,
The ADX is above 25, and
RSI is above 30 (indicating healthy momentum).
The trade is exited when RSI hits 70 or price reaches a dynamic profit or stop-loss level.
Short Entry:
A short position is entered when:
The 50 EMA crosses below the 200 EMA,
The ADX confirms trend strength above 25, and
RSI is below 70 (avoiding oversold conditions).
The short position closes if RSI drops to 30 or stop-loss/take-profit criteria are met.
Strategy Parameters
Fast EMA Length: Default set to 50.
Slow EMA Length: Default set to 200.
ADX Length: Default set to 14 with a threshold of 25 for filtering trends.
RSI: Length is 14 with overbought/oversold thresholds at 70 and 30.
Dynamic Take Profit & Stop Loss: Configurable, allowing for risk customization.
Backtesting Conditions
Account Size: $100,000
Position Size: 2% of equity per trade – within the recommended 1-5% risk management framework.
Slippage and Commission: Set to realistic values to improve accuracy.
The backtest ran on DOGE/USDT over a multi-month period, showing reliable performance on the 15-minute timeframe. While past performance is not a guarantee of future success, the results suggest this approach may offer a robust framework for trend-following traders.
Strategy Notes
This updated version prioritizes sustainability by ensuring trades risk no more than 2% of equity. The combination of multiple indicators helps avoid whipsaws and improves long-term profitability. Always test strategies with your own data and market conditions before live trading.
Likelihood of Winning - Probability Density FunctionIn developing the "Likelihood of Winning - Probability Density Function (PDF)" indicator, my aim was to offer traders a statistical tool to quantify the probability of reaching target prices. This indicator, grounded in risk assessment principles, enables users to analyze potential outcomes based on the normal distribution, providing insights into market dynamics.
The tool's flexibility allows for customization of the data series, lookback periods, and target settings for both long and short scenarios. It features a color-coded visualization to easily distinguish between probabilities of hitting specified targets, enhancing decision-making in trading strategies.
I'm excited to share this indicator with the trading community, hoping it will enhance data-driven decision-making and offer a deeper understanding of market risks and opportunities. My goal is to continuously improve this tool based on user feedback and market evolution, contributing to more informed trading practices.
This indicator leverages the "NormalDistributionFunctions" library, enabling easy integration into other indicators or strategies. Users can readily embed advanced statistical analysis into their trading tools, fostering innovation within the Pine Script community.
CMARSI Strategy (on ETHUSD) Seems working goodthere it is, it's using the Connor RSI with little variations.
C onnor M oving A verage RSI
