AI-Powered Strategy Optimization
Multi-iteration AI optimization analyzes backtest results and progressively refines strategy parameters to maximize profitability while managing drawdown.
Intelligent Analysis
AI analyzes performance patterns across iterations to understand which parameter combinations lead to better profitability and lower risk.
Progressive Improvement
Each iteration builds on previous results, progressively refining parameters until optimal performance is achieved.
Multi-Parameter Tuning
Optimizes stop loss, ROI targets, trailing stops, and more. Handles complex parameter interactions automatically.
Risk-Adjusted Results
Balances profitability with risk management. Finds parameters that maximize returns while keeping drawdown acceptable.
Optimization Process
Initial Backtest
Run backtest with default parameters to establish baseline performance
AI Analysis
AI analyzes results, identifies patterns, and determines which parameters to adjust
Generate Parameters
AI generates improved parameter set based on performance patterns
New Iteration
Run backtest with new parameters and compare results
Learn & Repeat
AI learns from results and generates next iteration until optimal found
Deploy Best
Automatically deploy the best-performing parameter configuration
Optimized Parameters
Stop Loss Levels
Find optimal stop loss that protects capital without premature exits
ROI Targets
Optimize multiple take-profit levels for maximum profit capture
Trailing Stop
Determine when trailing stops improve or hurt performance
Position Sizing
Optimize position sizes based on volatility and risk
Entry Timing
Fine-tune entry conditions for better win rates
Exit Timing
Optimize exit conditions to maximize profits