improve-trading-strategies

What problem does it solve?

This Skill enables iterative improvement of existing trading strategies through targeted refinements, parameter optimization, and ML-enhanced signals.

Core Features & Use Cases

• Targeted refinement: Make focused code changes to fix issues or add features without rewriting from scratch.
• Parameter optimization: Tune strategy parameters using backtests to improve performance while mitigating overfitting.
• ML integration (Allora): Integrate Allora Network signals as confirmation or primary signals to boost performance.
• Use Case: You have a profitable strategy but want to safely squeeze out more Sharpe with minimal risk; refine, then optimize, then enhance with ML, validating at each step.

Quick Start

1. Load tools: refine_strategy, optimize_strategy, enhance_with_allora
2. Refine a strategy: refine_strategy(strategy_name="MyStrategy", changes_description="Add trailing stop", mode="new")
3. Optimize and validate: optimize_strategy(strategy_name="MyStrategy_refined", start_date="2024-01-01", end_date="2024-12-31", symbol="BTC-USDT", timeframe="1h"); run_backtest(strategy_name="MyStrategy_refined")
4. Enhance with Allora (optional): enhance_with_allora(strategy_name="MyStrategy_refined_optimized", symbol="BTC-USDT", timeframe="1h", start_date="2024-01-01", end_date="2024-12-31")