SignalSense is a machine learning-driven algorithmic trading framework designed to optimize trading strategies across 29 financial instruments. It leverages XGBoost models, feature engineering, and systematic backtesting to enhance predictive accuracy and minimize risk.
- Machine Learning for Trading – Compared LSTM, Prophet, and XGBoost models, selecting XGBoost for its robustness in generalization.
- Risk Management – Applied rolling Sharpe ratio analysis, drawdown tracking, and stop-loss optimization to mitigate losses.
- Backtesting & Forward Testing – Evaluated trading strategies under historical and real-time market conditions to validate performance.
- Portfolio Diversification – Conducted correlation analysis to optimize asset selection and improve risk-adjusted returns.
| Instrument | Best PnL | Sharpe Ratio | Max Drawdown (%) | Total Return (%) |
|---|---|---|---|---|
| LIGHT.CMDUSD | 3470.378 | 0.338 | -0.019 | 0.347 |
| COPPER.CMDUSD | 605.740 | 0.074 | -0.036 | 0.061 |
| SUGAR.CMDUSD | 2776.105 | 0.280 | -0.037 | 0.278 |
| COTTON.CMDUSX | 357.390 | 0.036 | -0.089 | 0.036 |
| USDJPY | 383.533 | 0.086 | -0.017 | 0.038 |
| Instrument | PnL | Sharpe Ratio | Max Drawdown (%) | Total Return (%) |
|---|---|---|---|---|
| LIGHT.CMDUSD | 277.640 | 0.113 | -0.023 | 0.028 |
| COPPER.CMDUSD | 163.546 | 0.092 | -0.012 | 0.016 |
| SUGAR.CMDUSD | 119.860 | 0.069 | -0.016 | 0.012 |
| COTTON.CMDUSX | 103.810 | 0.069 | -0.010 | 0.010 |
| USDJPY | 92.209 | 0.129 | -0.009 | 0.009 |
- Instruments like LIGHT.CMDUSD and COPPER.CMDUSD demonstrated consistent performance across backtesting and forward testing.
- USDJPY showed sensitivity to market shifts, impacting forward test profitability.
- Correlation analysis highlighted potential diversification benefits when combining select assets.
✔️ Incorporate macroeconomic indicators and sentiment analysis for better predictions.
✔️ Implement adaptive parameter tuning for real-time strategy adjustments.
✔️ Expand to additional instruments and refine trading logic based on evolving market trends.