Enhancing Trading Strategy Robustness through Anomaly Detection
This project explores the use of anomaly detection techniques, such as One-Class SVM, to identify the conditions under which algorithmic trading strategies are likely to succeed, ensuring their applicability and extending the approach to portfolio-wide strategy optimization.