Quantitative Trading Strategy
Machine Learning & Financial Analysis
Developed a long-short equity strategy using Random Forest and Ridge Regression models to predict stock returns. Engineered features using Fama-French 5-factor risk decomposition and technical indicators (RSI, MACD), validating performance with Purged K-Fold cross-validation.
Key Achievements:
- •Implemented Fama-French 5-factor model for risk decomposition
- •Optimized Random Forest with Purged K-Fold cross-validation
- •Engineered rolling betas and momentum indicators
- •Achieved robust out-of-sample backtesting performance