Quantitative Research Analyst
CurrentDeveloped mean reversion trading strategy for stocks by ARIMA and ML algorithm to identify profitable opportunities through robustness and sensitivity analysis, leveraging statistical arbitrage to increase portfolio returns by 9%Built a Fama-French model based on factor model to forecast the performance of target stocks, adjusting portfolio returns with value factors, size factors and market risk premiumConducted 10 years of backtesting and 5 years of forward testing using historical and real-time data, ensuring statistical robustness. Achieved an 8% annualized return with a Sharpe ratio of 1.5 through a long-short equity strategyConstructed machine learning models for market prediction and regime detection, including Bayesian models by using historical data to predict return distribution, enhancing portfolio performance with sentiment analysis, turnover ratesCollaborated to optimize execution algorithms, reducing trading costs by 20% and improving market impact management