As a self-employed Quantitative Researcher, I translate mathematical frameworks into production-ready trading models using stochastic differential equations, Ito calculus, and time-series econometrics. I also apply competitive programming methods to optimize algorithmic trading infrastructure.
I designed multivariate forecasting pipelines that combine ARIMA/GARCH models with neural networks. In my equity-return forecasting project, I compared LSTM and Temporal Fusion Transformers and achieved a 13.4% annualized return on out-of-sample data.
My projects also include derivative pricing and statistical arbitrage. I implemented pricing methods for American and Asian options, and developed a cointegration-based pairs trading engine that achieved an out-of-sample annualized Sharpe ratio of 1.2.
