I work at the intersection of quantitative finance, machine learning, financial time series, and software engineering.
- ML for financial time series
- Volatility forecasting
- Statistical model comparison
- Backend & production ML systems
- Projects
Open-source quantitative finance platform focused on automated volatility forecasting and model benchmarking. https://dquant.space
My research focuses on comparing econometric and machine-learning approaches to financial forecasting.
- GARCH-family models
- Machine learning
- Volatility forecasting
- Monte Carlo methods
- Time-series analysis
- Statistical testing
- Walk-forward / out-of-sample evaluation
I aim to combine research, engineering, and reproducible benchmarking to build practical quantitative tools.
