With a strong foundation in quant modelling and a model-driven approach, my expertise spans across both the sell-side and buy-side, including work with FTSE Russell on portfolio construction and rebalancing.
I focus on AI-enabled Quant Research, leveraging the modern data-rich world to enhance back-testing, predictive forecasting, and the dynamic calibration of algorithmic trading strategies. This approach is instrumental in short-term risk factor analysis and scenario generation.
Throughout my career, I have worked on numerous market models, including SABR volatility, Heston models, and XVA simulations. In 2019, I published a book featuring Python prototypes for these models. While traditional CPU-driven approaches were the standard then, my current work focuses on scalable, AI-driven methodologies that move beyond these classical limitations.
The core of my philosophy remains a rigorous, model-driven approach to global markets, enhanced by the latest advancements in artificial intelligence.