Statistical Learning & Predictive Modelling
Applying advanced statistical methods to extract signals from noisy financial datasets, focusing on robust estimators and out-of-sample performance.
Quant Finance · Machine Learning · Computing
Building rigorous foundations in software engineering, mathematics, statistics and machine learning applied to quantitative finance.
This website documents my academic and technical journey toward quantitative finance and research-oriented software development, combining practical engineering experience with a growing focus on advanced mathematics, data-intensive systems and financial machine learning.
Research Focus
Time Series & Stochastic Processes
Modeling asset dynamics using continuous-time stochastic calculus and discrete-time ARMA/GARCH frameworks for volatility estimation.
Quantitative Finance
Developing systematic trading strategies, portfolio optimization techniques, and risk management models grounded in empirical finance.
Optimization & Numerical Methods
Implementing convex optimization routines and numerical PDE solvers for derivatives pricing and portfolio allocation under constraints.
Machine Learning
Exploring deep learning architectures, reinforcement learning, and NLP applied to alternative data for alpha generation.
Computing
Building high-performance, data visualization, and computational tools using Python, C++, and specialized numerical libraries.