This repository contains a collection of my projects in areas related to quantitative trading, including:
- Statistics & Data Analysis – exploring patterns, correlations, and signals in financial data using Python and numerical libraries.
- Mathematical Modeling – applying mathematical tools to model market behavior, risk, and asset dynamics.
- Market Microstructure – simulating order books, liquidity, and price formation to understand trading mechanisms.
- Financial Models – implementing classical and modern pricing models such as Black–Scholes, options strategies, and volatility analysis.
- Algorithmic & Quantitative Strategies – experimenting with trend-following, momentum, and other data-driven trading approaches.
Each project includes code, visualizations, and explanations, aiming to provide both practical implementations and educational insights into how quantitative techniques are applied in real financial markets.
This repository is a personal sandbox for developing skills in Python programming, data science, and quantitative finance, and serves as a reference for future projects and experiments.