Quantitative Finance & Algorithmic Trading in Python

This comprehensive program, designed by Holczer Balazs, offers a deep dive into the mathematical and practical frameworks of quantitative finance and algorithmic trading using Python. Aspiring quantitative analysts, data scientists, and finance professionals will find this curriculum highly valuable as it bridges the gap between theoretical financial engineering and hands-on programming. The course meticulously covers critical topics starting with stock market fundamentals, bond pricing dynamics, and the foundational Modern Portfolio Theory (Markowitz model). Learners will explore advanced concepts like the Capital Asset Pricing Model (CAPM), credit derivatives including Credit Default Swaps (CDS), and Collateralized Debt Obligations (CDOs). Additionally, it unpacks stochastic calculus via the Black-Scholes model, interest rate models like the Vasicek model, and risk management techniques such as Value-at-Risk (VaR) and Monte-Carlo simulations. By translating complex mathematical formulas into clean Python code, this training empowers students to build robust trading algorithms, simulate asset prices, and systematically manage portfolio risk, making it an excellent resource for anyone looking to build a career in quantitative analysis or algorithmic trading.