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Open-source investment analytics platform bridging academic research and retail finance. Features include portfolio risk decomposition [Fama-French Five Factor Model], retirement sustainability modeling [Block Bootstrap Monte Carlo], max drawdown/CVaR dashboards, and risk-return optimisation [Markowitz, Ledoit-Wolf] via an intuitive user interface.
A mean-variance analysis of a portfolio of risky assets, visualising the Markowitz bullet and the efficient frontier. We also compare the performance of a randomly selected portfolio within the Markowitz bullet, with that of an efficient portfolio of the same variance.
This project applies Markowitz’s Portfolio Theory to analyze the profitability and risk levels of a defense-focused portfolio during a period of high geopolitical tension. The model, implemented in Python, produces a visualization of the efficient frontier for the selected observation period.
This project is developed as part of the Computational Finance course. It covers not only classical and dynamic Markowitz portfolio optimization but also static and dynamic portfolio optimization based on Genetic Algorithms.