efficient-frontier

Financial portfolio optimization in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Portfolio Optimization in Python

A program for financial portfolio management, analysis and optimisation.

Entropy Pooling views and stress testing combined with Conditional Value-at-Risk (CVaR) portfolio optimization in Python.

Portfolio Construction and Risk Management book's Python code.

Finance Visualisations including Efficient Frontier, VaR & CVaR, and CAPM beta

A collection of various computational methods to optimize a user's investment portfolio using Modern Portfolio Theory and optimizing various factors such as Returns, Sharpe Ratio and Risk.

📈Financial Markowitz Portfolio Optimization (Bonds, Stocks, Commodities), including classical Efficient Frontier, Utility Function etc.

Fama-French models, idiosyncratic volatility, event study

Portfolio optimisation library for Julia. Over 50 risk measures (CVaR, EVaR, RLVaR, drawdown, OWA), hierarchical risk parity, HERC, nested clustered optimisation, risk budgeting, near-optimal centering, four Black-Litterman variants, entropy pooling, factor and high-order priors, denoising, and JuMP-backed convex and non-convex optimization.

critical line algorithm for efficient frontier

Heuristics for cardinality constrained portfolio optimisation

Modern Portfolio Theorem for portfolio optimization and asset allocation

Portfolio analysis and mean-variance optimisation in Python.

Financial Portfolio Optimization with amplpy

McPortfolio: A Model Context Protocol server providing 9 specialized tools for LLM-driven portfolio optimization using natural language, covering mean-variance to machine learning approaches.

A Portfolio Efficient Frontier Calculator which includes graphical visualization of Correlation, Security Market Line and Rolling Beta for U.S. Equities

Reinforcement learning model for portfolio management that takes investor preferences into account

Parametric quantum circuits for portfolio risk on IBM Quantum hardware. Class material for CACIC 2026 (in Spanish): slides and a Qiskit notebook with real market data.

Factor exposure-based stock selection and tangency portfolio construction on the STOXX 600 universe