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

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

Python library for portfolio optimization built on top of scikit-learn

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

Python financial widgets with okama and Dash (plotly)

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

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.

Fama-French models, idiosyncratic volatility, event study

critical line algorithm for efficient frontier

Modern Portfolio Theorem for portfolio optimization and asset allocation

Heuristics for cardinality constrained portfolio optimisation

Portfolio Optimisation library built in Julia.

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

Shiny Project for Illustrating Asset Management Principles

Portfolio optimization using Riskfolio-Lib

Portfolio optimization using efficient frontier curve

Simple trading bot algorithms based on Sharpe ratio and Moving Average

📉Some projects in ML and DL📈

No description provided.

Jupyter notebooks implementing Finance projects

An application of the paper "Rockafellar, R. and S. Uryasev. “Optimization of conditional value-at risk.” Journal of Risk 3 (2000): 21-41."

Investment Strategy to find the minimum risk portfolio combination/arrangement.

A complete detailed study of Machine Learning, Data Wrangling, Data Visualization and other techniques on Portfolio Management of Stocks.

Efficient Frontier Implementation in Python