Portfolio optimization with deep learning.
Investment portfolio and stocks analyzing tools for Python with free historical data
A JavaScript library to allocate and optimize financial portfolios.
Markowitz portfolio optimization on synthetic and real stocks
Python financial widgets with okama and Dash (plotly)
Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies. The two primary classes are "portfolio" and "stonks."
Backtesting of different trading strategies by applying different Modern Portfolio Theory (MPT) approaches on long-only ETFs portfolios in Python.
critical line algorithm for efficient frontier
Portfolio Optimization on a Quantum computer.
Interactive Streamlit dashboard for market risk analysis, Markowitz portfolio optimization, and financial planning. See in the link below:
This Python script performs portfolio optimization based on different optimization criteria: 'sharpe', 'cvar', 'sortino', and 'variance'. The script uses historical stock price data downloaded from Yahoo Finance.
Inversion of a real matrix and the solution of a set of linear equations using Crout's method
Portfolio optimization using Markowitz Theory | Python + SciPy | Efficient Frontier | Max Sharpe: 1.313 | Long-only constraints | Quant Finance
Constructing mean-variance efficient frontiers from MPT.
Visualisation et optimisation de portefeuilles financiers en Python via la théorie de Markowitz. Simulation de 10 000 portefeuilles, calcul du Sharpe ratio, et tracé de la frontière efficiente.
An open-source Python module for portfolio optimization and backtesting
A Java implementation of the VBA code for the Critical Line Algorithm in the book "Mean-Variance Analysis in Portfolio Choice and Capital Markets" by Harry M. Markowitz
Python implementation of Modern Portfolio Theory (MPT) with Efficient Frontier construction, Max Sharpe Tangency Portfolio, Capital Market Line (CML), leverage simulation, and real-data backtesting vs SPY.
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