Portfolio optimization with deep learning.
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Updated
Jan 24, 2024 - Python
Portfolio optimization with deep learning.
Markowitz portfolio optimization on synthetic and real stocks
Python financial widgets with okama and Dash (plotly)
Backtesting of different trading strategies by applying different Modern Portfolio Theory (MPT) approaches on long-only ETFs portfolios in Python.
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."
Portfolio Optimization on a Quantum computer.
critical line algorithm for efficient frontier
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.
Markowitz Modern Portfolio Theory implementation in Python — efficient frontier, risk-return optimization, and portfolio construction
Interactive Streamlit dashboard for market risk analysis, Markowitz portfolio optimization, and financial planning. See in the link below:
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Intelligent portfolio management using ARIMA trade timing + NLP sentiment analysis — >60% directional accuracy, Markowitz optimisation, full backtesting engine
Aplicação interativa para otimização de portfólio usando o modelo de Markowitz. Visualize a fronteira eficiente, realize backtests e gere relatórios detalhados de desempenho.
An open-source Python module for portfolio optimization and backtesting
Quantitative portfolio risk analyzer — VaR, Sharpe, Markowitz optimization, Monte Carlo simulation — Streamlit dashboard
Pipeline de Data Intelligence para análise fundamentalista (B3) e otimização de portfólios via Markowitz, com arquitetura de dados em camadas (Bronze, Silver, Gold).
Empirical comparison of Markowitz, Black-Litterman, and rule-based portfolio construction. Spoiler: the boring one wins.
Markowitz portfolio optimization using Python
Portfolio Theory for Climate-Resilient Farming in Myanmar | Markowitz optimization + Monte Carlo simulation for crop diversification | FastAPI + React + D3.js | AI for Agriculture Hackathon 2026
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