georgemuriithi/investment-portfolio-optim
An investment portfolio of stocks is created using Long Short-Term Memory (LSTM) stock price prediction and optimized weights. The performance of this portfolio is better compared to an equally weighted portfolio and a market capitalization-weighted portfolio.
This project helps investment analysts and quantitative traders explore how a portfolio of stocks might be optimized using predicted stock prices. It takes historical stock price data for major U.S. companies and outputs optimized portfolio weights designed to maximize returns. The end user is typically a quantitative analyst or someone interested in simulating advanced portfolio strategies.
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Use this if you are a quantitative analyst or finance researcher interested in simulating and evaluating advanced stock portfolio optimization strategies based on predictive models.
Not ideal if you are a retail investor looking for direct investment advice or a tool to predict real-life stock market movements, as this project is for research and demonstration purposes only.
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Jupyter Notebook
License
GPL-3.0
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Last pushed
Jan 18, 2024
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