AI4Finance-Foundation/FinML
FinML: A Practical Machine Learning Framework for Dynamic Stock Selection
This project helps investors and investment companies dynamically select top-performing S&P 500 stocks. It takes in historical financial ratios and daily stock prices, then applies machine learning to identify the top 20% of stocks to buy and hold for the next quarter. The output is a recommended list of stocks with suggested portfolio allocations, designed for financial analysts, portfolio managers, and individual investors seeking to outperform the market.
173 stars. No commits in the last 6 months.
Use this if you need a systematic, data-driven approach to identify promising S&P 500 stocks for short-term investment, moving beyond manual analysis or static strategies.
Not ideal if you are looking for long-term buy-and-hold value investing, or if you primarily trade outside of the S&P 500 universe.
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173
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52
Language
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Last pushed
Feb 27, 2024
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