adamd1985/pairs_trading_unsupervised_learning
The notebook with the experiments to replicate and enhance the stock clustering proposed by Han(2022) for alogtrading, with KMeans Optimization
This project helps quantitative traders and portfolio managers identify profitable pairs trading opportunities. It takes historical firm characteristics data (like company financial metrics and industry codes) and groups similar stocks together. The output is a refined clustering of stocks, which can then be used to form pairs for statistical arbitrage strategies.
No commits in the last 6 months.
Use this if you are a quantitative trader or portfolio manager looking to enhance your pairs trading strategies by identifying statistically similar stocks through unsupervised learning.
Not ideal if you need real-time trading signals or are looking for a fully automated trading system rather than a method for identifying potential pairs.
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Last pushed
Mar 07, 2024
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