fitzgerald-kyle/insider-training
A machine learning project that uses insider trade data to develop a successful share-trading strategy.
This project helps individual investors and financial analysts develop potential stock-trading strategies. It takes publicly available insider trading data and historical stock prices to generate a strategy that aims to outperform market benchmarks. The output is a simulated trading strategy and its performance metrics, designed for those interested in data-driven investment approaches.
No commits in the last 6 months.
Use this if you are an individual investor or financial analyst looking to explore how public insider trading data can be leveraged to create a stock trading strategy.
Not ideal if you are seeking direct financial advice or a guaranteed successful trading algorithm, as this is a research project demonstrating a potential approach.
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Last pushed
Dec 17, 2022
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