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Quantitative Alpha Research is a GitHub project that aims to provide users with a framework for performing quantitative alpha research and building profitable equity investment models using diverse data sources. By collecting, cleaning, and processing data from financial statements, news articles, and economic indicators, users can extract meaningful features that can be used for stock return forecasting and model building. With the help of algorithms such as regression, decision trees, or neural networks, users can then build and implement investment models that are optimized for maximum returns. The project also includes features for evaluating model performance, constructing portfolios, and managing risks associated with the portfolios.
To access the Quantitative Alpha Research GitHub project, please send a message requesting access. The project is currently in private mode to ensure that only authorized users can access and contribute to the repository.