Event-driven approach for stock return forecast
This project uses Machine Learning to analysis the impacts of various events to company's stock price and use it to predict future price changes.
34 different types of pre-classified events, from Departure of Directors to Failure to Make a Required Distribution, have been considered.
TP: 637 FP: 183 FN: 333 TN: 142
To run the model, run
Prepare dataset in
Prepare the corresponding model in