When calculating the results and preparing a list of undervalued and overvalued stocks in our StockPicking Lab, for every asset, stock, and ticker we use 2237 features.

We have deployed a new version of our SFA (Summary of Financial Articles) software.

Learning curves can bring important insight during the design process of a machine learning model.

We have been researching the selection of variables enterings. When there are too many variables, the model has a worse ability to generalize and is more prone to errors.

We have released a new version of the opinion app! The app underwent a complete redesign, we focused on a better UI and added a large number of products.

We have recently implemented the method Feature Binning and Quantile Transformation. Due to upgraded data preparation, our ML models now achieve better results.