Project Instructions

Applying Machine Learning to Asset Pricing problems helps us to discover non-linear relationships between economic variables and financial market regimes.

There are 3 data objects in the data folder:

• X_train.csv: This file contains various features related to the EU, US, and JPN markets, as well as short-term interest rates and two key commodities (Gold and Oil). • y_train.csv: This file provides the binary “state” of the market for each date in the training set. • X_test.csv: This file mirrors the structure of X_train, containing the same features.

The project is aimed to generate a series of predictions for the market regimes in the test set, y_test. The results is evaluated based on accuracy, the proportion of correctly predicted instances out of the total number of predictions.