Machine Learning Regression Analysis

This project is to forecast the United States Federal Funds Rate, one of the most anticipated and recognizable economic indicators in the financial world, by adopting machine learning techniques. Using various tools for forecasting the Federal Funds Rate of the United States, we further compare, analyse and discuss the results from different methods to draw conclusions on the strategies performed.

Project Topic

Forecasting US Fed Funds Rate with a dataset of US Fred Fund Rate from 1970 to 2020

Machine Learning Methods Used

1. Principal Component Analysis (PCA)
2. Linear Regression
3. Ridge Regression
4. Lasso Regression
5. Elastic Net Regression
6. Extreme Gradient Boosting (XGBoost)
7. Random Forest