FOMC Decision Prediction Model

In Spring 2025, club members developed a machine learning model to predict Federal Reserve interest rate decisions. The team began by researching key macroeconomic indicators, such as inflation, unemployment, and market volatility, which have historically influenced Fed policy. After gathering and cleaning the data, members trained a random forest classifier to predict whether the Fed would cut, hold, or hike rates. The final model achieved 86% accuracy and correctly predicted the Fed’s decisions to hold rates steady in both June and July of 2025. The project combined economic research with technical implementation and helped members understand how data can inform real-world policy forecasting.