Prediction of MBA refinance Index (Mortgage prepayment)

Deep Neural Network based Model

The ability to predict mortgage prepayment is of critical use to financial institutions from an interest rate risk perspective. The goal of this project to predict the MBA refinance index.

The main components of this project are

• Data Cleaning
• Exploratory data analysis
• Model Creation
• Model Evaluation

Data

Data for MBA refinance originated across USA between 1990-2021 Weekly performance update as a target variable Mortgage Bankers Association Refi Index (Bloomberg Terminal)

Data for national economic factors from FRED (Federal Reserve Economic Data) Economically significant data

11,451 daily observations, each described by roughly 26 feature variables

Results

Best model was with 5- layered sequential NN model (with hyper parameter tuning) The MAPE value of 8.44%. Although DNN (Deep Neural Network) is being used mostly in image recognition and NLP, it could be used to predict the quantitative data. The hyperparameter tuning was able to increase the performance of our model.