Prediction of Loan Rate for Mortgage Data: Deep Learning Versus Robust Regression

Donglin Wang (), Don Hong () and Qiang Wu ()
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Donglin Wang: Middle Tennessee State University
Don Hong: Middle Tennessee State University
Qiang Wu: Middle Tennessee State University

Computational Economics, 2023, vol. 61, issue 3, No 11, 1137-1150

Abstract: Abstract Mortgage data is often skewed, has missing information, and is contaminated by outliers. When mortgage companies or banks make prediction of note rates for new applicants, robust regression models are usually selected to deal with outliers. In this paper, we utilize deep neural network to predict the loan rate and compare its performance with three classical robust regression models. Two real mortgage data sets are used in this comparison. The results show that deep neural network has the best performance and therefore is recommended.

Keywords: Mortgage rate prediction; Deep neural network; Huber regression; Random sample consensus; Theil–Sen regression (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10614-022-10239-5

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