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Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks

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  • Episcopos, Athanasios
  • Pericli, Andreas
  • Hu, Jianxun

Abstract

This article explores the use of artificial neural networks in the modeling of foreclosure of commercial mortgages. The study employs a large set of individual loan histories previously used in the literature of proportional hazard models on loan default. Radial basis function networks are trained (estimated) using the same input variables as those used in the logistic. The objective is to demonstrate the use of networks in forecasting mortgage default and to compare their performance with that of the logistic benchmark in terms of prediction accuracy. Neural networks are shown to be superior to the logistic in terms of discriminating between "good" and "bad" loans. The study performs sensitivity analysis on the average loan and offers suggestions on further improving prediction of defaulting loans. Copyright 1998 by Kluwer Academic Publishers

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  • Episcopos, Athanasios & Pericli, Andreas & Hu, Jianxun, 1998. "Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks," The Journal of Real Estate Finance and Economics, Springer, vol. 17(2), pages 163-178, September.
    • Handle: RePEc:kap:jrefec:v:17:y:1998:i:2:p:163-78
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    Cited by:

    1. Justin Sirignano & Apaar Sadhwani & Kay Giesecke, 2016. "Deep Learning for Mortgage Risk," Papers 1607.02470, arXiv.org, revised Mar 2018.
    2. Xudong An & Yongheng Deng & Eric Rosenblatt & Vincent Yao, 2012. "Model Stability and the Subprime Mortgage Crisis," The Journal of Real Estate Finance and Economics, Springer, vol. 45(3), pages 545-568, October.
    3. Salman Bahoo & Marco Cucculelli & Xhoana Goga & Jasmine Mondolo, 2024. "Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis," SN Business & Economics, Springer, vol. 4(2), pages 1-46, February.
    4. An, Xudong & Deng, Yongheng & Gabriel, Stuart A., 2011. "Asymmetric information, adverse selection, and the pricing of CMBS," Journal of Financial Economics, Elsevier, vol. 100(2), pages 304-325, May.
    5. Brian Ciochetti & James Shilling, 2007. "Loss Recoveries, Realized Excess Returns, and Credit Rationing in the Commercial Mortgage Market," The Journal of Real Estate Finance and Economics, Springer, vol. 34(4), pages 425-445, May.
    6. Monica Billio & Michele Costola & Loriana Pelizzon & Max Riedel, 2022. "Buildings’ Energy Efficiency and the Probability of Mortgage Default: The Dutch Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(3), pages 419-450, October.
    7. Hoon Cho & Brian Ciochetti & James Shilling, 2013. "Are Commercial Mortgage Defaults Affected by Tax Considerations?," The Journal of Real Estate Finance and Economics, Springer, vol. 46(1), pages 1-23, January.

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