Benchmarking forecast approaches for mortgage credit risk for forward periods

Luong, TM; Scheule, H

Benchmarking forecast approaches for mortgage credit risk for forward periods

Luong, TM Scheule, H

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Publisher:: Elsevier BV
Publication Type:: Journal Article
Citation:: European Journal of Operational Research, 2022, 299, (2), pp. 750-767
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Luong, TM
dc.contributor.author	Scheule, H https://orcid.org/0000-0001-7283-5654
dc.date.accessioned	2022-01-24T02:47:07Z
dc.date.available	2022-01-24T02:47:07Z
dc.date.issued	2022
dc.identifier.citation	European Journal of Operational Research, 2022, 299, (2), pp. 750-767
dc.identifier.issn	0377-2217
dc.identifier.uri	http://hdl.handle.net/10453/153493
dc.description.abstract	This paper explores alternative forecast approaches for mortgage credit risk for forward periods of up to seven years. Using data from US prime mortgage loans from 2000 to 2016, we find that common borrower, loan contract and external features are significant in explaining credit risk over forward periods. Time variation may come through the ageing and forward channel. We develop a hybrid model for predicting default probabilities that combines both channels and outperforms standalone alternatives. This higher precision results in more accurate economic capital, IFRS 9/CECL loan loss provisioning and mortgage pricing, and hence, a more efficient and resilient resource allocation in commercial banks.
dc.language	en
dc.publisher	Elsevier BV
dc.relation.ispartof	European Journal of Operational Research
dc.relation.isbasedon	10.1016/j.ejor.2021.09.026
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Operations Research
dc.title	Benchmarking forecast approaches for mortgage credit risk for forward periods
dc.type	Journal Article
utslib.citation.volume	299
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2022-01-24T02:47:05Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	299
utslib.citation.issue	2

Abstract:

This paper explores alternative forecast approaches for mortgage credit risk for forward periods of up to seven years. Using data from US prime mortgage loans from 2000 to 2016, we find that common borrower, loan contract and external features are significant in explaining credit risk over forward periods. Time variation may come through the ageing and forward channel. We develop a hybrid model for predicting default probabilities that combines both channels and outperforms standalone alternatives. This higher precision results in more accurate economic capital, IFRS 9/CECL loan loss provisioning and mortgage pricing, and hence, a more efficient and resilient resource allocation in commercial banks.

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http://hdl.handle.net/10453/153493