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Modelling credit spreads on commercial mortgage loans

Sotiris Tsolacos (Bayes Business School, London, UK)
Nicole Lux (Bayes Business School, London, UK)

Journal of European Real Estate Research

ISSN: 1753-9269

Article publication date: 10 May 2022

Issue publication date: 17 October 2022

129

Abstract

Purpose

This paper offers empirical evidence on factors influencing credit spreads on commercial mortgage loans. It extends existing work on the pricing of commercial mortgage loans. The authors examine the relative significance of a range of factors on loan pricing that are lender, asset and loan specific. The research explores and quantifies the sources of spread differentials among commercial mortgage loans. The paper contributes to a limited literature on the subject and serves the purpose of price discovery in commercial property lending. It offers a framework to compare actual pricing with fundamental-based estimates of loan spreads.

Design/methodology/approach

Panel analysis is deployed to examine the cross-section and time-series determinants of commercial mortgage loan margins and credit spreads. Using an exclusive database of loan portfolios in the United Kingdom (UK), the panel analysis enables the authors to analyse and quantify the impact of a number of theory-consistent and plausible factors determining the cost of lending to commercial real estate (CRE), including type and origin of lender, loan size, loan to value (LTV) and characteristics of asset financed – type, location and grade.

Findings

Spreads on commercial mortgages and, therefore, loan pricing differ by the type of lender – bank, insurance company and debt fund. The property sector is another significant risk factor lenders price in. The LTV ratio has increased in importance since 2012. Prior to global financial crisis (GFC), lenders made little distinction in pricing different LTVs. Loans secured in secondary assets command a higher premium of 50–60bps. The analysis establishes an average premium of 35bps for loans advanced in regions compared to London. London is particularly seen a less risky region for loan advancements in the post-GFC era.

Research limitations/implications

The study considers the role of lender characteristics and the changing regulation in the pricing of commercial mortgage loans and provides a framework to study spreads or pricing in this market that can include additional fundamental influences, such as terms of individual loans. The ultimate aim of such research is to assess whether mortgage loans are correctly priced and spotting risks emanating from actual loan spreads being lower than fundamental-based spreads pointing to tight pricing and over-lending.

Practical implications

The analysis provides evidence on lender criteria that determine the cost of loans. The study confirms that differences in regulation affect loan pricing. The regulatory impact is most visible in the increased significance of LTV. In that sense, regulation has been effective in restricting lending at high LTV levels.

Originality/value

The paper exploits a database of a commercial mortgage loan portfolio to make loan pricing more transparent to the different types of lender and borrowers. Lenders can use the estimates to assess whether commercial loans are fairly priced. Borrowers better understand the relative significance of risk factors affecting margins and the price they are charged. The results of this paper are of value to regulators as they can assist to understand the determinants of loan margins and gauge conditions in the lending market.

Keywords

Acknowledgements

The authors are deeply grateful to the reviewers for the time they spent on our paper and their ongoing remarks that significantly improved the paper to its current form.

Citation

Tsolacos, S. and Lux, N. (2022), "Modelling credit spreads on commercial mortgage loans", Journal of European Real Estate Research, Vol. 15 No. 3, pp. 332-350. https://doi.org/10.1108/JERER-04-2021-0022

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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