Estimating Short-term Default Probabilities Conditional to Economic Conditions: Applications of Regularisation Approach and Economic Adjustment Coefficients

Mustafa Siti Aisyah (), Nor Safwan Mohd (), Halim Zairihan Abdul () and Zawawi Nur Haiza Muhammad ()
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Mustafa Siti Aisyah: Faculty of Business, Economics and Social Development, University of Malaysia Terengganu, Malaysia, Faculty of Technology Management and Business, University Tun Hussein Onn Malaysia
Nor Safwan Mohd: Faculty of Business, Economics and Social Development, University of Malaysia Terengganu, Malaysia, Victoria Institute of Strategic Economic Studies, Victoria University, Australia
Halim Zairihan Abdul: Faculty of Business, Economics and Social Development, University of Malaysia Terengganu, Malaysia
Zawawi Nur Haiza Muhammad: Faculty of Business, Economics and Social Development, University of Malaysia Terengganu, Malaysia

Business Systems Research, 2025, vol. 16, issue 1, 178-197

Abstract: Background Corporate bonds are crucial for corporations as they provide a flexible and often less costly alternative to equity financing. However, rising corporate debt levels, along with rating downgrades and economic uncertainty, can cause corporations to face financial distress, exacerbating the probability of default. Objectives The purpose of this paper is to estimate bond default probabilities conditional on fluctuations in economic growth over short-term frequencies using inputs from rating transitions. Methods/Approach The estimation is based on a Markov chain framework and the incorporation of economic growth by utilizing specifications of the economic adjustment coefficient. Further, quasi-optimisation of the roots matrix is utilized to extend the model within a quarterly domain. Results Economic growth (proxied by GDP) carries little informational content on the future default probabilities. Non-investment grade ratings depict higher default probability, while investment-grade ratings yield default propensity of less than 1.1% in the next quarters and exhibit higher distance between default probabilities by tenor points and neighbouring states as the time horizon lengthens. Conclusions First, practitioners can measure forward-looking bond exposure across different tenure buckets using the estimation approach developed in this study. Second, by considering historical fluctuations in the economic cycle as an additional factor for estimating future default probability, this study informs financial market regulators by providing entities with an alternative reference point to their in-house generated models, helping them meet regulatory requirements.

Keywords: credit ratings; default probability; Markov framework; regularisation approach; economic adjustment coefficients (search for similar items in EconPapers)
JEL-codes: G17 G2 G24 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bit:bsrysr:v:16:y:2025:i:1:p:178-197:n:1009

DOI: 10.2478/bsrj-2025-0009

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