A Framework for Integrating Extreme Weather Risk, Probability of Default, and Loss Given Default for Residential Mortgage Loans

Michael C. S. Wong; Ho Ming Ho

doi:10.3390/su151511808

A Framework for Integrating Extreme Weather Risk, Probability of Default, and Loss Given Default for Residential Mortgage Loans

Michael C. S. Wong^*
, Ho Ming Ho

^*Corresponding author for this work

College of Business

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

9 Citations (Scopus)

167 Downloads (CityUHK Scholars)

Abstract

This paper considers a hypothetical case in which a bank wants to build a routine climate stress test exercise on residential mortgage loans. The bank has regularly updated the probability of default (PD) and loss given default (LGD) on each residential mortgage loan under the internal-rating-based (IRB) approach of Basel II/III. Additionally, the bank estimates the stressed PD and stressed LGD associated with a predetermined extreme weather event. Using simulation techniques, this paper shows that the loss of the bank’s residential mortgage portfolio can reach a median of around 36% of the portfolio value. This remarkable loss comes from the effects of default correlation and property damage. Banks should pay more attention to such impacts of extreme weather events. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.

Original language	English
Article number	11808
Number of pages	16
Journal	Sustainability
Volume	15
Issue number	15
Online published	1 Aug 2023
DOIs	https://doi.org/10.3390/su151511808
Publication status	Published - Aug 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 10 Reduced Inequalities
SDG 13 Climate Action

Research Keywords

physical climate risk
residential mortgage loans
probability of default
loss given default
climate stress tests

Publisher's Copyright Statement

This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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title = "A Framework for Integrating Extreme Weather Risk, Probability of Default, and Loss Given Default for Residential Mortgage Loans",

abstract = "This paper considers a hypothetical case in which a bank wants to build a routine climate stress test exercise on residential mortgage loans. The bank has regularly updated the probability of default (PD) and loss given default (LGD) on each residential mortgage loan under the internal-rating-based (IRB) approach of Basel II/III. Additionally, the bank estimates the stressed PD and stressed LGD associated with a predetermined extreme weather event. Using simulation techniques, this paper shows that the loss of the bank{\textquoteright}s residential mortgage portfolio can reach a median of around 36\% of the portfolio value. This remarkable loss comes from the effects of default correlation and property damage. Banks should pay more attention to such impacts of extreme weather events. {\textcopyright} 2023 by the authors. Licensee MDPI, Basel, Switzerland.",

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T1 - A Framework for Integrating Extreme Weather Risk, Probability of Default, and Loss Given Default for Residential Mortgage Loans

AU - Wong, Michael C. S.

AU - Ho, Ho Ming

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N2 - This paper considers a hypothetical case in which a bank wants to build a routine climate stress test exercise on residential mortgage loans. The bank has regularly updated the probability of default (PD) and loss given default (LGD) on each residential mortgage loan under the internal-rating-based (IRB) approach of Basel II/III. Additionally, the bank estimates the stressed PD and stressed LGD associated with a predetermined extreme weather event. Using simulation techniques, this paper shows that the loss of the bank’s residential mortgage portfolio can reach a median of around 36% of the portfolio value. This remarkable loss comes from the effects of default correlation and property damage. Banks should pay more attention to such impacts of extreme weather events. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.

AB - This paper considers a hypothetical case in which a bank wants to build a routine climate stress test exercise on residential mortgage loans. The bank has regularly updated the probability of default (PD) and loss given default (LGD) on each residential mortgage loan under the internal-rating-based (IRB) approach of Basel II/III. Additionally, the bank estimates the stressed PD and stressed LGD associated with a predetermined extreme weather event. Using simulation techniques, this paper shows that the loss of the bank’s residential mortgage portfolio can reach a median of around 36% of the portfolio value. This remarkable loss comes from the effects of default correlation and property damage. Banks should pay more attention to such impacts of extreme weather events. © 2023 by the authors. Licensee MDPI, Basel, Switzerland.

KW - physical climate risk

KW - residential mortgage loans

KW - probability of default

KW - loss given default

KW - climate stress tests

UR - https://www.scopus.com/pages/publications/85167885321

UR - https://www.scopus.com/pages/publications/85167885321#tab=impact

U2 - 10.3390/su151511808

DO - 10.3390/su151511808

M3 - RGC 21 - Publication in refereed journal

SN - 2071-1050

VL - 15

JO - Sustainability

JF - Sustainability

IS - 15

M1 - 11808

ER -

A Framework for Integrating Extreme Weather Risk, Probability of Default, and Loss Given Default for Residential Mortgage Loans

Abstract

UN SDGs

Research Keywords

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Correction: Wong, M.C.S.; Ho, H.M. A Framework for Integrating Extreme Weather Risk, Probability of Default, and Loss Given Default for Residential Mortgage Loans. Sustainability, 2023, 15, 11808

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