Systematic credit risk in securitised mortgage portfolios

Lee, Yongwoong; Rösch, Daniel; Scheule, Harald

doi:10.1016/j.jbankfin.2020.105996

Cited by 5 publications

(3 citation statements)

References 35 publications

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“…In addition, the p-person correlation between regulatory systematic risk sensitivity and borrowers' default probability is positive (1.14%) and negative (−67.79%) in the economic approach. Hence, really and economically, the default contagion effect is important in the lower notation class of borrowers, contrary to the result of the regulatory approach, as found by Lee et al (2021). However, the regulatory authorities have supposed that the contagion effect is higher in the higher class of default risk.…”

Section: Resultsmentioning

confidence: 89%

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Investigation and Modelling of Economic Systematic Risk and Capital Requirement: A Monte Carlo Simulation

Benhamed

Gassouma

2023

JRFM

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This paper tests the ability of the regulatory capital requirement to cover credit losses at default, as carried out by the economic (optimal) capital requirement in Tunisian banks. The common factor in borrowers that leads to a credit default is systematic risk. However, the sensitivity to these factors differs between borrowers. To this end, we derived two kinds of sensitivity to systematic risk: the first is recognised by the Basel Committee; the second is derived from an economic approach. Hence, we can observe the impact of sensitivity to systematic risk on capital requirements. Empirically, we studied a sample of 100 individual borrowers from a Tunisian deposit bank that had credit in January 2020. We estimated the default probability for each borrower and then simulated their systematic risk sensitivity using the Monte Carlo approach, and compared them with the regulatory risk sensitivity. Then, we tested their effects on the economic and regulatory capital requirements. The results indicate that regulatory capital overestimates economic capital. This is due to the overestimation of borrowers’ contagion in terms of default risk, as shown by the superiority of their regulatory sensitivity systematic risk compared to the simulated risk. This leads banks to devote more capital than is really necessary to reach the regulatory standard. Hence, there was an increase in capital costs and the possibility of an arbitrage opportunity.

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Section: Resultsmentioning

confidence: 89%

“…Many studies have pointed out the impact of systematic risk on default borrowers. Lee et al (2021) investigated the effect of systematic risk on the borrowers' class notation of a set of US-securitized loans. They showed that systematic risk is decomposed into general systemic risk and specific systematic risk.…”

Section: Introductionmentioning

confidence: 99%

Investigation and Modelling of Economic Systematic Risk and Capital Requirement: A Monte Carlo Simulation

Benhamed

Gassouma

2023

JRFM

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“…The data was collected from the monthly loan performance reports of residential mortgage-backed securities to investors and provided by International Financial Research. The data is comparable to Rajan et al (2015) and has been used in prior literature (e.g., Lee et al, 2021). We construct two data sets: an origination panel for the Stage 1 model and an observation panel for the Stage 2 model.…”

Section: Datamentioning

confidence: 99%

Impact of mortgage soft information in loan pricing on default prediction using machine learning

2022

Self Cite

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We analyze the impact of soft information on US mortgages for default prediction and provide a new measure for lender soft information that is based on the interest rates offered to borrowers and incremental to public hard information. Hard and soft information provide for a variation in annual default probabilities of approximately 3%. Soft information has a lesser impact over time and time since origination. Lenders rely more on soft information for high-risk borrowers. Our study evidences the importance of soft information collected at loan origination.

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Asymmetric asset correlation in credit portfolios

Cho

Lee²

2022

Finance Research Letters

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Systematic credit risk in securitised mortgage portfolios

Cited by 5 publications

References 35 publications

Investigation and Modelling of Economic Systematic Risk and Capital Requirement: A Monte Carlo Simulation

Investigation and Modelling of Economic Systematic Risk and Capital Requirement: A Monte Carlo Simulation

Impact of mortgage soft information in loan pricing on default prediction using machine learning

Asymmetric asset correlation in credit portfolios

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