Asymmetric asset correlation in credit portfolios

Cho, Yongbok; Lee, Yongwoong

doi:10.1016/j.frl.2022.103037

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…Using a Bayesian approach in which asset correlations are modeled using an inverse Wishart prior and equity correlations to obtain the posterior distribution, Dias (2020) found that probabilistic forecasts of defaults were produced with better out-of-sample performance than the standard ASRF model. Cho and Lee (2022) used a time-varying credit risk model to extract empirical asset correlations from loan loss data (the identical dataset to that used in our work). The model outperformed the regulatory model for US credit portfolios with strong empirical evidence of cyclical and asymmetric asset correlation.…”

Section: Theoretical Development and Literature Reviewmentioning

confidence: 99%

Measurement and Calibration of Regulatory Credit Risk Asset Correlations

van Dyk,

van Vuuren

2023

JRFM

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Vasicek’s asymptotic single risk factor (ASRF) model is employed by the Basel Committee on Banking Supervision (BCBS) in its internal ratings-based (IRB) approach for estimating credit losses and regulatory credit risk capital. This methodology requires estimates of asset correlations; these are prescribed by the BCBS. Practitioners are interested to know market-implied asset correlations since these influence economic capital and lending behavior. These may be backed out from ASRF loan loss distributions using ex post loan losses. Prescribed asset correlations have been neither updated nor recalibrated since their introduction in 2008 with the implementation of the Basel II accord. The market milieu has undergone significant alterations and adaptations since then; it is unlikely that these remain relevant. Loan loss data from a developed (US) and developing (South Africa) economy spanning at least two business cycles for each region were used to explore the relevance of the BCBS calibration. Results obtained from three alternative methodologies are compared with prescribed BCBS values, and the latter were found to be countercyclical to empirical loan loss experience, resulting in less punitive credit risk capital requirements than required in market crises and more punitive requirements than required in calm conditions.

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Section: Theoretical Development and Literature Reviewmentioning

confidence: 99%

Measurement and Calibration of Regulatory Credit Risk Asset Correlations

van Dyk,

van Vuuren

2023

JRFM

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Boosting credit risk models

Baesens

Smedts

2023

The British Accounting Review

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On Asymmetric Correlations and Their Applications in Financial Markets

Cao

Sun

et al. 2023

JRFM

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Progress on asymmetric correlations of asset returns has recently advanced considerably. Asymmetric correlations can cause problems in hedging effectiveness and overstate the value of diversification. Furthermore, considering the asymmetric correlations in portfolio construction significantly enhances performance. The purpose of this paper is to trace developments and identify areas that require further research. We examine three aspects of asymmetric correlations: first, the existence of asymmetric correlations between asset returns and their significance tests; second, the test on the existence of asymmetric correlations between different markets and financial assets; and third, the root cause analysis of asymmetric correlations. In the first part, the contents of extreme value theory, the H statistic and a model-free test are covered. In the second part, commonly used models such as copula and GARCH are included. In addition to the GARCH and copula formulations, many other methods are included, such as regime switching, the Markov switching model, and the multifractal asymmetric detrend cross-correlation analysis method. In addition, we compare the advantages and differences between the models. In the third part, the causes of asymmetry are discussed, for example, higher common fundamental risk, correlation of individual fundamental risk, and so on.

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Asymmetric asset correlation in credit portfolios

Cited by 3 publications

References 15 publications

Measurement and Calibration of Regulatory Credit Risk Asset Correlations

Measurement and Calibration of Regulatory Credit Risk Asset Correlations

Boosting credit risk models

On Asymmetric Correlations and Their Applications in Financial Markets

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