Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors

Lee, Yongwoong; Poon, Ser‐Huang

doi:10.1016/j.jedc.2014.02.008

Cited by 10 publications

(2 citation statements)

References 35 publications

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“…However, this remark is not subjected to further analysis. In other works this issue is virtually dodged, even if a dynamic modeling for the hazard rates is considered, as in Wilson (1997a,b) and Lee and Poon (2014).…”

Section: Unconditional Measurement and Non-stationaritymentioning

confidence: 99%

“…We consider as a proxy of hazard rate series the quarterly series of charge-off provided by the FDIC 7 for "Mort- These series are similar to those employed by Scheule (2004, 2010) and Lee and Poon (2014). As discussed therein, they present some shortcomings, like vulnerability to normative distortions 8 or the fact that they represent a money default ratio instead of a frequency one.…”

Section: Proposition Amentioning

confidence: 99%

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A New Approach to the Unconditional Measurement of Default Risk

2014

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This paper analyzes the unconditional measurement of default risk and proposes an alternative modeling approach. We begin the analysis by showing that when conducted under non-stationarity, the objective of the unconditional measurement changes and that some relevant problems appear as a consequence of the sample dependence. Based on this result, we introduce our approach and discuss its consistency, practical advantages, and the main differences from the conventional static framework. An empirical analysis is also conducted. Under nonstationarity, the regulatory model for the unconditional probability of default distribution performs badly when compared to our approach. Results also show that the capital figure presents a determinant and nontrivial dependence on the homogeneity and severity of the economic scenario represented in the sample. We begin the analysis by showing that when conducted under non-stationarity, the objective of the unconditional measurement changes and that some relevant problems appear as a consequence of the sample dependence. Based on this result, we introduce our approach and discuss its consistency, practical advantages, and the main differences from the conventional static framework. An empirical analysis is also conducted. Under non-stationarity, the regulatory model for the unconditional probability of default distribution performs badly when compared to our approach. Results also show that the capital figure presents a determinant and non-trivial dependence on the homogeneity and severity of the economic scenario represented in the sample.

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Section: Unconditional Measurement and Non-stationaritymentioning

confidence: 99%

Section: Proposition Amentioning

confidence: 99%