LGD and RR modeling - Comparison of models

Article type: Research Article

Authors: Tuysuz, Sukriye^a;

Affiliations: [a] Department of International Finance, Faculty of Commerce, Yeditepe University, Kayisdagi Cad., Istanbul, Turkey E-mail: [email protected]

Correspondence: [*] E-mail: [email protected]

Abstract: Since Basel 2, a financial institution can determine the capital required for credit risk by using internal models, which require the determination of Loss Given Default (LGD). LGD is also an important element in assets pricing. The dynamics of LGD can be evaluated directly or can be extracted from the dynamics of the recovery rate (RR). Observed LGDs/RRs present an asymmetric and bimodal distribution. In this article several models formalizing these features are employed: simple models and models modeling the unusual nature of LGDs/RRs (skewed regressions, adjusted regressions, inflated regressions). In sum, 25 models were retained for evaluating the dynamics of LGDs and RRs and 13 covariates. Performances of models were compared by using several classical and advanced metrics determined by using 10-fold cross-validation. According to obtained results, the best way to forecast LGDs is either to model and forecast it directly with the beta regression and with the zero-adjusted beta regression or drawn it from the fitted and forecasted RRs with its performing models. These latter models are the beta regression and the one-adjusted beta regression. As expected, most of the retained explanatory variables influence the dynamics of LGDs/RRs.

Keywords: LGD, RR, skewed distributions, validation, discrimination, 10-fold cross-validation

DOI: 10.3233/RDA-202063

Journal: Risk and Decision Analysis, vol. 8, no. 3-4, pp. 77-101, 2021