Loss Given Default Modeling: a Comparative Analysis

Name: Loss Given Default Modeling: a Comparative Analysis
Brand: LAP Lambert Academic Publishing
SKU: 9786202093750
Price: 572 CZK
Availability: InStock

Autor: Olga Yashkir, Yuri Yashkir

Jazyk:

Vazba: Brožovaná

Vydavatel: LAP Lambert Academic Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

572 Kč

Several most popular Loss Given Default (LGD) models were investigated (LSM, Tobit, Three-Tiered Tob...

Informace o knize

Autor

Olga Yashkir, Yuri Yashkir

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2017

Stránek

EAN

9786202093750

Enbook ID

18715689

Vydavatel

LAP Lambert Academic Publishing

Hmotnost

Rozměry

150 x 220 x 3

Kompletní popis

Several most popular Loss Given Default (LGD) models were investigated (LSM, Tobit, Three-Tiered Tobit, Beta Regression, Inflated Beta Regression, Censored Gamma Regression) in order to compare their performance. We show that for a given input data set, the quality of the model calibration depends mainly on the proper choice of explanatory variables, but not on the fitting model. Model factors were chosen based on their correlation with historical LGDs of the calibration data set. Numerical values of non-quantitative parameters (industry, ranking, type of collateral) were introduced as their LGD average. We show that different debt instruments depend on different sets of model factors (from three factors for Revolving Credit or for Subordinated Bonds to eight factors for Senior Secured Bonds). Calibration of LGD models using distressed business cycle periods provide better fit than data from total available time span. Calibration algorithms and details of their realization using the R statistical package are presented. We demonstrate how LGD models can be used for stress testing. The results of this study can be of use to risk managers concerned with the Basel accord compliance.

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Loss Given Default Modeling: a Comparative Analysis

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