Bank loan recovery rates: Measuring and nonparametric density estimation

Calabrese, Raffaella; Zenga, M

doi:10.1016/j.jbankfin.2009.10.001

Cited by 79 publications

(60 citation statements)

References 19 publications

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“…On the one hand, the Bernoulli random variable allows to reproduce the high concentration of data at total recovery and total loss (Calabrese and Zenga, 2010;Renault and Scaillet, 2004;Schuermann, 2003). On the other hand, the beta distribution is well suited 1 to the modelling of LGDs (Bruche and González-Aguado, 2008;Gupton et al, 1997;Gupton and Stein, 2002).…”

Section: Used Inmentioning

confidence: 99%

Downturn Loss Given Default: Mixture distribution estimation

Calabrese

2014

European Journal of Operational Research

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The internal estimates of Loss Given Default (LGD) must reflect economic downturn conditions, thus estimating the "downturn LGD", as the new Basel Capital Accord Basel II establishes. We suggest a methodology to estimate the downturn LGD distribution to overcome the arbitrariness of the methods suggested by Basel II. We assume that LGD is a mixture of an expansion and recession distribution. In this work, we propose an accurate parametric model for LGD and we estimate its parameters by the EM algorithm. Finally, we apply the proposed model to empirical data on Italian bank loans.

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Section: Used Inmentioning

confidence: 99%

Downturn Loss Given Default: Mixture distribution estimation

Calabrese

2014

European Journal of Operational Research

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“…Parametric LGD models are regression based. Besides OLS and logit regression new models have been developed recently: inflated beta regression ( [6]), generalized beta regression ( [7]), censored gamma regression ( [8]), zeroadjusted gamma regression ( [9]), and mixture-models ( [10] and [11]). In [12] the authors point out some problems that arise in LGD estimation and show how they may be solved.…”

Section: When Modelingmentioning

confidence: 99%

From Power Curves to Discriminative Power: Measuring Model Performance of LGD Models

Frontczak¹,

Jaeger²,

Schumacher³

2017

JMF

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Measuring model performance of rating systems is a major task for banks.The concept of discrimination, i.e. the discriminative power, is used in credit risk modeling to assess the quality of a risk model concerning the separation of extreme events. For PD models CAP (Cumulative Accuracy Profile) or ROC (Receiver Operating Characteristic) curves are used to build a quantity called Accuracy Ratio, which is used to measure the discriminative power. These ideas are well known and broadly used in practice. Although such a measure is also desirable for models of the loss given default (LGD models), it is not documented in the literature. In this note we close this gap. We develop a measure for the discriminative power of LGD models based on Lorenz curves. We study first properties and introduce some alternatives for its calculation from a practical point of view.

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“…Although this approach is more complex, its greater accuracy and flexibility allow it to be applied to many kinds of debt (Calabrese and Zenga, 2010).…”

Section: Literature Reviewmentioning

confidence: 99%