Predicting Default Risk under Asymmetric Binary Link Functions

33 Pages Posted: 11 Mar 2019

See all articles by Yiannis Dendramis

Yiannis Dendramis

University of Cyprus - Department of Accounting and Finance

Elias Tzavalis

Athens University of Economics and Business - Department of Economics

Petros Varthalitis

Economic and Social Research Institute, Dublin; Trinity College (Dublin)

Eleni Athanasiou

affiliation not provided to SSRN

Date Written: February 19, 2019

Abstract

In this paper we propose the use of an asymmetric binary link function to extend the proportional hazard model for predicting loan default. The rationale behind this approach is that the symmetry assumption, that has been widely used in the literature, could be considered as quite restrictive, especially during periods of financial distress. In our approach we allow for a flexible level of asymmetry in the probability of default by the use of the skewed logit distribution. This enable us to estimate the actual level of asymmetry that is associated with the data at hand. We implement our approach to both simulated data and a rich micro dataset of consumer loan accounts. Our results provide clear cut evidence that ignoring the actual level of asymmetry leads to seriously biased estimates of the slope coefficients, inaccurate marginal effects of the covariates of the model, and overestimation of the probability of default. Regarding the predictive power of the covariates of the model, we have found that loan specific covariates, contain considerably more information about the loan default than macroeconomic covariates, which are often used in practice to carry out macroprudential stress testing.

Keywords: Survival analysis, Credit Risk, Consumer Loans, Asymmetric distribution

JEL Classification: G12, E21, E27, E43

Suggested Citation

Dendramis, Yiannis and Tzavalis, Elias and Varthalitis, Petros and Athanasiou, Eleni, Predicting Default Risk under Asymmetric Binary Link Functions (February 19, 2019). Available at SSRN: https://ssrn.com/abstract=3337856 or http://dx.doi.org/10.2139/ssrn.3337856

Yiannis Dendramis

University of Cyprus - Department of Accounting and Finance ( email )

75 Kallipoleos Street
Nicosia CY 1678, Nicosia P.O. Box 2
Cyprus

Elias Tzavalis (Contact Author)

Athens University of Economics and Business - Department of Economics ( email )

76 Patission Street
GR-10434 Athens
Greece

Petros Varthalitis

Economic and Social Research Institute, Dublin ( email )

Whitaker Square
Sir John Rogerson's Quay
Dublin 2
Ireland

HOME PAGE: http://www.esri.ie/

Trinity College (Dublin) ( email )

Department of Economics
Dublin, DC
Ireland

Eleni Athanasiou

affiliation not provided to SSRN

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