A Model on Credit Analysis: Combining a First Passage Model and Survival Analysis for Corporate Default

52 Pages Posted: 11 Aug 2017 Last revised: 9 Jan 2019

See all articles by Seung Mo Cho

Seung Mo Cho

Yeungnam University - School of Economics & Finance

Date Written: June 30, 2013

Abstract

In this paper, we offer a new set of credit analysis models combining two traditional approaches of corporate default prediction: the survival analysis approach and the structural model approach. We first derive a modified version of the Black and Cox (1976) first passage model (a structural model) and estimate its model parameters based on the Miyake and Inoue (2009) method originally applied to parameter estimation for the Merton (1974) model (another structural model). And then based on the previous literature and various statistical techniques, we select some significant factors affecting corporate default and construct various survival analysis regression models with those factors including or excluding our first passage model as an independent variable. And by comparing our new combined models (the survival analysis regression models including the first passage model as an independent variable) with their corresponding plain models (the survival analysis regression models excluding the first passage model as an independent variable), we conclude that our new combined models are superior to their counterparts. And finally, by comparing those superior models, we propose a single best-fitting combined model for corporate default: an accelerated failure time model by Kalbfleisch and Prentice (1980) under the Weibull distribution with our modified Black and Cox (1976) model as an independent variable.

Keywords: Credit analysis, Corporate default, Survival analysis, Structural model, Black-Cox model, Merton model

JEL Classification: G24, G32, G33

Suggested Citation

Cho, Seung Mo, A Model on Credit Analysis: Combining a First Passage Model and Survival Analysis for Corporate Default (June 30, 2013). Financial Stability Studies, Vol. 14, No. 1, Korea Deposit Insurance Corporation(KDIC), 2013, pp. 109-159., Available at SSRN: https://ssrn.com/abstract=3016996 or http://dx.doi.org/10.2139/ssrn.3016996

Seung Mo Cho (Contact Author)

Yeungnam University - School of Economics & Finance ( email )

214-1, Dae-dong
Kyongsan, 712-749
Korea, Republic of (South Korea)

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