EMPIRICAL STUDIES OF STRUCTURAL CREDIT RISK MODELS AND THE APPLICATION IN DEFAULT PREDICTION: REVIEW AND NEW EVIDENCE

Han-Hsing Lee (), Ren-Raw Chen and Cheng-Few Lee
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Han-Hsing Lee: Graduate Institution of Finance, National Chiao Tung University, Hsunchu, Taiwan
Ren-Raw Chen: Finance and Economics, Fordham University, New York, NY 10023, USA
Cheng-Few Lee: Department of Finance and Economics, Rutgers Business School, Rutgers University, Piscataway, NJ 08854, USA
Authors registered in the RePEc Author Service: Cheng Few Lee

International Journal of Information Technology & Decision Making (IJITDM), 2009, vol. 08, issue 04, 629-675

Abstract: This paper first reviews empirical evidence and estimation methods of structural credit risk models. Next, an empirical investigation of the performance of default prediction under the down-and-out barrier option framework is provided. In the literature review, a brief overview of the structural credit risk models is provided. Empirical investigations in extant literature papers are described in some detail, and their results are summarized in terms of subject and estimation method adopted in each paper. Current estimation methods and their drawbacks are discussed in detail. In our empirical investigation, we adopt the Maximum Likelihood Estimation method proposed by Duan [Mathematical Finance10(1994) 461–462]. This method has been shown by Ericsson and Reneby [Journal of Business78(2005) 707–735] through simulation experiments to be superior to the volatility restriction approach commonly adopted in the literature. Our empirical results surprisingly show that the simple Merton model outperforms the Brockman and Turtle [Journal of Financial Economics67(2003) 511–529] model in default prediction. The inferior performance of the Brockman and Turtle model may be the result of its unreasonable assumption of the flat barrier.

Keywords: Structural credit risk model; estimation approach; default prediction; Maximum Likelihood Estimation (MLE) (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0219622009003703

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