Market-Based Evaluation for Models to Predict Bond Ratings

Konan Chan () and Narasimhan Jegadeesh ()
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Konan Chan: Department of Finance, College of Management, National Taiwan University, Taipei 10660, Taiwan, ROC
Narasimhan Jegadeesh: Goizueta Business School, Emory University, 1300 Clifton Road, Atlanta, GA 30322-2722, USA

Review of Pacific Basin Financial Markets and Policies (RPBFMP), 2004, vol. 07, issue 02, 153-172

Abstract: Previous studies have examined different statistical models to predict corporate bond ratings. However, these papers use agency ratings as the benchmark to assess models and ignore the evidence that agency ratings may not be accurate in a timely manner. In this paper, we propose a new approach which incorporates ex-post bond returns to evaluate rating prediction models. Relative rating strength portfolios, formed by buying under-rated bonds with agency ratings lower than model ratings and selling over-rated bonds with agency ratings higher than model ratings, are employed to test the performance of different statistical models in rating predictions. Our results show that one version of multiple discriminant analysis model can generate a statistically significant abnormal return of 5% over a 5-year horizon. The ordered probit model which is believed to possess theoretical advantages in classifying bonds does not perform better. This suggests that using traditional measures to evaluate models can be misleading. The existence of a profitable trading strategy also raises the concern of market efficiency in the corporate bond market.

Keywords: Bond rating prediction; relative rating strength portfolio; bond trading strategy; bond market efficiency (search for similar items in EconPapers)
JEL-codes: G1 G2 G3 (search for similar items in EconPapers)
Date: 2004
References: View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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DOI: 10.1142/S0219091504000081

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