Alternative Method for Determining Industrial Bond Ratings: Theory and Empirical Evidence

Lie-Jane Kao and Cheng Few Lee

Chapter 57 in Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning:(In 4 Volumes), 2020, pp 2081-2105 from World Scientific Publishing Co. Pte. Ltd.

Abstract: The financial ratio-based credit-scoring model for bond rating system requires the maximization of two conflicting objectives simultaneously, namely, the explanatory and discriminatory power, which had not been directly addressed in literature. The main purpose of this study is to develop a credit-scoring model that combines the principle component analysis and Fisher’s discriminant analysis using the MINIMAX goal programming technique so the maximization of the two conflicting objectives can be compromised. The performance of alternative credit-scoring models including the stepwise discriminant analysis by Pinch and Mingo, Fisher’s discriminant analysis, and the principle component analysis is analyzed and compared using dataset from previous studies. We find that the proposed hybrid credit-scoring model outperforms other alternative models in both explanatory and discriminatory powers.

Keywords: Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data (search for similar items in EconPapers)
JEL-codes: C01 C1 G32 (search for similar items in EconPapers)
Date: 2020
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Journal Article: ALTERNATIVE METHOD FOR DETERMINING INDUSTRIAL BOND RATINGS: THEORY AND EMPIRICAL EVIDENCE (2012)
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