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Credit Analysis, Bond Rating Forecasting, and Default Probability Estimation

In: HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING

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  • Cheng Few Lee

Abstract

In this chapter, we will discuss how to use discriminant analysis to do credit analysis and calculate financial z-score, then we will use both discriminant analysis and factor analysis to forecast bond rating by using financial ratio information. In addition, we will discuss Ohlson’s model and the KMV–Merton model for default probability estimation. Finally, we will cite some empirical results about default probability estimation and compare the results of two different probability estimation models.

Suggested Citation

  • Cheng Few Lee, 2020. "Credit Analysis, Bond Rating Forecasting, and Default Probability Estimation," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 78, pages 2635-2671, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789811202391_0078
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    More about this item

    Keywords

    Financial Econometrics; Financial Mathematics; Financial Statistics; Financial Technology; Machine Learning; Covariance Regression; Cluster Effect; Option Bound; Dynamic Capital Budgeting; Big Data;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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