Abstract
This chapter 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 (1994). This method has been shown by Ericsson and Reneby (2005) 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 (2003) 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.
| Original language | English |
|---|---|
| Title of host publication | Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (In 4 Volumes) |
| Publisher | World Scientific Publishing Co. |
| Pages | 1845-1901 |
| Number of pages | 57 |
| ISBN (Electronic) | 9789811202391 |
| ISBN (Print) | 9789811202384 |
| DOIs | |
| State | Published - 01 01 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2021 by World Scientific Publishing Co. Pte. Ltd.
Keywords
- Default prediction
- Down-and-out barrier model
- Estimation approach
- KMV estimation method
- Maximum likelihood estimation (MLE)
- Monte carlo experiment
- Structural credit risk model
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