Validation of the Merton Distance to the Default Model under Ambiguity

Journal of Risk and Financial Management

Wei-ling Chen¹ 

[1] Department of Quantitative Finance, National Tsing Hua University, Hsinchu 30013, Taiwan; E-Mail

关键词: Merton’s distance to default model;    naive model;    default probability;    ambiguity aversion;    consumer confidence index;    statistical significance;   

DOI  :  10.3390/jrfm7010013

来源: mdpi

【 摘 要 】

Bharath and Shumway (2008) provide evidence that shows that it is the functional form of Merton’s (1974) distance to default (DD) model that makes it useful and important for predicting defaults. In this paper, we investigate whether the default predictability of the Merton DD model would be affected by taking investors’ ambiguity aversion into consideration. The Cox proportional hazard model is used to compare the forecasting power of Bharath and Shumway’s naive model, which retains the functional form of the Merton DD model and computes the default probability in a naive way, with our new model, which treats investors’ ambiguity aversion as additional information. We provide evidence to show that our new model performs better than Bharath and Shumway’s naive model. In addition, our empirical results show that the statistical significance of Bharath and Shumway’s naive default probability is retained in the credit default swap (CDS) spread regressions, though the sign of the coefficient is changed. However, both the sign and the statistical significance of our model are retained in the CDS spread regressions.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.