Forecasting Probability of default of Corporations with the Merton model: Using Capital Asset Pricing Model with Time Varying Beta

Subject Areas : Financial engineering

mehdi sabeti ¹ , Gholamreza Zomorodian ^{2 *} , mirfeyz fallah ³ , mehrzad minuyi ⁴

1 - Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran and member of Modern Financial Risk Research Group
3 - Department of Financial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran and member of Modern Financial Risk Research Group
4 - Department of Industrial Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

Received: 2021-06-29 Accepted : 2021-08-04 Published : 2022-09-23

Keywords: Credit Risk, Probability of Default, structural method, MGARCH,

Abstract :

The purpose of this article is to predict probability of default of 60 corporations with structural Merton model. we used market data of 60 corporations from 2018/08/01 to 2019/09/01 witch are listed in Tehran Stock Exchange For predicting probability of default . to reach this goal we estimated assets value of corporations, volatility of assets and drift rate. We used Capital asset pricing method to estimate expected assets return. Then We used simple regression method and multivariate GARCH (MGARCH) to estimate Beta of corporations. in the end we compute d likelihood function of the average predicted default for each industry and compared the results with actual default rate of that industry in the next year after predicted date. Regarding obtained results of likelihood function probability of default prediction with multivariate GARCH (MGARCH) approach outperform the simple regression model, therefore we recommend using the MGARCH approach for its better prediction performance.