This study attempts to improve a Credit Portfolio View model (CPV model) which is an econometric credit risk model by adding the effect of default contagion and rating migration. In this study, macroeconomic variables along with several forms of default contagion and rating migration variables are fit with default probability data of a corporate sector. As a result, some models which fit well with default probability are used to assess the impact of these new variables in fitting default probability. We can point out the variables that fit well with default probability. Moreover, this study also attempts to propose a new method to compute a conditional rating transition matrix which incorporates the state-of-economy. The novelty of this matrix is that each rating transition probability in a rating transition matrix is adjusted based on the overall probability. A new equation is proposed; in addition, parameters are estimated. Furthermore, some models which fit well with default probability are used to forecast default probability in the next ten years for further analyses. The overall default probabilities, the conditional rating transition probabilities, and the cumulative default probabilities are then simulated from a Monte Carlo simulation. The default probability distributions are then created. As a result, we get the empirical results of default probability distributions along with interesting suggestions to improve the CPV model.
A CREDIT CONTAGION MODEL OF A CORPORATE PORTFOLIO
Post by MSF Chula at Sunday, 31 January 2021 10:38 PM
Last updated at Sunday, 31 January 2021 10:38 PM