Abstract
This article compares the reliability of a discrete-time and a continuous-time Markov chain model for estimating credit risk and for investigating loans of Chiao Tung Bank in Taiwan. The continuous-time Markov chain model can capture the migration of rare events. The time-varying risk premium was also extracted from the loan value and corresponding risk-free price and the transition matrix was transferred to risk-neutral transition matrix by the time-varying risk premium. Finally, the empirical results indicate that the discrete-time Markov chain model may be underestimating the default probability in both the lowest risk and speculative rating class. Comparing the loss given default and the NPL ratio, the continuous-time Markov chain model is more reliable and effective for gauging the credit risk of bank loans.
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