Using the autoregressive conditional duration model to analyse the process of default contagion

Credit events are not independent, and the contagion effect is very common. The seriousness of the contagion effect depends on the change in the default contagion duration before and after credit events. This study uses the Autoregressive Conditional Duration (ACD) model to capture the durations of a series of credit events and to study the characteristics of a default duration series. The empirical samples are listed and Over-The-Counter (OTC) companies in Taiwan. The Moving Block Bootstrap (MBB) in Liu and Singh (1992) is employed to copy the sample data. The sample period is from October 1982 to December 2007. The results show that, in the entire sample and subsamples of the electronic information industry and construction industry, the default duration series demonstrates the conditional autocorrelation and cluster effect. The ACD model helps capture the contagion effect of credit events.