摘要：This paper studies the impact of a number of volatile data sets on volatility spillover tests. We investigate a type of data generating process, AR(1)-GARCH(1,1), with an extensive set of Monte Carlo simulations. It is found that causation pattern, due to causality between two series, is in.uenced by the intensity of volatility clustering. Two testing pro cedures are applied for testing causality in the variance. We notice a severe size and power distortion when the clustering parameter is high and when the pro cess is near integration. Furthermore, whenever there is a severe size distortion, there is a serial auto correlation in the standardized residuals. This is seen when the asymptotic distribution of the statistics is used to define a critical region. So, instead of relying on the asymptotic distribution, we calculate the percentiles of the test statistic with the null hypothesis of no spillover e.ect and use them as a critical region for both size and p ower. We observe a significant improvement in the results.
