Abstract
In this study, we have investigated sudden changes in volatility and re-examined the persistence of volatility in Japanese and Korean stock markets during 1986–2008. Using the iterated cumulative sums of squares (ICSS) algorithm, we have determined that the identification of sudden changes is generally associated with global financial and political events. We have also demonstrated that controlling sudden changes effectively reduces the persistence of volatility or long memory and that incorporating information regarding sudden changes in variance improves the accuracy of estimating volatility dynamics and forecasting future volatility for researchers and investors.
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