ABSTRACT
The major aim of this empirical study is to estimate the volatility time series returns for a cluster of international stock markets, such as: Switzerland, Austria, China and Hong Kong. The paper demonstrates statistical modeleling in order to capture volatility clusters and changes in long and short term volatility impact. The econometric approch is based on randomly selected daily closing return collected for the main indices of stock markets in Switzerland, Austria, China and Hong Kong for the sample period January 2003 to September 2021. We used various statistical properties to test normalities based on using GARCH family models for estimating financial market volatility. Moreover, the sampled time interval includes two extreme events such as the global financial crisis (GFC) of 2007–2008 and the recent COVID-19 pandemic. © 2021, Universitatea din Craiova. All rights reserved.