AbstractThis study aims to compare the variance structure of high (daily) and low (weekly, monthly) data frequencies. Using the ARCH (1) and GARCH (1, 1) models, the study finds that the intensity of shocks is not the same for all series. The study first finds that the statistical properties of the three returns data series are substantially different from each other, and the persistence of conditional volatility is also different for the three series. The presence of persistence is greater in daily stock returns than in other data sets, which demonstrates that volatility patterns are sensitive to data series frequencies. Simply put, the results reveal that the variance structure of high-frequency data is dissimilar to low-frequency data, and the variance structure of daily data is very much related to the stylized facts associated with stock return volatility. Keywords: ARCH, GARCH models, KSE 100 -index, persistence.1. IntroductionThe most significant research topic in financial markets over the past three decades is stock return volatility. Since the publication of Engle's (1982) ARCH article, volatility has received considerable attention from researchers, practitioners, and policy makers. This interest is due to the fact that volatility is a measure of risk and different participants use it for different reasons. Volatility has been high for developing and developed countries in recent years, but is much higher for developing countries. So the study of volatility is more important in developing countries. After the 1987 crash, the need to measure volatility takes center stage… the focus of the article… the market: modeling and forecasting Kraft prices and conditional volatility” Unpublished research paper. Rizwan, M.F. and Khan, S. (2007), "Volatility of stock returns in emerging stock markets (KSEs): the relative effects of country and global factors", International Review of Business Research Papers Vol.3 No.2 June 2007 , pp. Selcuk, F. (2004), "Asymmetric Stochastic Volatility in Emerging Stock Markets", unpublished research paper, University of Southern California, Department of Economics. Bali, K. and Demirtas, O. (2006), “Testing Mean Reversion in Stock Market Volatility” Research Paper published Zhu, J. (2007), "Prcing Volatility of Stock Returns with Volatile and Persistent Components", School of Economics and Management, April. 23, 2007.