The thesis concentrate on a volatility analysis os a stock market in the Czech Republic in years 1994-2009 including a comparison with a data available from world developed stock markets - namely European region, USA and Japan, econometric tools include GARCH model and its most popular derivates and generalisations I.E. IGARCH, EGARCH AND APARCH PROCESSES. The thesis is split into two main parts. The first part is devoted to a PSE volatility analysis based only on domestic data series involving GARCH class model estimations, forecasting abilities comparison and also a structural-break analysis based on the ICSS algorithm including the Inclan-Tiao test and its successors. Next part involves a dynamic analysis based on DCC MVGARCH model, which describes a change in a volatility spillover effect during the time. Data source used during the model estimation includes a development of stock indices and also net profits from point of view of Czech investor investing on global markets. It is furthermore supported by Granger causality estimation, which reveals a long-lasting unidirectional dependence of PSE on other developed markets. The complex results, which arise from a synergistic compound of particular econometric models, show that the stock market in the Czech Republic came through three main phases
