Abstract
In the paper we research statistical properties of the Central European stock markets. We focus mainly on the tail behavior of the Czech, Polish, and Hungarian stock markets and compare them to the benchmark U.S. and German stock markets.
We fit the data of the 4-year period from March 2005 to March 2009 with the stable probability distribution model and discuss its tail behavior. As the estimation of the tail exponent is very sensitive to the size of the data set, the estimates can be misleading for short daily samples.
Thus, we employ high-frequency 1-minute data, which proves to be a good choice as it reveals interesting findings about the distributional properties. Furthermore, we study the difference in stock market behavior before and during the financial crisis.