Comparative study on Warsaw Stock Exchange and Vienna Stock Exchange

A very important research topic is describing the way in which different asset price movements are correlated. Modern portfolio theory methods are based on observed correlations between returns at daily or larger time scales. One expects that coarse scale correlations originate from intraday movements that are strongly correlated. This implies the important question of how to obtain better estimates of such correlations by using high-frequency data. Here, one can observe an analogous paradox as for volatility estimation under microstructure noise. It is surprising that the correlation coefficient is an increasing function of the time resolution, and that correlation very quickly decays and almost vanishes at a very high frequency. The dependence of correlations between stock prices on the sampling frequency of time series involves a phenomenon called the Epps effect. The actual correlations between returns of stocks decrease as the sampling frequency of data increases. The Epps effect has received considerable attention, not only from economists but also from mathematicians and theoretical physicists. But there are only a few contributions to the subject. The Epps effect seems to be an unexpected phenomenon at a first glance. However it is simply explainable by different factors; e.g., the asynchrony of trade times. It is clear that 1-minute returns are, in fact, returns for the last trade prices