In addressing the question of the time scales characteristic for the market
formation, we analyze high frequency tick-by-tick data from the NYSE and from
the German market. By using returns on various time scales ranging from seconds
or minutes up to two days, we compare magnitude of the largest eigenvalue of
the correlation matrix for the same set of securities but for different time
scales. For various sets of stocks of different capitalization (and the average
trading frequency), we observe a significant elevation of the largest
eigenvalue with increasing time scale. Our results from the correlation matrix
study go in parallel with the so-called Epps effect. There is no unique
explanation of this effect and it seems that many different factors play a role
here. One of such factors is randomness in transaction moments for different
stocks. Another interesting conclusion to be drawn from our results is that in
the contemporary markets the emergence of significant correlations occurs on
time scales much smaller than in the more distant history.Comment: 13 page