Comparing long-range correlations in ITT for groups of stocks with varying average levels of trading activity on the NYSE and the NASDAQ.

<p>(a) Dependence of exponent , characterizing the strength of correlations in ITT over scales from seconds up to a trading day, on the average level of trading activity. Each datapoint represents the group average over a subset of stocks, with a matching range of average intertrade times for the two markets. Stocks are grouped into subsets as indicated by vertical dashed lines in Fig. 3a,b. The consistent difference in the scaling exponent between NYSE and NASDAQ stocks suggests that independent of company characteristics such as market capitalization and industry sector, the temporal organization of ITT within a trading day carries an imprint of market structure. (b) Dependence of exponent characterizing correlations in ITT over time scales from a trading day to several months, on the average level of trading activity. On both markets we observe similar behavior with no systematic difference in the values of between NYSE and NASDAQ subsets of stocks with matching ranges of . These results suggest that over time horizons longer than a trading day, the impact of market structure on trading dynamics is less pronounced as more information is available to investors over longer time scales, driving their trading activity. The resulting more coherent behavior of investors is reflected in stronger correlations over longer time scales.