CRIF Working Paper No. 02017

Time-Varying Arrival Rates of Informed and Uninformed Trades

Title: Time-Varying Arrival Rates of Informed and Uninformed Trades

Authors: David Easley (Cornell University)

              Robert Engle (New York Unviersity)

              Maureen O'Hara (Cornell University)

              Liuren Wu (Fordham University)

Contact: wu@fordham.edu

Abstract: In this paper we extend the model of Easley and O'Hara (1992) to allow the arrival rates of informed and uninformed trades to be time-varying and and forecastable. We specify a generalized autoregressive bivariate process for the arrival rates of informed and uninformed trades and estimate the model on 16 actively traded stocks on the New York Stock Exchange over 15 years of transaction data. Our results show that uninformed trades are highly persistent. Uninformed order arrivals clump together, with high uninformed volume days likely to follow high uninformed volume days, and conversely. This behavior is consistent with the passive characterization of the uninformed found in the literature. But we do find an important difference in how the uninformed behave; they avoid trading when the informed are forecasted to be present. Informed trades also exhibit complex patterns, but these patterns are not consistent with the strategic behavior posited in the literature. The informed do not appear to hide in order flow, but instead they trade persistently. 

     We also investigate the correlation between the arrival rates of trades and trade composition on market volatility, liquidity, and depth. We find that although volatility increases with the forecasted arrival rates of total trades, it is relatively independent of the forecasted composition of the trade. We use the opening bid-ask spread as a measure of market liquidity. We find that as the number of trades increases over time, the relative proportion of informed trades decreases and hence, spreads become narrower and the market becomes more liquid. Finally, we compute the price impact curve of consecutive buy orders and report the half life of the price impact as a measure of market depth. We find a positive correlation between the half life and total trades indicating that the market is deeper in presence of more trades.         

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