Time-Varying Arrival Rates of Informed and Uninformed Trades
38 Pages Posted: 21 Dec 2001
Date Written: December 7, 2001
We propose a dynamic model of trade and estimate the model on 16 actively traded stocks on the New York Stock Exchange over 15 years of transaction data. We investigate (1) how the arrival rates of informed and uninformed trades vary over time, (2) how they interact with each other, and (3) what the implications are of the trade dynamics on the securities price processes such as market liquidity, depth, and volatility.
In particular, 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 forecastable. We specify a generalized autoregressive bivariate process for (1) the arrival rates of trades and (2) the logarithm of the arrival rates. Calibration results indicate that the two specifications exhibit similar performance. They both point to some common features of the trade dynamics. First, the arrival rates of both informed and uninformed trades are highly persistent. Heavy trading is more likely to be followed by heavy trading. Second, uninformed traders tend to follow their own type but to avoid the informed traders. Uninformed traders refrain from entering the market after a day with many informed traders. Informed traders, on the other hand, are not as responsive to the arrival of uninformed traders. Finally, while the arrival rates of both types of traders increase over time, it is mainly the increase in the arrival of uninformed traders that contributes to the surge in trading activities.
Given the forecasted arrival rates, we investigate the correlation between the arrival rates of trades and trade composition on market volatility and liquidity. First, we find that the forecasted arrival rates of both types of trades are positively correlated with intra-day volatility measures such as the absolute returns on daily open-close and high-low. Hence, potentially we could use the forecasted arrival rates to enhance the forecasting of daily volatilities. Second, under our model structure, the opening bid-ask spread, a measure of market liquidity, is proportional to the relative proportion of informed trades and the significance of the information event. We find that the proportion of informed trades is negatively correlated with the total number of trades. As the number of trades increases over time, the relative proportion of informed trades increases and hence, assuming relative time stability on the significance of information events, the opening bid-ask spread becomes 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. The difference in mean half life across stocks indicates their difference in market depth. The positive correlation between the half life and total trades indicates that the market is deeper in presence of more trades.
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