Estimating the probability of informed trading—does trade misclassification matter?
- 关键词：Informed trading ; Market microstructure ; Trade classification
- 刊名：Journal of Financial Markets
- 出版年：2007
- 期刊代码：48_13864181
- 类别：bus
- 出版时间：February 2007
- 卷：10
- 期：1
- 页码：26-47
- 文件大小：373 K
摘要
Easley et al. [1996. Journal of Finance 51, 1405–1436] have proposed an empirical methodology to estimate the probability of informed trading (PIN). This approach has been employed in a wide range of applications in market microstructure, corporate finance, and asset pricing. To estimate the model, a researcher only needs the number of buyer- and seller-initiated trades. This information, however, is generally unobservable and has to be inferred from trade-classification algorithms, which are known to be inaccurate. In this paper, we show analytically that inaccurate trade classification leads to downward-biased PIN estimates and that the magnitude of the bias is related to a security's trading intensity. Simulation results and empirical evidence based on order and transaction data from the New York Stock Exchange are consistent with this argument. We propose a data-based adjustment procedure that substantially reduces the misclassification bias.