Recently Duarte and Young (2009) study the probability of informed trading (PIN) proposed by Easley et al. (2002) and decompose it into two parts: the adjusted PIN (APIN) as a measure of asymmetric information and the probability of symmetric order-flow shock (PSOS) as a measure of illiquidity. They provide some cross-section estimates of these measures using daily data over annual periods. In this paper we propose a method to estimate daily APIN and PSOS by extending the method in Tay et al. (2009) using high-frequency transaction data. Our empirical results show that while PIN is positively contemporaneously correlated with variance, APIN is not. On the other hand, PSOS is positively correlated with daily average e ective spread and variance, which is consistent with the interpretation of PSOS as a measure of illiquidity. Compared to APIN, PSOS exhibits clustering and sporadic bursts over time.
autoregressive conditional duration, market microstructure, probability of informed trading, probability of symmetric order-flow shock, transaction data
Journal of Applied Econometrics
PREVE, Daniel and TSE, Yiu Kuen.
Estimation of Time Varying Adjusted Probability of Informed Trading and Probability of Symmetric Order-Flow Shock. (2013). Journal of Applied Econometrics. 28, (7), 1138-1152. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1398
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