Recently, Duarte and Young (2009) studied the probability of informed trading (PIN) proposed by Easley et al. (2002) and decomposed 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 effective 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.