The Implied Intra-Day Probability of Informed Trading

The paper develops a methodology for estimating the intra-day probability of informed trading for NYSE stocks, implied by the specialist’s quotes and depths. The time series pattern of our measure ( PROBINF ) in an intra-day analysis around earnings announcements is consistent with previous findings and with expectations regarding informed trading. Moreover, we find that PROBINF exhibits a strong and robust relationship with PIN , the level of insider trading and with measures of the price impact of trades. Our methodology complements the one developed in Easley et al. (J Financ 51(3):811–833, 1996a , J Financ 51(4):1405–1436, b ), as it can be used to measure short term changes in informed trading and information asymmetry around events such as merger and acquisition announcements, share repurchases, stock splits, dividend announcements and index additions and deletions.