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A PIN per day shows what news convey: the intraday probability of informed trading

Thomas Pöppe (), Michael Aitken, Dirk Schiereck and Ingo Wiegand
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Thomas Pöppe: Technische Universität Darmstadt
Dirk Schiereck: Technische Universität Darmstadt
Ingo Wiegand: Stanford University

Review of Quantitative Finance and Accounting, 2016, vol. 47, issue 4, No 12, 1187-1220

Abstract: Abstract This paper develops a new intraday estimation procedure for the sequential microstructure trading model initially proposed by Easley et al. (Rev Financ Stud 10:805–835, 1997a). Using a full year of intraday trading data for the top 100 German stocks, we demonstrate how the new estimation procedure eliminates or significantly reduces the shortcomings of the original approach in recent, high-frequency trading environments. We slice a trading day in buckets of several minutes’ length to obtain one estimate of the composite variable probability of informed trading (PIN) per day. This approach makes PIN applicable in short horizon event studies. Convergence rates are above 95 % even for the most liquid stocks and the model’s underlying assumptions of independence for the arrival of traders and information events are fulfilled to a much higher degree than in the original approach. An empirical application in an event study type setting demonstrates how official announcements stipulated in German insider trading legislation significantly reduce information asymmetry upon public disclosure.

Keywords: Capital markets; Probability of informed trading; Information asymmetry; High-frequency trading; Insider trading regulation (search for similar items in EconPapers)
JEL-codes: G14 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11156-015-0535-z

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