A PIN Per Day Shows What News Convey – The Intraday Probability of Informed Trading

75 Pages Posted: 26 Aug 2013

See all articles by Michael J. Aitken

Michael J. Aitken

Macquarie Graduate School of Management

Thomas Pöppe

Darmstadt University of Technology - Chair for Corporte Finance

Dirk Schiereck

Darmstadt University of Technology

Ingo Wiegand

Darmstadt University of Technology

Date Written: August 26, 2013

Abstract

Insider trading and the effectiveness of regulatory actions trying to detect and prevent it are of great interest to traders, regulators, prosecutors and the public. This paper develops an intraday estimation procedure for the sequential trading model initially proposed by Easley et al. (1987, 1992, 1996, 1997) to show how official announcements stipulated in German insider trading legislation significantly reduce information asymmetry upon public disclosure. Using a full year of intraday trading data for the top 100 German stocks, we demonstrate how the new estimation procedure presented in this paper eliminates or significantly reduces the shortcomings of the original approach in recent, high-frequency trading environments, which are convergence problems during parameter estimation, limited applicability in short horizon event studies and violations of the model’s underlying assumptions.

Keywords: Capital Markets, Probability of Informed Trading, High-Frequency Trading, Insider Trading Regulation, Event Study

JEL Classification: G14

Suggested Citation

Aitken, Michael J. and Pöppe, Thomas and Schiereck, Dirk and Wiegand, Ingo, A PIN Per Day Shows What News Convey – The Intraday Probability of Informed Trading (August 26, 2013). Available at SSRN: https://ssrn.com/abstract=2316041 or http://dx.doi.org/10.2139/ssrn.2316041

Michael J. Aitken

Macquarie Graduate School of Management ( email )

North Ryde
Sydney, New South Wales 2109
Australia

Thomas Pöppe (Contact Author)

Darmstadt University of Technology - Chair for Corporte Finance ( email )

Hochschulstrasse 1
Darmstadt, 64289
Germany

Dirk Schiereck

Darmstadt University of Technology ( email )

Universitaets- und Landesbibliothek Darmstadt
Magdalenenstrasse 8
Darmstadt, Hesse D-64289
Germany

Ingo Wiegand

Darmstadt University of Technology ( email )

Universitaets- und Landesbibliothek Darmstadt
Magdalenenstrasse 8
Darmstadt, Hesse D-64289
Germany

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