scholarly journals Insider Trading Regulation: The Path Dependent Choice between Property Rights and Securities Fraud

Author(s):  
Stephen M. Bainbridge
1991 ◽  
Vol 30 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kurt Stanberry ◽  
Barbara Crutchfield George ◽  
Maria Ross

2001 ◽  
Vol 87 (7) ◽  
pp. 1229 ◽  
Author(s):  
Zohar Goshen ◽  
Gideon Parchomovsky

2020 ◽  
Vol 17 (5) ◽  
pp. 558-600
Author(s):  
Ana Taleska

AbstractParity-of-information is purported to be the single overarching policy rationale for the European Union (EU) regulation on insider trading. This is because securities trading on the basis of informational advantages is generally prohibited under EU rules, as is tipping (and issuers’ selective disclosure) of material, non-public information. Yet, EU regulations allow market actors, including investment professionals and analysts, that have discovered valuable information -and thereby, have an informational advantage vis-à-vis their trading counterparties- to trade on this information. Relatedly, issuers of financial instruments, takeover bidders and merging parties can share information with a selected group of investors prior to public announcement of the transaction (market sounding), whereas firms can delay public disclosure of inside information and prevent all other market participants from trading on this information. I argue that these exceptions from the parity-of-information theory are -from a doctrinal standpoint- best explained as property rights in information of market actors that have developed new proprietary information with respect to European listed securities. This article, therefore, aims at providing a property rights account of the exceptions to the parity-of-information theory and it illustrates the trade-offs between the parity-of-information and the property rights in information theories underlying European insider trading rules. By extension, I analyze the specific case of activist campaigns as inside information and argue that it would be consistent with the property rights approach to allow activist investors to share their investment and trading strategies with other market participants that further their activist agenda.


2020 ◽  
Vol 7 (3) ◽  
pp. 12-29
Author(s):  
M. Fevzi Esen

Insider trading is one the most common deceptive trading practice in securities markets. Data mining appears as an effective approach to tackle the problems in fraud detection with high accuracy. In this study, the authors aim to detect outlying insider transactions depending on the variables affecting insider trading profitability. 1,241,603 sales and purchases of insiders, which range from 2010 to 2017, are analyzed by using classical and robust outlier detection methods. They computed robust distance scores based on minimum volume ellipsoid, Stahel-Donoho, and fast minimum covariance determinant estimators. To investigate the outlying observations that are likely to be fraudulent, they employ event study analysis to measure abnormal returns of outlying transactions. The results are compared to the abnormal returns of non-outlying transactions. They find that outlying transactions gain higher abnormal returns than transactions that are not flagged as outliers. Business intelligence and analytics may be a useful strategy for detecting and preventing of financial fraud for companies.


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