An event based approach for quantifying the effects of securities fraud in the IT industry
Lorne Switzer () and
Jun Wang ()
Additional contact information
Jun Wang: University of Western Ontario
Information Systems Frontiers, 11 pages
Abstract Detecting the incidence and impact of illegal insider trading is a difficult process since access to the actual trading records of insiders that overlap precisely with fraudulent events is difficult. This paper provides a case study of a specific IT stock in Canada that was successfully prosecuted in the Canadian court system for market manipulation and illegal insider trading violations. The study provides a quantification of the impact of insider trading activities by the President directly through his own account or through accounts under his control, and illustrates the impact of some off-exchange transactions by the impugned parties. Overall, the costs of the insider trading violations are quite high, given the significant wealth effects produced by the events surrounding this case.
Keywords: Insider trading; Market manipulation in IT industry; Market efficiency; Event studies (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s10796-017-9753-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Journal Article: An event based approach for quantifying the effects of securities fraud in the IT industry (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v::y::i::d:10.1007_s10796-017-9753-3
Ordering information: This journal article can be ordered from
Access Statistics for this article
Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao
More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().