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How to test an insider trading law and its effectiveness: Price movements and comparative empirical data from Taiwan

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  • Lin, Chien-Chung
  • Wu, Huan-Ting

Abstract

Successfully enforcing insider trading law, as well as determining the effectiveness of that enforcement, is one of the quandaries of securities law. The main reason for this perplexity is that there is no tally of how many illegal trading activities are actually taking place. To solve this problem, this study proposes to use pre-announcement price run-up as a proxy for measuring the effectiveness of an insider trading law. After examining mergers and acquisitions data from Taiwan’s Financial Supervisory Commission from 2003 to 2016 and adjusting for market effect, we arrive at an average cumulative abnormal return of 6.62% before the official announcement of the events. This constitutes a 58.9% run-up compared with the post-announcement price increase.

Suggested Citation

  • Lin, Chien-Chung & Wu, Huan-Ting, 2019. "How to test an insider trading law and its effectiveness: Price movements and comparative empirical data from Taiwan," International Review of Law and Economics, Elsevier, vol. 57(C), pages 22-36.
    • Handle: RePEc:eee:irlaec:v:57:y:2019:i:c:p:22-36
    DOI: 10.1016/j.irle.2018.11.002
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    Cited by:

    1. Prashant Priyadarshi & Prabhat Kumar, 2024. "A comprehensive review on insider trading detection using artificial intelligence," Journal of Computational Social Science, Springer, vol. 7(2), pages 1645-1664, October.

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