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Trading Behavior Prior to Public Release of Analyst Reports: Evidence from Korea

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  • Bobae Choi
  • Kooyul Jung
  • Doowon Lee

Abstract

This paper investigates information leakage from analyst reports prior to their public release. Previous studies document abnormal trading by institutions or short selling before announcement of recommendation changes. Such prerelease abnormal trading is interpreted as evidence of information leakage from analyst reports. However, if sophisticated investors obtain information similar to what analysts have from other sources, abnormal prerelease trading patterns would be observed even if there were no information leakage from analyst reports. This paper, using a unique data set from Korea, aims to determine whether a direct causal link between recommendation changes and prerelease trading exists, by comparing trading behavior of client investors with non†client investors. We find that abnormal prerelease trading by client investors, especially client institutions, is earlier in timing and greater in magnitude than that of other investor groups, supporting the information leakage hypothesis. We further find that net buying by client institutions and client large individuals is positively associated with firm, analyst, and earnings forecast change variables that influence formulation of recommendation changes and their impacts.

Suggested Citation

  • Bobae Choi & Kooyul Jung & Doowon Lee, 2015. "Trading Behavior Prior to Public Release of Analyst Reports: Evidence from Korea," Contemporary Accounting Research, John Wiley & Sons, vol. 32(1), pages 105-138, March.
  • Handle: RePEc:wly:coacre:v:32:y:2015:i:1:p:105-138
    DOI: 10.1111/1911-3846.12090
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    Cited by:

    1. Sébastien Galanti & Zahra Ben Braham, 2017. "Information efficiency on an emerging market: analysts' recommendations in Tunisia," Economics Bulletin, AccessEcon, vol. 37(1), pages 377-390.
    2. Dai, Rui & Massoud, Nadia & Nandy, Debarshi K. & Saunders, Anthony, 2017. "Hedge funds in M&A deals: Is there exploitation of insider information?," Journal of Corporate Finance, Elsevier, vol. 47(C), pages 23-45.
    3. Zhang, Yuan-Yuan & Zhang, Yue-Jun, 2022. "The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. Mao, Ruiqi & Segara, Reuben & Westerholm, Joakim, 2019. "Analyst tipping: Evidence on Finnish stocks," International Review of Financial Analysis, Elsevier, vol. 66(C).

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