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The stock market behaviour prior and subsequent to new highs

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  • Oliver Schnusenberg

Abstract

Until recently, the empirical focus of the finance literature has been on the long-accepted weak-form and potentially semistrong-form of market efficiency, as initially argued by Sharpe and by Lintner. A recently heavily researched area of behavioural financial research may bring us one step closer to understanding the psychology of investors and its effects on financial markets. The objective of this article is to investigate the aggregate behaviour of the stock market immediately prior and subsequent to new stock market highs over the period 1988 to 2002. General results indicate that abnormal returns over five windows prior to new level highs with highs of 50, 100, 500, and 1000 points in the Dow Jones Industrial Average and the S&P 500 index are significantly lower than returns over the same windows on non-high days. Interestingly, there is little momentum associated with abnormal returns subsequent to new highs. Furthermore, there is some evidence that the variance of abnormal returns in the windows surrounding new high days is significantly larger than the variance of abnormal returns over the same window on non-high days for all levels investigated and both prior and subsequent to the new high days. These results indicate that new index highs in a stock market index present a psychological barrier for investors, who trade cautiously as the new index high is approached. The larger return variance prior and subsequent to the new high day is indicative of active buying and selling activity prior and subsequent to the new high.

Suggested Citation

  • Oliver Schnusenberg, 2006. "The stock market behaviour prior and subsequent to new highs," Applied Financial Economics, Taylor & Francis Journals, vol. 16(6), pages 429-438.
  • Handle: RePEc:taf:apfiec:v:16:y:2006:i:6:p:429-438
    DOI: 10.1080/09603100500400437
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    Cited by:

    1. Joshua Becker & Douglas Guilbeault & Ned Smith, 2021. "The Crowd Classification Problem: Social Dynamics of Binary Choice Accuracy," Papers 2104.11300, arXiv.org.
    2. Joshua Aaron Becker & Douglas Guilbeault & Edward Bishop Smith, 2022. "The Crowd Classification Problem: Social Dynamics of Binary-Choice Accuracy," Management Science, INFORMS, vol. 68(5), pages 3949-3965, May.

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