IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v49y2017i8p812-822.html
   My bibliography  Save this article

Skewness preferences, asset prices and investor sentiment

Author

Listed:
  • Benjamin M. Blau

Abstract

Prior research has found that investors have strong preferences for stocks with positive skewness. These preferences have been shown to lead to price premiums and subsequent underperformance. This study extends this growing body of literature by testing whether the underperformance of stocks with positive skewness is driven by periods of high investor sentiment. The motivation for these tests is based on a broad literature in Psychology that an individual’s mood can directly affect the individual’s subjective probability assessments. In the framework of our tests, more optimism among investors may strengthen investors’ skewness preferences. The empirical results in this study support this idea as the underperformance of positively skewed stocks is shown to be primarily driven by periods of high investor sentiment.

Suggested Citation

  • Benjamin M. Blau, 2017. "Skewness preferences, asset prices and investor sentiment," Applied Economics, Taylor & Francis Journals, vol. 49(8), pages 812-822, February.
    • Handle: RePEc:taf:applec:v:49:y:2017:i:8:p:812-822
    DOI: 10.1080/00036846.2016.1205727
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2016.1205727
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2016.1205727?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lepone, Grace & Yang, Zhini, 2020. "Do early birds behave differently from night owls in the stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    2. Mei-Chen Lin, 2020. "When analysts encounter lottery-like stocks: lottery-like stocks and analyst stock recommendations," Review of Quantitative Finance and Accounting, Springer, vol. 55(1), pages 327-353, July.
    3. Sheng-Ping Yang & Thanh Nguyen, 2019. "Skewness Preference and Asset Pricing: Evidence from the Japanese Stock Market," JRFM, MDPI, vol. 12(3), pages 1-10, September.
    4. Jiang, Shanshan & Fan, Hong, 2018. "Credit risk contagion coupling with sentiment contagion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 186-202.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:applec:v:49:y:2017:i:8:p:812-822. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.