IDEAS home Printed from https://ideas.repec.org/a/wsi/afexxx/v17y2022i03ns2010495222500178.html
   My bibliography  Save this article

Does Premium Exist In The Stock Market For Labor Income Growth Rate? A Six-Factor-Asset-Pricing Model: Evidence From Pakistan

Author

Listed:
  • NAVEED KHAN

    (Department of Management Sciences, Islamia College University, Peshawar, Pakistan)

  • HASSAN ZADA

    (Department of Management Sciences, SZABIST Islamabad, Pakistan)

  • IMRAN YOUSAF

    (Department of Business Studies, Namal University, Mianwali, Pakistan)

Abstract

The objective of this study is to explore Roy and Shijin [(2018). A six factor assets pricing model. Borsa Istanbul Review, 18(3), 205–217] six-factor-model of asset pricing by extending Fama and French five-factor model to include human capital as a sixth factor in the context of Pakistan — an emerging country in Asia, and to test the validity of the six-factor asset pricing model in explaining time-series variations in portfolio returns of Pakistan equity market. For this purpose, we use Fama and Macbeth’s two-pass time series regression technique to test the validity and applicability of the six-factor model. The findings indicate that the six factors model is an appropriate asset pricing model for explaining time-series variations in Pakistan. Furthermore, the human capital (labor income growth rate) is significant for most of the portfolios constructed in this study, which implies that the human capital significantly explains time-series variations in portfolio returns. The empirical results encourage all types of investors and academics to incorporate human capital into asset pricing models. It helps in more accurately estimating the required rate of return, which can improve asset pricing models.

Suggested Citation

  • Naveed Khan & Hassan Zada & Imran Yousaf, 2022. "Does Premium Exist In The Stock Market For Labor Income Growth Rate? A Six-Factor-Asset-Pricing Model: Evidence From Pakistan," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 1-24, September.
  • Handle: RePEc:wsi:afexxx:v:17:y:2022:i:03:n:s2010495222500178
    DOI: 10.1142/S2010495222500178
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2010495222500178
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S2010495222500178?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.

    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:wsi:afexxx:v:17:y:2022:i:03:n:s2010495222500178. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/afe/afe.shtml .

    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.