IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v24y2019i3p1170-1192.html
   My bibliography  Save this article

Does one model fit all in global equity markets? Some insight into market factor based strategies in enhancing alpha

Author

Listed:
  • Subhransu S. Mohanty

Abstract

The sources of risk in a marketplace are systematic, cross‐sectional, and time varying in nature. Though the capital asset pricing model (CAPM) provides an excellent risk–return framework and the market beta may reflect the risk associated with risky assets, there are opportunities for investors to take advantage of dimensional and time‐varying return anomalies in order to improve their investment returns. In this paper, we restrict our analysis to return variations linked to market factor anomalies or factor or dimensional beta using the Fama–French three‐factor; Carhart four‐factor; Fama‐French five‐factor; and Asness, Frazzini, and Pederson (AFP)'s five‐ and six‐factor models. We find significant variations in explaining sources of risk across 22 developed and 21 emerging markets with data over a long period from 1991 to 2016. Each market is unique in terms of factor risk characteristics, and market risk as explained by the CAPM is not the true risk measure. Hence, contrary to the risk–return efficiency framework, we find that lower market risk results in higher excess return in 19 out of the 22 developed markets, which is a major anomaly. However, although in majority of the markets, the AFP models result in reducing market risk (15 countries) and enhancing alpha (11 countries), it is also very interesting to note that the CAPM is second only in generating excess returns in the developed markets. We are conscious of the fact, however, that each market is unique in its composition and trend even over a long time horizon, and hence, a generalized approach in asset allocation cannot be adopted across all the markets.

Suggested Citation

  • Subhransu S. Mohanty, 2019. "Does one model fit all in global equity markets? Some insight into market factor based strategies in enhancing alpha," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 1170-1192, July.
  • Handle: RePEc:wly:ijfiec:v:24:y:2019:i:3:p:1170-1192
    DOI: 10.1002/ijfe.1710
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.1710
    Download Restriction: no

    File URL: https://libkey.io/10.1002/ijfe.1710?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
    ---><---

    Citations

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


    Cited by:

    1. Fernando Anuno & Mara Madaleno & Elisabete Vieira, 2023. "Using the Capital Asset Pricing Model and the Fama–French Three-Factor and Five-Factor Models to Manage Stock and Bond Portfolios: Evidence from Timor-Leste," JRFM, MDPI, vol. 16(11), pages 1-22, November.
    2. Li, Jie & Zhou, Zhong-Qiang & Zhang, Yongjie & Xiong, Xiong, 2023. "Information interaction among institutional investors and stock price crash risk based on multiplex networks," International Review of Financial Analysis, Elsevier, vol. 89(C).
    3. Abid, Ilyes & Benlemlih, Mohammed & El Ouadghiri, Imane & Peillex, Jonathan & Urom, Christian, 2023. "Fossil fuel divestment and energy prices: Implications for economic agents," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 1-16.
    4. José Luis Miralles-Quirós & María Mar Miralles-Quirós & José Manuel Nogueira, 2020. "Sustainable Development Goals and Investment Strategies: The Profitability of Using Five-Factor Fama-French Alphas," Sustainability, MDPI, vol. 12(5), pages 1-16, February.
    5. Javier Rojo‐Suárez & Ana Belén Alonso‐Conde & Ricardo Ferrero‐Pozo, 2022. "Liquidity, time‐varying betas and anomalies: Is the high trading activity enhancing the validity of the CAPM in the UK equity market?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 45-60, January.
    6. Lien, Donald & Hung, Pi-Hsia & Lo, Hsiang-Yu, 2022. "Order Choices: An Intraday Analysis of the Taiwan Stock Exchange," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Ariel Lanza & Enrico Bernardini & Ivan Faiella, 2020. "Mind the gap! Machine learning, ESG metrics and sustainable investment," Questioni di Economia e Finanza (Occasional Papers) 561, Bank of Italy, Economic Research and International Relations Area.

    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:wly:ijfiec:v:24:y:2019:i:3:p:1170-1192. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.