IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v18y2018i8p1315-1326.html
   My bibliography  Save this article

Modelling fundamental analysis in portfolio selection

Author

Listed:
  • Huazhu Zhang
  • Cheng Yan

Abstract

We derive a closed-form appraisal/information ratio of the investors who are able to observe some information about security fundamentals, by solving a simple instantaneous mean-variance portfolio choice problem in a continuous-time framework. Both analytical and numerical results suggest that investors should choose securities with a more volatile mispricing, a less volatile fundamental, a higher mean-reverting speed and a larger dividend. Our model calibrated with realistic parameters easily outperforms top-percentile portfolio managers in reality, which suggests that the implementation of fundamental analysis may be impeded in practice due to limits of arbitrage. Our paper is a first, necessarily simple, step towards filling the gap of modelling fundamental analysis in portfolio selection.

Suggested Citation

  • Huazhu Zhang & Cheng Yan, 2018. "Modelling fundamental analysis in portfolio selection," Quantitative Finance, Taylor & Francis Journals, vol. 18(8), pages 1315-1326, August.
    • Handle: RePEc:taf:quantf:v:18:y:2018:i:8:p:1315-1326
    DOI: 10.1080/14697688.2017.1418520
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2017.1418520
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/14697688.2017.1418520?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. Xiang, Yun & He, Jiaxuan, 2022. "Pairs trading and asset pricing," Pacific-Basin Finance Journal, Elsevier, vol. 72(C).
    2. Pier Francesco Procacci & Tomaso Aste, 2018. "Forecasting market states," Papers 1807.05836, arXiv.org, revised May 2019.
    3. Ren, Xiaohang & Zhang, Xiao & Yan, Cheng & Gozgor, Giray, 2022. "Climate policy uncertainty and firm-level total factor productivity: Evidence from China," Energy Economics, Elsevier, vol. 113(C).
    4. D'Amico, Guglielmo & De Blasis, Riccardo, 2024. "Dividend based risk measures: A Markov chain approach," Applied Mathematics and Computation, Elsevier, vol. 471(C).
    5. Qinkai Chen, 2021. "Stock Movement Prediction with Financial News using Contextualized Embedding from BERT," Papers 2107.08721, arXiv.org.

    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:quantf:v:18:y:2018:i:8:p:1315-1326. 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/RQUF20 .

    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.