IDEAS home Printed from https://ideas.repec.org/a/aad/iseicj/v4y2016i0p229-234.html
   My bibliography  Save this article

Estimating The Hedge Ratios

Author

Listed:
  • Mária Bohdalová

    (Comenius University in Bratislava, Faculty of Management)

  • Michal Greguš

    (Comenius University in Bratislava, Faculty of Management)

Abstract

This paper examines the problem of hedging portfolio returns. Many practitioners and academicians endeavor to solve the problem of how to calculate the optimal hedge ratio accurately. In this paper we compare estimates of the hedge ratio from a classical approach of a linear quantile regression, based on selected quantiles as medians, with that of a non-linear quantile regression. To estimate the hedge ratios, we have used a calibrated Student t distribution for the marginal densities and a Student t copula of the portfolio returns using a maximum likelihood estimation. We created two portfolios of the assets, one for equal weight and another for optimal weight in respect of minimal risk. Our findings show that an assumption of Student t marginal leads to a better estimation of the hedge ratio.

Suggested Citation

  • Mária Bohdalová & Michal Greguš, 2016. "Estimating The Hedge Ratios," CBU International Conference Proceedings, ISE Research Institute, vol. 4(0), pages 229-234, September.
    • Handle: RePEc:aad:iseicj:v:4:y:2016:i:0:p:229-234
    DOI: 10.12955/cbup.v4.874
    as

    Download full text from publisher

    File URL: https://ojs.journals.cz/index.php/CBUIC/article/view/874/976
    Download Restriction: no
    File URL: https://libkey.io/10.12955/cbup.v4.874?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
    ---><---

    More about this item

    Keywords

    quantile regressionhedge ratio; copula;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:aad:iseicj:v:4:y:2016:i:0:p:229-234. 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: Petr Hájek (email available below). General contact details of provider: https://ojs.journals.cz/index.php/CBUIC .

    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.