IDEAS home Printed from
   My bibliography  Save this article

Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures


  • Gatfaoui, Hayette


We build a portfolio encompassing U.S. crude oil, natural gas and stocks to study the diversification power of energy commodities. Such diversification power depends on the joint dependence structure of the three types of assets. According to Gatfaoui (2016a), the dependence structure is time-varying because individual asset returns exhibit several variance regimes. We identify the corresponding regime-specific multivariate copulas, and incorporate them to well-chosen risk measures. Specifically, we minimize the portfolio's variance, semi-variance and tail risk, in the presence and the absence of constraints on the portfolio's expected return and/or stock investment. First, the return constraint reduces the performance of the optimal portfolio. Second, the regime-specific portfolio optimization implements an enhanced active management strategy over the whole sample period. Finally, the tail-risk optimal portfolio offers the most interesting risk-return tradeoff. However, variance and semi-variance optimal portfolios can also be considered in the absence of a return constraint.

Suggested Citation

  • Gatfaoui, Hayette, 2019. "Diversifying portfolios of U.S. stocks with crude oil and natural gas: A regime-dependent optimization with several risk measures," Energy Economics, Elsevier, vol. 80(C), pages 132-152.
  • Handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:132-152
    DOI: 10.1016/j.eneco.2018.12.013

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

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

    More about this item


    Copula; Energy commodity; Portfolio optimization; Stock market; Tail risk;

    JEL classification:

    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions


    Access and download statistics


    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:eee:eneeco:v:80:y:2019:i:c:p:132-152. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.