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Are oil and gas stocks from the Australian market riskier than coal and uranium stocks? Dependence risk analysis and portfolio optimization

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  • Arreola Hernandez, Jose

Abstract

This article models the dependence risk and resource allocation characteristics of two 20-stock coal–uranium and oil–gas sector portfolios from the Australian market in the context of the global financial crisis of 2008–2009. The modeling framework implemented consists of pair vine copulas and, linear and nonlinear portfolio optimization methods with respect to five risk measures. The paper's objectives are to find out if the oil and gas stocks are riskier than the coal and uranium stocks, to identify the optimization method and risk measure that produce the best risk-return trade-off, to recognize the stocks in which the optimal weight allocations converge on average, and to acknowledge the vine copula model that best accounts for the overall dependence of the energy portfolios. The research findings indicate that the oil stocks have higher dependence risk than the coal, uranium and gas stocks in financial crisis periods. The higher risk of the oil stocks is confirmed by the larger concentration of symmetric and asymmetric dependence they have in the negative tail. The canonical vine (c-vine) copula model is observed to better capture the overall dependence of the energy portfolios. The combination of a pair c-vine copula and nonlinear portfolio optimization produces the highest return relative to risk. The optimal weight allocations converge on average in some stocks.

Suggested Citation

  • Arreola Hernandez, Jose, 2014. "Are oil and gas stocks from the Australian market riskier than coal and uranium stocks? Dependence risk analysis and portfolio optimization," Energy Economics, Elsevier, vol. 45(C), pages 528-536.
  • Handle: RePEc:eee:eneeco:v:45:y:2014:i:c:p:528-536
    DOI: 10.1016/j.eneco.2014.08.015
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    References listed on IDEAS

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    More about this item

    Keywords

    Energy stocks; C-vines; D-vines; Dependence structure; Risk measures; Portfolio optimization;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G1 - Financial Economics - - General Financial Markets

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