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Canonical vine copulas in the context of modern portfolio management: Are they worth it?

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  • Low, Rand Kwong Yew
  • Alcock, Jamie
  • Faff, Robert
  • Brailsford, Timothy

Abstract

In the context of managing downside correlations, we examine the use of multi-dimensional elliptical and asymmetric copula models to forecast returns for portfolios with 3–12 constituents. Our analysis assumes that investors have no short-sales constraints and a utility function characterized by the minimization of Conditional Value-at-Risk (CVaR). We examine the efficient frontiers produced by each model and focus on comparing two methods for incorporating scalable asymmetric dependence structures across asset returns using the Archimedean Clayton copula in an out-of-sample, long-run multi-period setting. For portfolios of higher dimensions, we find that modeling asymmetries within the marginals and the dependence structure with the Clayton canonical vine copula (CVC) consistently produces the highest-ranked outcomes across a range of statistical and economic metrics when compared to other models incorporating elliptical or symmetric dependence structures. Accordingly, we conclude that CVC copulas are ‘worth it’ when managing larger portfolios.

Suggested Citation

  • Low, Rand Kwong Yew & Alcock, Jamie & Faff, Robert & Brailsford, Timothy, 2013. "Canonical vine copulas in the context of modern portfolio management: Are they worth it?," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3085-3099.
  • Handle: RePEc:eee:jbfina:v:37:y:2013:i:8:p:3085-3099 DOI: 10.1016/j.jbankfin.2013.02.036
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    Cited by:

    1. Grover, Vaibhav, 2015. "Identifying Dependence Structure among Equities in Indian Markets using Copulas," MPRA Paper 66302, University Library of Munich, Germany.
    2. 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.
    3. Arreola Hernandez, Jose & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Al Janabi, Mazin A. M. & Reboredo, Juan Carlos, 2014. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," MPRA Paper 73399, University Library of Munich, Germany, revised Aug 2016.
    4. Mangold, Benedikt, 2017. "New concepts of symmetry for copulas," FAU Discussion Papers in Economics 06/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    5. Marcel Wollschlager & Rudi Schafer, 2015. "Impact of non-stationarity on estimating and modeling empirical copulas of daily stock returns," Papers 1506.08054, arXiv.org.
    6. David Walsh-Jones & Daniel Jones & Christoph Reisinger, 2014. "Modelling of dependence in high-dimensional financial time series by cluster-derived canonical vines," Papers 1411.4970, arXiv.org.
    7. repec:spr:empeco:v:53:y:2017:i:3:d:10.1007_s00181-016-1165-6 is not listed on IDEAS
    8. Al Janabi, Mazin A.M. & Arreola Hernandez, Jose & Berger, Theo & Nguyen, Duc Khuong, 2017. "Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1121-1131.
    9. repec:eee:touman:v:48:y:2015:i:c:p:268-282 is not listed on IDEAS
    10. Bekiros, Stelios & Hernandez, Jose Arreola & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2015. "Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios," Resources Policy, Elsevier, vol. 46(P2), pages 1-11.
    11. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    12. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2015. "Is volatility clustering of asset returns asymmetric?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 62-76.
    13. Humphrey, Jacquelyn E. & Benson, Karen L. & Low, Rand K.Y. & Lee, Wei-Lun, 2015. "Is diversification always optimal?," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 521-532.
    14. Reboredo, Juan C., 2015. "Is there dependence and systemic risk between oil and renewable energy stock prices?," Energy Economics, Elsevier, vol. 48(C), pages 32-45.
    15. Marwa Talbi & Rihab Bedoui & Lotfi Belkacem & Christian De Peretti, 2017. "Which Precious metal shines brightest for international investors? : A Vine Copula approach," Working Papers hal-01664146, HAL.
    16. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    17. Huang, Wanling & Mollick, André Varella & Nguyen, Khoa Huu, 2016. "U.S. stock markets and the role of real interest rates," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 231-242.
    18. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, Open Access Journal, vol. 4(4), pages 1-15, October.
    19. Stübinger, Johannes & Mangold, Benedikt & Krauss, Christopher, 2016. "Statistical arbitrage with vine copulas," FAU Discussion Papers in Economics 11/2016, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    20. repec:eee:eneeco:v:66:y:2017:i:c:p:493-507 is not listed on IDEAS

    More about this item

    Keywords

    Vine copula; Clayton copula; Asymmetric dependence; Portfolio management; Canonical vine; Conditional value-at-risk;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions

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