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Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach

Author

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  • Arreola Hernandez, Jose
  • Hammoudeh, Shawkat
  • Nguyen, Duc Khuong
  • Al Janabi, Mazin A. M.
  • Reboredo, Juan Carlos

Abstract

We use regular vine (r-vine), canonical vine (c-vine) and drawable vine (d-vine) copulas to examine the dependence risk characteristics of three 20-stock portfolios from the retail, manufacturing and gold-mining equity sectors of the Australian market in periods before, during and after the 2008-2009 global financial crisis (GFC). Our results indicate that the retail portfolio is less risky than the manufacturing counterpart in the crisis period, while the gold-mining portfolio is less risky than both the retail and manufacturing sector portfolios. Both the retail and gold stocks display a higher propensity to yield positively skewed returns in the crisis periods, contrary to the manufacturing stocks. The r-vine is found to best capture the multivariate dependence structure of the stocks in the retail and gold-mining portfolios, while the d-vine does it for the manufacturing stock portfolio. These findings could be used to develop dependence risk and investment risk-adjusted strategies for investment, rebalancing and hedging which more adequately account for the downside risk in various market conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:pra:mprapa:73399
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    References listed on IDEAS

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    16. 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.
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    Cited by:

    1. Hanif, Waqas & Mensi, Walid & Vo, Xuan Vinh & BenSaïda, Ahmed & Hernandez, Jose Arreola & Kang, Sang Hoon, 2023. "Dependence and risk management of portfolios of metals and agricultural commodity futures," Resources Policy, Elsevier, vol. 82(C).
    2. Hanif, Waqas & Arreola Hernandez, Jose & Sadorsky, Perry & Yoon, Seong-Min, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    3. Kamal, Elham & Bouri, Elie, 2023. "Dependence structure among rare earth and financial markets: A multiscale-vine copula approach," Resources Policy, Elsevier, vol. 83(C).
    4. Maziar Sahamkhadam & Andreas Stephan, 2023. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2139-2166, December.
    5. Tamara Teplova & Mikova Evgeniia & Qaiser Munir & Nataliya Pivnitskaya, 2023. "Black-Litterman model with copula-based views in mean-CVaR portfolio optimization framework with weight constraints," Economic Change and Restructuring, Springer, vol. 56(1), pages 515-535, February.
    6. Himchan Jeong & Dipak Dey, 2020. "Application of a Vine Copula for Multi-Line Insurance Reserving," Risks, MDPI, vol. 8(4), pages 1-23, October.
    7. Syed Jawad Hussain Shahzad & Naveed Raza & David Roubaud & Jose Arreola Hernandez & Stelios Bekiros, 2019. "Gold as Safe Haven for G-7 Stocks and Bonds: A Revisit," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 885-912, December.
    8. Magnolia Sosa Castro & Christian Bucio Pacheco & Héctor Eduardo Díaz Rodríguez, 2021. "Extreme Volatility Dependence in Exchange Rate," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 40(82), pages 25-55, February.
    9. Uddin, Gazi Salah & Hernandez, Jose Areola & Shahzad, Syed Jawad Hussain & Hedström, Axel, 2018. "Multivariate dependence and spillover effects across energy commodities and diversification potentials of carbon assets," Energy Economics, Elsevier, vol. 71(C), pages 35-46.
    10. Jose Arreola Hernandez & Mazin A.M. Al Janabi, 2020. "Forecasting of dependence, market, and investment risks of a global index portfolio," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 512-532, April.
    11. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
    12. Shahzad, Syed Jawad Hussain & Arreola-Hernandez, Jose & Bekiros, Stelios & Shahbaz, Muhammad & Kayani, Ghulam Mujtaba, 2018. "A systemic risk analysis of Islamic equity markets using vine copula and delta CoVaR modeling," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 56(C), pages 104-127.
    13. Noureddine Benlagha & Wael Hemrit, 2018. "The Dynamic and Dependence of Takaful and Conventional Stock Return Behaviours: Evidence from the Insurance Industry in Saudi Arabia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(4), pages 285-323, December.
    14. Zhikai Peng & Jinchuan Ke, 2022. "Spillover Effect of the Interaction between Fintech and the Real Economy Based on Tail Risk Dependent Structure Analysis," Sustainability, MDPI, vol. 14(13), pages 1-22, June.

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    More about this item

    Keywords

    vine copulas; risk analysis; dependence structure; retail and manufacturing stocks;
    All these keywords.

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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