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Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks

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  • Hammoudeh, Shawkat
  • Araújo Santos, Paulo
  • Al-Hassan, Abdullah

Abstract

Value-at-Risk (VaR) is used to analyze the market downside risk associated with investments in six key individual assets including four precious metals, oil and the S&P 500 index, and three diversified portfolios. Using combinations of these assets, three optimal portfolios and their efficient frontiers within a VaR framework are constructed and the returns and downside risks for these portfolios are also analyzed. One-day-ahead VaR forecasts are computed with nine risk models including calibrated RiskMetrics, asymmetric GARCH type models, the filtered Historical Simulation approach, methodologies from statistics of extremes and a risk management strategy involving combinations of models. These risk models are evaluated and compared based on the unconditional coverage, independence and conditional coverage criteria. The economic importance of the results is also highlighted by assessing the daily capital charges under the Basel Accord rule. The best approaches for estimating the VaR for the individual assets under study and for the three VaR-based optimal portfolios and efficient frontiers are discussed. The VaR-based performance measure ranks the most diversified optimal portfolio (Portfolio #2) as the most efficient and the pure precious metals (Portfolio #1) as the least efficient.

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Bibliographic Info

Article provided by Elsevier in its journal The North American Journal of Economics and Finance.

Volume (Year): 25 (2013)
Issue (Month): C ()
Pages: 318-334

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Handle: RePEc:eee:ecofin:v:25:y:2013:i:c:p:318-334

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Web page: http://www.elsevier.com/locate/inca/620163

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Keywords: Key assets; Value-at-Risk; Optimal portfolios; Efficient frontiers; Risk management;

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References

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Citations

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Cited by:
  1. Shawkat Hammoudeh & Michael McAleer, 2012. "Risk Management and Financial Derivatives: An Overview," Working Papers in Economics 12/10, University of Canterbury, Department of Economics and Finance.
  2. Mohamed El Hedi Arouri & Shawkat Hammoudeh & Duc Khuong Nguyen & Amine Lahiani, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Working Papers hal-00798036, HAL.
  3. Chia-Lin Chang & Hui-Kuang Hsu & Michael McAleer, 2013. "The Impact of China on Stock Returns and Volatility in the Taiwan Tourism Industry," Documentos de Trabajo del ICAE 2013-30, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Aug 2013.
  4. Mihaela NICOLAU & Giulio PALOMBA & Ilaria TRAINI, 2013. "Are Futures Prices Influenced by Spot;Prices or Vice-versa? An Analysis of Crude;Oil, Natural Gas and Gold Markets," Working Papers 394, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  5. Gustavo A. Marrero & Luis A. Puch & Francisco J. Ramos-Real, 2013. "Mean-variance portfolio methods for energy policy risk management," Documentos de Trabajo del ICAE 2013-41, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  6. Araújo Santos, Paulo & Fraga Alves, Isabel & Hammoudeh, Shawkat, 2013. "High quantiles estimation with Quasi-PORT and DPOT: An application to value-at-risk for financial variables," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 487-496.

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