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Long memory and structural breaks in modeling the return and volatility dynamics of precious metals

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  • Mohamed El Hedi Arouri

    (EconomiX - CNRS : UMR7166 - Université Paris X - Paris Ouest Nanterre La Défense)

  • Shawkat Hammoudeh

    (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II)

  • Amine Lahiani

    (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans)

  • Duc Khuong Nguyen

    (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II)

Abstract

We investigate the potential of structural changes and long memory (LM) properties in returns and volatility of the four major precious metal commodities traded on the COMEX markets (gold, silver, platinum and palladium). Broadly speaking, a random variable is said to exhibit long memory behavior if its autocorrelation function is not integrable, while structural changes can induce sudden and significant shifts in the time-series behavior of that variable. The results from implementing several parametric and semiparametric methods indicate strong evidence of long range dependence in the daily conditional return and volatility processes for the precious metals. Moreover, for most of the precious metals considered, this dual long memory is found to be adequately captured by an ARFIMA-FIGARCH model, which also provides better out-of-sample forecast accuracy than several popular volatility models. Finally, evidence shows that conditional volatility of precious metals is better explained by long memory than by structural breaks.

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Paper provided by HAL in its series Working Papers with number hal-00798033.

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Date of creation: 07 Mar 2013
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Handle: RePEc:hal:wpaper:hal-00798033

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Cited by:
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  2. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Working Papers, Department of Research, Ipag Business School 2014-325, Department of Research, Ipag Business School.
  3. Walid Chkili & Shawkat Hammoudeh & Duc Khuong Nguyen, 2013. "Long memory and asymmetry in the volatility of commodity markets and Basel Accord: choosing between models," Working Papers, Department of Research, Ipag Business School 2013-009, Department of Research, Ipag Business School.
  4. Mohamed El Hedi Arouri & Amine Lahiani & Duc Khuong Nguyen, 2014. "World gold prices and stock returns in China: insights for hedging and diversification strategies," Working Papers, Department of Research, Ipag Business School 2014-110, Department of Research, Ipag Business School.
  5. Amélie Charles & Olivier Darné & Jae H. Kim, 2014. "Precious metals shine? A market efficiency perspective," Working Papers hal-01010516, HAL.
  6. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process," Energy Economics, Elsevier, Elsevier, vol. 42(C), pages 343-354.
  7. Sinha, Pankaj & Mathur, Kritika, 2013. "A study on the Price Behavior of Base Metals traded in India," MPRA Paper 47028, University Library of Munich, Germany.
  8. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
  9. repec:ipg:wpaper:9 is not listed on IDEAS
  10. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, Elsevier, vol. 30(C), pages 101-119.
  11. Brooks, Chris & Prokopczuk, Marcel & Wu, Yingying, 2013. "Commodity futures prices: More evidence on forecast power, risk premia and the theory of storage," The Quarterly Review of Economics and Finance, Elsevier, Elsevier, vol. 53(1), pages 73-85.
  12. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Value-at-risk Predictions of Precious Metals with Long Memory Volatility Models," MPRA Paper 53229, University Library of Munich, Germany.

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