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Investigating the leverage effect in commodity markets with a recursive estimation approach

Listed author(s):
  • Chevallier, Julien
  • Ielpo, Florian

This paper investigates the presence of the leverage effect in commodities, in comparison with financial markets. The EGARCH model with a Mixture of Normals distribution (EGARCH-MN) is used to capture (i) heavy tails and skewness in the conditional returns, and (ii) leverage effects and time-varying long-term component in the volatility specification. Besides, the estimation strategy relies on an innovative recursive (REC) method, which allows disentangling the leverage effect from the unconditional skewness as an empirical result. When applied to a broadly diversified dataset of assets during 1995–2012, the EGARCH-MN models offers state-of-the-art specifications with leverage and fat-tailed skewed densities, that allow to contrast the specific characteristics of commodities with traditional assets (equities, bonds, FX).

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File URL: http://www.sciencedirect.com/science/article/pii/S0275531914000543
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Article provided by Elsevier in its journal Research in International Business and Finance.

Volume (Year): 39 (2017)
Issue (Month): PB ()
Pages: 763-778

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Handle: RePEc:eee:riibaf:v:39:y:2017:i:pb:p:763-778
DOI: 10.1016/j.ribaf.2014.09.010
Contact details of provider: Web page: http://www.elsevier.com/locate/ribaf

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