Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach
AbstractWe study the conditional dependence structure between crude oil prices and U.S. dollar exchange rates using a copula-GARCH approach. Various copula functions of the elliptical, Archimedean and quadratic families are used to model the underlying dependence structure in both bearish and bullish market phases. Over the 2000–2011 period, we find evidence of significant and symmetric dependence for almost all the oil-exchange rate pairs considered. The rise in the price of oil is found to be associated with the depreciation of the dollar. Moreover, we show that Student-t copulas best capture the extreme dependence, and that taking the extreme comovement into account leads to improve the accuracy of VaR forecasts. Our main results remain unchanged when considering alternative GARCH-type specifications and the crisis period, but are sensitive to the use of raw returns.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of International Money and Finance.
Volume (Year): 32 (2013)
Issue (Month): C ()
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Web page: http://www.elsevier.com/locate/inca/30443
Copulas; Dependence measures; Crude oil price; U.S. dollar exchange rates; CML method;
Other versions of this item:
- Riadh Aloui & Mohamed Safouane Ben Aïssa & Duc Khuong Nguyen, 2014. "Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach," Working Papers 2014-564, Department of Research, Ipag Business School.
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
- Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
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AMSE Working Papers
1421, Aix-Marseille School of Economics, Marseille, France, revised May 2014.
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