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Commodity volatility shocks and BRIC sovereign risk: A GARCH-quantile approach

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  • Bouri, Elie
  • Jalkh, Naji
  • Roubaud, David

Abstract

We study whether the contemporaneous and lagged volatility of the commodity/energy markets can help predict the volatility of Brazil, Russia, India, China (BRIC) sovereign risk in the quantiles. We first define the latent volatility using Generalized Autoregressive Conditional Heteroscedasticity (GARCH) specifications and then use it within a quantile-based regression augmented with a dichotomous variable identifying the periods before and after the mid-2014 energy price decline. The analysis on daily data from January 4, 2010 to August 31, 2016 provides evidence that the volatility relation between commodity/energy and sovereign Credit Default Swap (CDS) markets is not the same under different volatility conditions, although energy volatility is slightly more important than commodity volatility. Importantly, the volatility of commodity/energy markets shapes sovereign risk in middle and upper volatility quantiles of commodities/energy exporters (Brazil and Russia). While in commodities/energy importers, such as China, predictability is only significant in upper volatility quantiles. Notably, we reveal the importance of the mid-2014 energy price decline for the volatility dynamics of BRIC sovereign risk; after the mid-2014, the volatility of the sovereign risk has increased in Brazil and Russia, while it has decreased in India. Finally, we recommend adoption of measures to reduce commodity and energy dependency.

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  • Bouri, Elie & Jalkh, Naji & Roubaud, David, 2019. "Commodity volatility shocks and BRIC sovereign risk: A GARCH-quantile approach," Resources Policy, Elsevier, vol. 61(C), pages 385-392.
  • Handle: RePEc:eee:jrpoli:v:61:y:2019:i:c:p:385-392
    DOI: 10.1016/j.resourpol.2017.12.002
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    More about this item

    Keywords

    C10; G10; Q02; Q40; Volatility transmission; Energy commodities; Sovereign CDS; BRIC; Quantile regression;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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