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The connectedness between crude oil and financial markets: Evidence from implied volatility indices

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  • Awartani, Basel
  • Aktham, Maghyereh
  • Cherif, Guermat

Abstract

In this paper we exploit newly introduced implied volatility indexes to investigate the directional risk transfer from oil to US equities, Euro/Dollar exchange rates, precious metals and agricultural commodities. We find significant volatility transmission from oil to equities but little transmission to agricultural commodities. The total pairwise directional connectedness to equities is around 20.4%, while it is only 1.6%, 1.0% and 2.0% to wheat, corn, and soybeans respectively. The risk spillover from oil to precious metals and Euro/Dollar foreign exchange rates is moderate. For instance, the oil market uncertainty spills 11.0%, 11.1% and 8.9% to gold, silver and Euro/Dollar exchange rate respectively. The volatility crossover from all of these markets to oil is tiny, implying that oil is the main driver of its association with these markets. Finally, we provide evidence that the transmission from oil to other markets has increased since the collapse of oil prices in July 2014.

Suggested Citation

  • Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    • Handle: RePEc:eee:jocoma:v:4:y:2016:i:1:p:56-69
    DOI: 10.1016/j.jcomm.2016.11.002
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    More about this item

    Keywords

    Oil price volatility; Equity volatility; directional connectedness; Implied volatility;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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