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Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest

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  • Antonakakis, Nikolaos
  • Chatziantoniou, Ioannis
  • Filis, George

Abstract

In this study we examine the dynamic structural relationship between oil price shocks and stock market returns or volatility for a sample of both net oil–exporting and net oil–importing countries between 1995:09 and 2013:07. We accomplish that, by extending the Diebold and Yilmaz (2014) dynamic connectedness measure using structural forecast error variance decomposition. The results for both stock market returns and volatility suggest that connectedness varies across different time periods, and that this time–varying character is aligned with certain developments that take place in the global economy. In particular, aggregate demand shocks appear to act as the main transmitters of shocks to stock markets during periods characterised by economic–driven events, while supply–side and oil–specific demand shocks during periods of geopolitical unrest. Furthermore, differences regarding the directions and the strength of connectedness can be reported both between and within the net oil–importing and net oil–exporting countries. These results are of particular importance to investors and portfolio managers, given the recent financialisation of the oil market.

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  • Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
  • Handle: RePEc:eee:finana:v:50:y:2017:i:c:p:1-26
    DOI: 10.1016/j.irfa.2017.01.004
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    Cited by:

    1. Lina M. Cortés & Javier Perote & Andrés Mora-Valencia, 2017. "Implicit probability distribution for WTI options: The Black Scholes vs. the semi-nonparametric approach," DOCUMENTOS DE TRABAJO CIEF 015923, UNIVERSIDAD EAFIT.
    2. repec:eee:eneeco:v:68:y:2017:i:c:p:1-18 is not listed on IDEAS

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    Keywords

    Oil price shocks; Stock market; Connectedness; Structural Vector Autoregression; Geopolitical unrest; Economic crisis;

    JEL classification:

    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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