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Dynamic relations between oil and stock markets: Volatility spillovers, networks and causality


  • Jose Eduardo Gomez-Gonzalez

    () (Banco de la República de Colombia)

  • Jorge Hirs-Garzon

    () (Universidad del Valle, Colombia)

  • Sebastian Sanin-Restrepo

    () (Banco de la República de Colombia)


We study the relation between oil and stock market returns for a set of seven countries that are important participants in commodity markets. Total and directional spillover indicators are computed using forecast error variance decomposition from vector autoregressions, and their dynamic nature is explored. We find that, on average, oil markets are net volatility receptors while the stock markets of Norway and the US are the main volatility trasmitters. However, transmission intensities and net positions present considerable time variation, being substantially different in moments of financial distress with respect to normal times. Furthermore, we perform dynamic Granger causality tests on recursive windows to explore the validity of the exogeneity assumption of oil market shocks frequently made in the literature. Our results show the existence of bidirectional causality relations, being stronger from stock to oil markets. The results of this study provide empirical evidence suggesting the validity of the oil markets financialization hypothesis, and have important implications for global investors and policymakers. **** RESUMEN: Se estudia la relación entre los retornos de los mercados petroleros y los mercados accionarios de siete países que son participantes importantes de los mercados de bienes básicos. Se computan indicadores totales y direccionales de transmisión de volatilidad usando métodos de descomposición de la varianza del error de pronóstico de vectores auto-regresivos y se explora su dinámica. Se encuentra que, en promedio, los mercados de petróleo son receptores netos de volatilidad mientras que los mercados accionarios de Noruega y de los Estados Unidos son los principales transmisores de la misma. Sin embargo, las intensidades de transmisión y las posiciones netas exhiben importante variación temporal, siendo sustancialmente diferentes en momentos de tensión financiera frente a momentos de tranquilidad en los mercados. Adicionalmente, se realizan pruebas de causalidad en sentido de Granger dinámicas en ventanas recursivas para probar la validez de los supuestos de exogeneidad de los choques a los mercados petroleros que se hacen de forma frecuente en la literatura. Los resultados muestran que existen relaciones de causalidad bidireccionales, que son más fuertes de los mercados accionarios hacia el petróleo que viceversa. Los resultados de este estudio proveen evidencia empírica que sugiere la validez de la hipótesis de financiarización de los mercados de petróleo y tienen implicaciones importantes para los inversionistas globales y para los hacedores de política.

Suggested Citation

  • Jose Eduardo Gomez-Gonzalez & Jorge Hirs-Garzon & Sebastian Sanin-Restrepo, 2018. "Dynamic relations between oil and stock markets: Volatility spillovers, networks and causality," Borradores de Economia 1051, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:1051

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    References listed on IDEAS

    1. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    2. Lee, Bi-Juan & Yang, Chin Wei & Huang, Bwo-Nung, 2012. "Oil price movements and stock markets revisited: A case of sector stock price indexes in the G-7 countries," Energy Economics, Elsevier, vol. 34(5), pages 1284-1300.
    3. Bedoui, Rihab & Braeik, Sana & Goutte, Stéphane & Guesmi, Khaled, 2018. "On the study of conditional dependence structure between oil, gold and USD exchange rates," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 134-146.
    4. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    5. Gamba-Santamaria, Santiago & Gomez-Gonzalez, Jose Eduardo & Hurtado-Guarin, Jorge Luis & Melo-Velandia, Luis Fernando, 2017. "Stock market volatility spillovers: Evidence for Latin America," Finance Research Letters, Elsevier, vol. 20(C), pages 207-216.
    6. Diaz, Elena Maria & Molero, Juan Carlos & Perez de Gracia, Fernando, 2016. "Oil price volatility and stock returns in the G7 economies," Energy Economics, Elsevier, vol. 54(C), pages 417-430.
    7. Suleyman Basak & Anna Pavlova, 2016. "A Model of Financialization of Commodities," Journal of Finance, American Finance Association, vol. 71(4), pages 1511-1556, August.
    8. Boldanov, Rustam & Degiannakis, Stavros & Filis, George, 2016. "Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 209-220.
    9. repec:eee:ecmode:v:67:y:2017:i:c:p:184-192 is not listed on IDEAS
    10. Ding, Haoyuan & Kim, Hyung-Gun & Park, Sung Y., 2016. "Crude oil and stock markets: Causal relationships in tails?," Energy Economics, Elsevier, vol. 59(C), pages 58-69.
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    More about this item


    Time-varying causality; Oil price; Stock market returns; Emerging market economies; Causalidad variable en el tiempo; Precios del petróleo; Retornos de mercados accionarios; Economías emergentes.;

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes


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