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Measurement of Volatility Spillovers and Asymmetric Connectedness on Commodity and Equity Markets

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  • Tereza Palanska

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic)

Abstract

We study volatility spillovers among commodity and equity markets by employing a recently developed approach based on realized measures and forecast error variance decomposition invariant to the variable ordering from vector-autoregressions. This enables us to measure total, directional and net volatility spillovers as well as the asymmetry of responses to positive and negative shocks. We exploit high-frequency data on the prices of Crude oil, Corn, Cotton and Gold futures, and the S&P 500 Index and use a sample which spans from January 2002 to December 2015 to cover the entire period around the global financial crisis of 2008. Our empirical analysis reveals that on average, the volatility shocks related to other markets account for around one fifth of the volatility forecast error variance. We find that shocks to the stock markets play the most important role as the S&P 500 Index dominates all commodities in terms of general volatility spillover transmission. Our results further suggest that volatility spillovers across the analyzed assets were rather limited before the global financial crisis, which then boosted the connectedness between commodity and stock markets. Furthermore, the volatility due to positive and negative shocks is transmitted between markets at different magnitudes and the prevailing effect has varied. In the pre-crisis period, the positive spillovers dominated the negative ones, however, in several years following the crisis, the negative shocks have had a significantly higher impact on the volatility spillovers across the markets, pointing to an overall increase in uncertainty in the commodity and equity markets following a major crisis. In recent years, the asymmetric measures seem to have returned to their pre-crises directions and magnitudes.

Suggested Citation

  • Tereza Palanska, 2018. "Measurement of Volatility Spillovers and Asymmetric Connectedness on Commodity and Equity Markets," Working Papers IES 2018/27, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2018.
  • Handle: RePEc:fau:wpaper:wp2018_27
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    File URL: http://ies.fsv.cuni.cz/sci/publication/show/id/5886/lang/cs
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    Cited by:

    1. Dejan Živkov & Boris Kuzman & Jonel Subić, 2022. "Measuring the risk-adjusted performance of selected soft agricultural commodities," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(3), pages 87-96.
    2. Shah, Adil Ahmad & Dar, Arif Billah, 2021. "Exploring diversification opportunities across commodities and financial markets: Evidence from time-frequency based spillovers," Resources Policy, Elsevier, vol. 74(C).
    3. Zaghum Umar & Oluwasegun Babatunde Adekoya & Mariya Gubareva & Sabri Boubaker, 2024. "Returns and volatility connectedness among the Eurozone equity markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3103-3122, July.
    4. Liu, Pan & Power, Gabriel J. & Vedenov, Dmitry, 2021. "Fair-weather Friends? Sector-specific volatility connectedness and transmission," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 712-736.
    5. Walid Abass Mohammed, 2021. "Volatility Spillovers among Developed and Developing Countries: The Global Foreign Exchange Markets," JRFM, MDPI, vol. 14(6), pages 1-30, June.
    6. Garcia-Jorcano, Laura & Sanchis-Marco, Lidia, 2022. "Spillover effects between commodity and stock markets: A SDSES approach," Resources Policy, Elsevier, vol. 79(C).
    7. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    8. Dejan Živkov & Suzana Balaban & Marijana Joksimović, 2022. "Making a Markowitz portfolio with agricultural commodity futures," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(6), pages 219-229.

    More about this item

    Keywords

    Volatility; Spillovers; Relized Semivariance; Asymmetric effects; Commodity markets; Equity markets;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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