IDEAS home Printed from https://ideas.repec.org/p/rie/riecdt/46.html
   My bibliography  Save this paper

Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets

Author

Listed:
  • Gomez-Gonzalez, Jose Eduardo
  • Hirs-Garzon, Jorge
  • Uribe, Jorge M.

Abstract

We explore the higher order linkages between energy commodity markets and global financial markets. Our focus is on spillovers of realized good and bad volatilities, realized signed jump variation, realized skewness and realized kurtosis. Our results show that the measurement of risk spillovers is sensitive to the definition of risk used in their construction. Asymmetries between good and bad volatility transmission matter, and results when jumps and higher order risk measures are considered are substantially different from those obtained when traditional volatility measures are used. We provide empirical support for theoretical asset pricing models that conduct the optimization required for portfolio balancing in the mean-variance-skewness space by showing that risk diversification opportunities vary greatly when one considers variance or skewness as the fundamental proxy for risk.

Suggested Citation

  • Gomez-Gonzalez, Jose Eduardo & Hirs-Garzon, Jorge & Uribe, Jorge M., 2020. "Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets," Working papers 46, Red Investigadores de Economía.
  • Handle: RePEc:rie:riecdt:46
    as

    Download full text from publisher

    File URL: http://repositorio.redinvestigadores.org/bitstream/handle/Riec/67/Draft%20%20May%2010%202020.pdf?sequence=1&isAllowed=y
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Walter Briec & Kristiaan Kerstens & Octave Jokung, 2007. "Mean-Variance-Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach," Management Science, INFORMS, vol. 53(1), pages 135-149, January.
    2. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. 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.
    4. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    5. 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.
    6. Jérôme Lahaye & Sébastien Laurent & Christopher J. Neely, 2011. "Jumps, cojumps and macro announcements," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 893-921, September.
    7. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    8. Andersen, Torben G. & Bollerslev, Tim & Meddahi, Nour, 2011. "Realized volatility forecasting and market microstructure noise," Journal of Econometrics, Elsevier, vol. 160(1), pages 220-234, January.
    9. Briec, Walter & Kerstens, Kristiaan, 2010. "Portfolio selection in multidimensional general and partial moment space," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 636-656, April.
    10. Xavier Gabaix, 2012. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 645-700.
    11. Trautmann, Stefan T. & Kuilen, Gijs van de, 2018. "Higher order risk attitudes: A review of experimental evidence," European Economic Review, Elsevier, vol. 103(C), pages 108-124.
    12. Robert J. Barro, 2006. "Rare Disasters and Asset Markets in the Twentieth Century," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(3), pages 823-866.
    13. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    14. 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.
    15. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    16. Geman, Hélyette & Kharoubi, Cécile, 2008. "WTI crude oil Futures in portfolio diversification: The time-to-maturity effect," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2553-2559, December.
    17. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    18. Jose E. Gomez‐Gonzalez & Jorge Hirs‐Garzon & Jorge M. Uribe, 2020. "Giving and receiving: Exploring the predictive causality between oil prices and exchange rates," International Finance, Wiley Blackwell, vol. 23(1), pages 175-194, March.
    19. Wen, Xiaoqian & Wei, Yu & Huang, Dengshi, 2012. "Measuring contagion between energy market and stock market during financial crisis: A copula approach," Energy Economics, Elsevier, vol. 34(5), pages 1435-1446.
    20. 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.
    21. Itamar Drechsler, 2013. "Uncertainty, Time-Varying Fear, and Asset Prices," Journal of Finance, American Finance Association, vol. 68(5), pages 1843-1889, October.
    22. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    23. Jakša Cvitanić & Vassilis Polimenis & Fernando Zapatero, 2008. "Optimal portfolio allocation with higher moments," Annals of Finance, Springer, vol. 4(1), pages 1-28, January.
    24. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    25. Mathieu Jacomy & Tommaso Venturini & Sebastien Heymann & Mathieu Bastian, 2014. "ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-12, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Uribe, Jorge M., 2022. "Spillovers beyond the variance: Exploring the higher order risk linkages between commodity markets and global financial markets," Journal of Commodity Markets, Elsevier, vol. 28(C).
    2. Gomez-Gonzalez, Jose E. & Hirs-Garzon, Jorge & Gamboa-Arbelaez, Juliana, 2020. "Dynamic relations between oil and stock market returns: A multi-country study," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    3. Gomez-Gonzalez, Jose E. & Hirs-Garzón, Jorge & Sanín-Restrepo, Sebastián, 2021. "Dynamic relations between oil and stock markets: Volatility spillovers, networks and causality," International Economics, Elsevier, vol. 165(C), pages 37-50.
    4. Cheng, Tingting & Liu, Junli & Yao, Wenying & Zhao, Albert Bo, 2022. "The impact of COVID-19 pandemic on the volatility connectedness network of global stock market," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    5. Shi Chen & Wolfgang Karl Hardle & Brenda L'opez Cabrera, 2020. "Regularization Approach for Network Modeling of German Power Derivative Market," Papers 2009.09739, arXiv.org.
    6. Feng, Huiqun & Zhang, Jun & Guo, Na, 2023. "Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors," International Review of Financial Analysis, Elsevier, vol. 89(C).
    7. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    8. Okorie, David Iheke & Lin, Boqiang, 2022. "Givers never lack: Nigerian oil & gas asymmetric network analyses," Energy Economics, Elsevier, vol. 108(C).
    9. Stenfors, Alexis & Chatziantoniou, Ioannis & Gabauer, David, 2022. "Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    10. Li, Hailing & Pei, Xiaoyun & Yang, Yimin & Zhang, Hua, 2024. "Assessing the impact of energy-related uncertainty on G20 stock market returns: A decomposed contemporaneous and lagged R2 connectedness approach," Energy Economics, Elsevier, vol. 132(C).
    11. Mensi, Walid & Ziadat, Salem Adel & Rababa'a, Abdel Razzaq Al & Vo, Xuan Vinh & Kang, Sang Hoon, 2024. "Oil, gold and international stock markets: Extreme spillovers, connectedness and its determinants," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 1-17.
    12. Cui, Jinxin & Maghyereh, Aktham & Goh, Mark & Zou, Huiwen, 2022. "Risk spillovers and time-varying links between international oil and China’s commodity futures markets: Fresh evidence from the higher-order moments," Energy, Elsevier, vol. 238(PB).
    13. Amar, Amine Ben & Goutte, Stéphane & Isleimeyyeh, Mohammad & Benkraiem, Ramzi, 2022. "Commodity markets dynamics: What do cross-commodities over different nearest-to-maturities tell us?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    14. Bostanci, Gorkem & Yilmaz, Kamil, 2020. "How connected is the global sovereign credit risk network?," Journal of Banking & Finance, Elsevier, vol. 113(C).
    15. Jiasha Fu & Hui Qiao, 2022. "The Time-Varying Connectedness Between China’s Crude Oil Futures and International Oil Markets: A Return and Volatility Spillover Analysis," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 341-376, December.
    16. Wang, Gang-Jin & Xie, Chi & Zhao, Longfeng & Jiang, Zhi-Qiang, 2018. "Volatility connectedness in the Chinese banking system: Do state-owned commercial banks contribute more?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 205-230.
    17. Matteo Foglia & Vasilios Plakandaras & Rangan Gupta & Elie Bouri, 2023. "Multi-Layer Spillovers between Volatility and Skewness in International Stock Markets Over a Century of Data: The Role of Disaster Risks," Working Papers 202337, University of Pretoria, Department of Economics.
    18. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    19. Hassan, Kamrul & Hoque, Ariful & Gasbarro, Dominic, 2019. "Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis," Energy Economics, Elsevier, vol. 80(C), pages 950-969.
    20. Yi, Shuyue & Xu, Zishuang & Wang, Gang-Jin, 2018. "Volatility connectedness in the cryptocurrency market: Is Bitcoin a dominant cryptocurrency?," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 98-114.

    More about this item

    Keywords

    Energy commodity markets; Risk spillover; Higher order risk measure; LASSO methods;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rie:riecdt:46. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CAIE (email available below). General contact details of provider: https://edirc.repec.org/data/redcoea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.