IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v80y2019icp321-335.html
   My bibliography  Save this article

Feedback spillover dynamics of crude oil and global assets indicators: A system-wide network perspective

Author

Listed:
  • Singh, Vipul Kumar
  • Kumar, Pawan
  • Nishant, Shreyank

Abstract

Crude oil, the critical driver of the world economy, is quick to be blamed for causing volatility in all classes of assets, viz. equity, commodities, bonds, and currencies. The feedback mechanism between crude oil and these four asset classes makes the volatility spillover connectedness dynamics more complex and an important area to explore. Henceforth, we quantify and analyze the time-varying system-wide volatility spillover connectedness dynamics of crude oil and global asset indicators (GAIs) covering four major asset classes for the period from 2000 to 2016. Additionally, we have used the confluence of generalized error variance decomposition (GEVD) and network diagrams. According to the findings of this paper, crude oil is affected more by the GAIs than vice versa, thus making the crude oil price more vulnerable to volatility fluctuations in GAIs. On a pairwise basis, the study finds that commodities and currency are more tightly knit to crude oil, with CADUSD and gold being more sensitive to crude oil price fluctuations. In addition, the equity indices of the US and the UK have become more sensitive to crude oil price volatility following the GFC. The study opens future discourse for portfolio managers and policymakers to explore the spillover pattern and act accordingly by mitigating risk via the compensatory mechanism of positive/negative spillover pairs.

Suggested Citation

  • Singh, Vipul Kumar & Kumar, Pawan & Nishant, Shreyank, 2019. "Feedback spillover dynamics of crude oil and global assets indicators: A system-wide network perspective," Energy Economics, Elsevier, vol. 80(C), pages 321-335.
    • Handle: RePEc:eee:eneeco:v:80:y:2019:i:c:p:321-335
    DOI: 10.1016/j.eneco.2019.01.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319300209
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2019.01.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hamilton, James D., 1996. "This is what happened to the oil price-macroeconomy relationship," Journal of Monetary Economics, Elsevier, vol. 38(2), pages 215-220, October.
    2. 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.
    3. Restrepo, Natalia & Uribe, Jorge M. & Manotas, Diego, 2018. "Financial risk network architecture of energy firms," Applied Energy, Elsevier, vol. 215(C), pages 630-642.
    4. Yu, Jia-Wei & Xie, Wen-Jie & Jiang, Zhi-Qiang, 2018. "Early warning model based on correlated networks in global crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1335-1343.
    5. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Post-Print hal-01474252, HAL.
    6. Jan J. J. Groen & Paolo A. Pesenti, 2011. "Commodity Prices, Commodity Currencies, and Global Economic Developments," NBER Chapters, in: Commodity Prices and Markets, pages 15-42, National Bureau of Economic Research, Inc.
    7. Mensi, Walid & Hammoudeh, Shawkat & Al-Jarrah, Idries Mohammad Wanas & Sensoy, Ahmet & Kang, Sang Hoon, 2017. "Dynamic risk spillovers between gold, oil prices and conventional, sustainability and Islamic equity aggregates and sectors with portfolio implications," Energy Economics, Elsevier, vol. 67(C), pages 454-475.
    8. Kang, Wensheng & Ratti, Ronald A. & Yoon, Kyung Hwan, 2014. "The impact of oil price shocks on U.S. bond market returns," Energy Economics, Elsevier, vol. 44(C), pages 248-258.
    9. Richards, Anthony J., 1995. "Comovements in national stock market returns: Evidence of predictability, but not cointegration," Journal of Monetary Economics, Elsevier, vol. 36(3), pages 631-654, December.
    10. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 31-67.
    11. Tian, Shuairu & Hamori, Shigeyuki, 2016. "Time-varying price shock transmission and volatility spillover in foreign exchange, bond, equity, and commodity markets: Evidence from the United States," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 163-171.
    12. Ben S. Bernanke & Mark Gertler & Mark Watson, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 28(1), pages 91-157.
    13. Wang, Yu Shan & Chueh, Yen Ling, 2013. "Dynamic transmission effects between the interest rate, the US dollar, and gold and crude oil prices," Economic Modelling, Elsevier, vol. 30(C), pages 792-798.
    14. Roger D. Huang & Ronald W. Masulis & Hans R. Stoll, 1996. "Energy shocks and financial markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(1), pages 1-27, February.
    15. 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.
    16. Lizardo, Radhamés A. & Mollick, André V., 2010. "Oil price fluctuations and U.S. dollar exchange rates," Energy Economics, Elsevier, vol. 32(2), pages 399-408, March.
    17. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    18. Nandha, Mohan & Hammoudeh, Shawkat, 2007. "Systematic risk, and oil price and exchange rate sensitivities in Asia-Pacific stock markets," Research in International Business and Finance, Elsevier, vol. 21(2), pages 326-341, June.
    19. Ji, Qiang & Bouri, Elie & Roubaud, David, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 1-12.
    20. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    21. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    22. Singh, Vipul Kumar & Nishant, Shreyank & Kumar, Pawan, 2018. "Dynamic and directional network connectedness of crude oil and currencies: Evidence from implied volatility," Energy Economics, Elsevier, vol. 76(C), pages 48-63.
    23. Charlot, Philippe & Marimoutou, Vêlayoudom, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Energy Economics, Elsevier, vol. 44(C), pages 456-467.
    24. Nazlioglu, Saban & Erdem, Cumhur & Soytas, Ugur, 2013. "Volatility spillover between oil and agricultural commodity markets," Energy Economics, Elsevier, vol. 36(C), pages 658-665.
    25. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    26. Nadal, Raquel & Szklo, Alexandre & Lucena, André, 2017. "Time-varying impacts of demand and supply oil shocks on correlations between crude oil prices and stock markets indices," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1011-1020.
    27. Akram, Q. Farooq, 2009. "Commodity prices, interest rates and the dollar," Energy Economics, Elsevier, vol. 31(6), pages 838-851, November.
    28. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2015. "Regional and global spillovers and diversification opportunities in the GCC equity sectors," Emerging Markets Review, Elsevier, vol. 24(C), pages 160-187.
    29. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    30. 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.
    31. Zhang, Yue-Jun & Fan, Ying & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Spillover effect of US dollar exchange rate on oil prices," Journal of Policy Modeling, Elsevier, vol. 30(6), pages 973-991.
    32. Chen, Peng, 2015. "Global oil prices, macroeconomic fundamentals and China's commodity sector comovements," Energy Policy, Elsevier, vol. 87(C), pages 284-294.
    33. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    34. Le, Thai-Ha & Chang, Youngho, 2015. "Effects of oil price shocks on the stock market performance: Do nature of shocks and economies matter?," Energy Economics, Elsevier, vol. 51(C), pages 261-274.
    35. Nazlioglu, Saban & Soytas, Ugur, 2012. "Oil price, agricultural commodity prices, and the dollar: A panel cointegration and causality analysis," Energy Economics, Elsevier, vol. 34(4), pages 1098-1104.
    36. Maghyereh, Aktham I. & Awartani, Basel & Tziogkidis, Panagiotis, 2017. "Volatility spillovers and cross-hedging between gold, oil and equities: Evidence from the Gulf Cooperation Council countries," Energy Economics, Elsevier, vol. 68(C), pages 440-453.
    37. Mensi, Walid & Tiwari, Aviral & Bouri, Elie & Roubaud, David & Al-Yahyaee, Khamis H., 2017. "The dependence structure across oil, wheat, and corn: A wavelet-based copula approach using implied volatility indexes," Energy Economics, Elsevier, vol. 66(C), pages 122-139.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cui Jinxin & Zou Huiwen, 2020. "Connectedness Among Economic Policy Uncertainties: Evidence from the Time and Frequency Domain Perspectives," Journal of Systems Science and Information, De Gruyter, vol. 8(5), pages 401-433, October.
    2. Song, Zhouying & Zhu, Qiaoling & Han, Mengyao, 2021. "Tele-connection of global crude oil network: Comparisons between direct trade and embodied flows," Energy, Elsevier, vol. 217(C).
    3. Ding, Qian & Huang, Jianbai & Chen, Jinyu, 2021. "Dynamic and frequency-domain risk spillovers among oil, gold, and foreign exchange markets: Evidence from implied volatility," Energy Economics, Elsevier, vol. 102(C).
    4. Pawan Kumar & Vipul Kumar Singh, 2023. "Examining the Time Varying Spillover Dynamics of Indian Financial Indictors from Global and Local Economic Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 99-121, March.
    5. Tanin, Tauhidul Islam & Sarker, Ashutosh & Brooks, Robert & Do, Hung Xuan, 2022. "Does oil impact gold during COVID-19 and three other recent crises?," Energy Economics, Elsevier, vol. 108(C).
    6. Kumar, Pawan & Singh, Vipul Kumar & Rao, Sandeep, 2023. "Does the substitution effect lead to feedback effect linkage between ethanol, crude oil, and soft agricultural commodities?," Energy Economics, Elsevier, vol. 119(C).
    7. Cui, Jinxin & Goh, Mark & Li, Binlin & Zou, Huiwen, 2021. "Dynamic dependence and risk connectedness among oil and stock markets: New evidence from time-frequency domain perspectives," Energy, Elsevier, vol. 216(C).
    8. Yuan, Ying & Du, Xinyu, 2023. "Dynamic spillovers across global stock markets during the COVID-19 pandemic: Evidence from jumps and higher moments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    9. 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).
    10. Tang, Chun & Liu, Xiaoxing & Chen, Guangkun, 2023. "The spillover effects in the “Energy – Carbon – Stock” system – Evidence from China," Energy, Elsevier, vol. 278(PA).
    11. Demiralay, Sercan & Gencer, Hatice Gaye & Bayraci, Selcuk, 2022. "Carbon credit futures as an emerging asset: Hedging, diversification and downside risks," Energy Economics, Elsevier, vol. 113(C).
    12. Yuntong Liu & Yu Wei & Yi Liu & Wenjuan Li, 2020. "Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-12, December.
    13. Bajaj, Vimmy & Kumar, Pawan & Singh, Vipul Kumar, 2023. "Systemwide directional connectedness from Crude Oil to sovereign credit risk," Journal of Commodity Markets, Elsevier, vol. 30(C).
    14. Tadahiro Nakajima & Yuki Toyoshima, 2020. "Examination of the Spillover Effects among Natural Gas and Wholesale Electricity Markets Using Their Futures with Different Maturities and Spot Prices," Energies, MDPI, vol. 13(7), pages 1-14, March.
    15. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    16. Suleman, Muhammad Tahir & McIver, Ron & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness between Islamic stock and commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    17. Kumar, Pawan & Singh, Vipul Kumar, 2022. "Does crude oil fire the emerging markets currencies contagion spillover? A systemic perspective," Energy Economics, Elsevier, vol. 116(C).
    18. Hassan, Kamrul & Hoque, Ariful & Wali, Muammer & Gasbarro, Dominic, 2020. "Islamic stocks, conventional stocks, and crude oil: Directional volatility spillover analysis in BRICS," Energy Economics, Elsevier, vol. 92(C).
    19. Manickavasagam, Jeevananthan & Visalakshmi, S. & Apergis, Nicholas, 2020. "A novel hybrid approach to forecast crude oil futures using intraday data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    20. Umar, Zaghum & Aharon, David Y. & Esparcia, Carlos & AlWahedi, Wafa, 2022. "Spillovers between sovereign yield curve components and oil price shocks," Energy Economics, Elsevier, vol. 109(C).
    21. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    22. Kumar, Pawan & Singh, Vipul Kumar, 2022. "Systemic spillover dynamics of crude oil with Indian Financial indicators in post WPI revision and COVID era," Resources Policy, Elsevier, vol. 77(C).

    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. Maitra, Debasish & Guhathakurta, Kousik & Kang, Sang Hoon, 2021. "The good, the bad and the ugly relation between oil and commodities: An analysis of asymmetric volatility connectedness and portfolio implications," Energy Economics, Elsevier, vol. 94(C).
    2. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    3. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & Perez de Gracia, Fernando, 2018. "Oil volatility, oil and gas firms and portfolio diversification," Energy Economics, Elsevier, vol. 70(C), pages 499-515.
    4. Guhathakurta, Kousik & Dash, Saumya Ranjan & Maitra, Debasish, 2020. "Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications," Energy Economics, Elsevier, vol. 85(C).
    5. Malik, Farooq & Umar, Zaghum, 2019. "Dynamic connectedness of oil price shocks and exchange rates," Energy Economics, Elsevier, vol. 84(C).
    6. Mensi, Walid & Hamed Al-Yahyaee, Khamis & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Dynamic spillover and connectedness between oil futures and European bonds," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    7. Huszár, Zsuzsa R. & Kotró, Balázs B. & Tan, Ruth S.K., 2023. "Dynamic volatility transfer in the European oil and gas industry," Energy Economics, Elsevier, vol. 127(PA).
    8. Maghyereh, Aktham I. & Awartani, Basel & Bouri, Elie, 2016. "The directional volatility connectedness between crude oil and equity markets: New evidence from implied volatility indexes," Energy Economics, Elsevier, vol. 57(C), pages 78-93.
    9. Kumar, Pawan & Singh, Vipul Kumar, 2022. "Systemic spillover dynamics of crude oil with Indian Financial indicators in post WPI revision and COVID era," Resources Policy, Elsevier, vol. 77(C).
    10. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Oil price shocks and the return and volatility spillover between industrial and precious metals," Energy Economics, Elsevier, vol. 99(C).
    11. Jozef Baruník and Ev~en Kocenda, 2019. "Total, Asymmetric and Frequency Connectedness between Oil and Forex Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Special I).
    12. Si Mohammed, Kamel & Tedeschi, Marco & Mallek, Sabrine & Tarczyńska-Łuniewska, Małgorzata & Zhang, Anqi, 2023. "Realized semi variance quantile connectedness between oil prices and stock market: Spillover from Russian-Ukraine clash," Resources Policy, Elsevier, vol. 85(PA).
    13. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Maitra, Debasish & Al-Jarrah, Idries Mohammad Wanas, 2019. "Portfolio management and dependencies among precious metal markets: Evidence from a Copula quantile-on-quantile approach," Resources Policy, Elsevier, vol. 64(C).
    14. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    15. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    16. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir, 2021. "Dynamic return and volatility spillovers among S&P 500, crude oil, and gold," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 153-170, January.
    17. 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).
    18. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    19. Maitra, Debasish & Chandra, Saurabh & Dash, Saumya Ranjan, 2020. "Liner shipping industry and oil price volatility: Dynamic connectedness and portfolio diversification," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    20. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & de Gracia, Fernando Perez, 2023. "Dynamic connectedness among the implied volatilities of oil prices and financial assets: New evidence of the COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 114-123.

    More about this item

    Keywords

    Bonds; Commodity; Connectedness; Crude oil; Currency; Equity; Generalized error variance decomposition; Spillover; Volatility; Network;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:eneeco:v:80:y:2019:i:c:p:321-335. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.