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Oil prices and financial stress: A volatility spillover analysis

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  • Nazlioglu, Saban
  • Soytas, Ugur
  • Gupta, Rangan

Abstract

This paper examines whether there is a volatility transmission between oil prices and financial stress by means of the volatility spillover test. We employ WTI crude oil prices and Cleveland financial stress index for the period 1991–2014 and divide the sample into pre-crisis, in-crisis, and post-crisis periods due to the downward trend in oil price in 2008. The volatility model estimations indicate that oil prices and financial stress index are dominated by long-run volatility. The volatility spillover causality test supports evidence on risk transfer from oil prices to financial stress before the crisis and from financial stress to oil prices after the crisis. The impulse response analysis shows that the volatility transmission pattern has similar dynamics before and after the crisis and is characterized by higher and long-lived effects during the crisis. Our results have implications for both policy makers and investors, and for future work.

Suggested Citation

  • Nazlioglu, Saban & Soytas, Ugur & Gupta, Rangan, 2015. "Oil prices and financial stress: A volatility spillover analysis," Energy Policy, Elsevier, vol. 82(C), pages 278-288.
  • Handle: RePEc:eee:enepol:v:82:y:2015:i:c:p:278-288
    DOI: 10.1016/j.enpol.2015.01.003
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    2. Gupta, Rangan & Kanda, Patrick & Tiwari, Aviral Kumar & Wohar, Mark E., 2019. "Time-varying predictability of oil market movements over a century of data: The role of US financial stress," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. Gaoke Liao & Zhenghui Li & Ziqing Du & Yue Liu, 2019. "The Heterogeneous Interconnections between Supply or Demand Side and Oil Risks," Energies, MDPI, Open Access Journal, vol. 12(11), pages 1-17, June.
    4. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    5. Das, Debojyoti & Kannadhasan, M. & Bhattacharyya, Malay, 2019. "Do the emerging stock markets react to international economic policy uncertainty, geopolitical risk and financial stress alike?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 1-19.
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    9. Zhao, Zhen-yu & Zhu, Jiang & Xia, Bo, 2016. "Multi-fractal fluctuation features of thermal power coal price in China," Energy, Elsevier, vol. 117(P1), pages 10-18.
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    11. Zhang, Yali & Wang, Jun, 2019. "Linkage influence of energy market on financial market by multiscale complexity synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 254-266.
    12. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    13. Mohamed Albaity & Hasan Mustafa, 2018. "International and Macroeconomic Determinants of Oil Price: Evidence from Gulf Cooperation Council Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 8(1), pages 69-81.
    14. Christopher Thiem, 2018. "Oil price uncertainty and the business cycle: Accounting for the influences of global supply and demand within a VAR GARCH-in-mean framework," Applied Economics, Taylor & Francis Journals, vol. 50(34-35), pages 3735-3751, July.
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    21. Zhang, Dayong & Cao, Hong & Dickinson, David G. & Kutan, Ali M., 2016. "Free cash flows and overinvestment: Further evidence from Chinese energy firms," Energy Economics, Elsevier, vol. 58(C), pages 116-124.
    22. Liu, Xueyong & An, Haizhong & Li, Huajiao & Chen, Zhihua & Feng, Sida & Wen, Shaobo, 2017. "Features of spillover networks in international financial markets: Evidence from the G20 countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 265-278.
    23. 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.
    24. Feng, Sida & Huang, Shupei & Qi, Yabin & Liu, Xueyong & Sun, Qingru & Wen, Shaobo, 2018. "Network features of sector indexes spillover effects in China: A multi-scale view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 461-473.

    More about this item

    Keywords

    Oil prices; Financial stress index; Causality; Volatility spillover;

    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G1 - Financial Economics - - General Financial Markets

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