[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v41y2021i10p1655-1673.html
   My bibliography  Save this article

The dynamics of cross‐boundary fire—Financial contagion between the oil and stock markets

Author

Listed:
  • Haiying Wang
  • Ying Yuan
  • Tianyang Wang
Abstract
Motivated by the complex dynamics between the oil and stock markets, this study develops a dynamic Markov regime switching‐copula‐extreme value theory model to quantitatively investigate financial contagion and its characteristics between these two markets. The proposed model is applied to daily returns on crude oil prices and the stock markets in the United States and China over six major extreme downside risk events. We find that financial contagion is shorter, stronger, and more susceptible to extreme downside shocks in the United States than in China. In addition, the COVID‐19 crisis shows the largest financial contagion compared with previous crises.

Suggested Citation

  • Haiying Wang & Ying Yuan & Tianyang Wang, 2021. "The dynamics of cross‐boundary fire—Financial contagion between the oil and stock markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1655-1673, October.
    • Handle: RePEc:wly:jfutmk:v:41:y:2021:i:10:p:1655-1673
    DOI: 10.1002/fut.22239
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22239
    Download Restriction: no
    File URL: https://libkey.io/10.1002/fut.22239?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
    ---><---

    References listed on IDEAS

    as
    1. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Role of index futures on China's stock markets: Evidence from price discovery and volatility spillover," Pacific-Basin Finance Journal, Elsevier, vol. 44(C), pages 13-26.
    2. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    3. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.
    4. Qu, Hui & Wang, Tianyang & Zhang, Yi & Sun, Pengfei, 2019. "Dynamic hedging using the realized minimum-variance hedge ratio approach – Examination of the CSI 300 index futures," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    5. Tianyang Wang & James S. Dyer, 2012. "A Copulas-Based Approach to Modeling Dependence in Decision Trees," Operations Research, INFORMS, vol. 60(1), pages 225-242, February.
    6. Chatrath, Arjun & Miao, Hong & Ramchander, Sanjay & Wang, Tianyang, 2016. "An examination of the flow characteristics of crude oil: Evidence from risk-neutral moments," Energy Economics, Elsevier, vol. 54(C), pages 213-223.
    7. Jin Boon Wong, 2021. "Stock market reactions to different types of oil shocks: Evidence from China," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 179-193, February.
    8. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    9. Ye, Wuyi & Luo, Kebing & Liu, Xiaoquan, 2017. "Time-varying quantile association regression model with applications to financial contagion and VaR," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1015-1028.
    10. Akihiro Omura & Neda Todorova, 2019. "The quantile dependence of commodity futures markets on news sentiment," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 818-837, July.
    11. Annastiina Silvennoinen & Susan Thorp, 2016. "Crude Oil and Agricultural Futures: An Analysis of Correlation Dynamics," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(6), pages 522-544, June.
    12. Donald Lien & Hsiang‐Tai Lee & Her‐Jiun Sheu, 2018. "Hedging systematic risk in the commodity market with a regime‐switching multivariate rotated generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(12), pages 1514-1532, December.
    13. Miao, Hong & Ramchander, Sanjay & Wang, Tianyang & Yang, Dongxiao, 2017. "Influential factors in crude oil price forecasting," Energy Economics, Elsevier, vol. 68(C), pages 77-88.
    14. Mensi, Walid & Hammoudeh, Shawkat & Shahzad, Syed Jawad Hussain & Shahbaz, Muhammad, 2017. "Modeling systemic risk and dependence structure between oil and stock markets using a variational mode decomposition-based copula method," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 258-279.
    15. Jin Boon Wong & Qin Zhang, 2020. "Impact of international energy prices on China's industries," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 722-748, May.
    16. Ron Alquist & Reinhard Ellwanger & Jianjian Jin, 2020. "The effect of oil price shocks on asset markets: Evidence from oil inventory news," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(8), pages 1212-1230, August.
    17. Zihui Yang & Yinggang Zhou, 2017. "Quantitative Easing and Volatility Spillovers Across Countries and Asset Classes," Management Science, INFORMS, vol. 63(2), pages 333-354, February.
    18. Doina Chichernea & Kershen Huang & Alex Petkevich, 2019. "Does maturity matter? The case of treasury futures volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(10), pages 1301-1321, October.
    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. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    21. Maryam Ahmadi & Niaz Bashiri Behmiri & Matteo Manera, 2020. "The theory of storage in the crude oil futures market, the role of financial conditions," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1160-1175, July.
    22. Mohammad Isleimeyyeh, 2020. "The role of financial investors in determining the commodity futures risk premium," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(9), pages 1375-1397, September.
    23. Tsai, Chun-Li, 2015. "How do U.S. stock returns respond differently to oil price shocks pre-crisis, within the financial crisis, and post-crisis?," Energy Economics, Elsevier, vol. 50(C), pages 47-62.
    24. Hong Miao & Sanjay Ramchander & Tianyang Wang & Jian Yang, 2018. "The impact of crude oil inventory announcements on prices: Evidence from derivatives markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 38-65, January.
    25. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    26. Ng, Lilian & Wu, Fei, 2007. "The trading behavior of institutions and individuals in Chinese equity markets," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2695-2710, September.
    27. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong, 2019. "Measuring tail risk with GAS time varying copula, fat tailed GARCH model and hedging for crude oil futures," Pacific-Basin Finance Journal, Elsevier, vol. 55(C), pages 95-109.
    28. Jian Yang & Yinggang Zhou, 2020. "Return and volatility transmission between China's and international crude oil futures markets: A first look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 860-884, June.
    29. Georgios Bampinas & Theodore Panagiotidis, 2017. "Oil and stock markets before and after financial crises: A local Gaussian correlation approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 37(12), pages 1179-1204, December.
    30. Zhu, Huiming & Guo, Yawei & You, Wanhai & Xu, Yaqin, 2016. "The heterogeneity dependence between crude oil price changes and industry stock market returns in China: Evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 55(C), pages 30-41.
    31. Driesprong, Gerben & Jacobsen, Ben & Maat, Benjamin, 2008. "Striking oil: Another puzzle?," Journal of Financial Economics, Elsevier, vol. 89(2), pages 307-327, August.
    32. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    33. Paulo Horta & Sérgio Lagoa & Luís Martins, 2016. "Unveiling investor-induced channels of financial contagion in the 2008 financial crisis using copulas," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 625-637, April.
    34. Zhang, Guofu & Liu, Wei, 2018. "Analysis of the international propagation of contagion between oil and stock markets," Energy, Elsevier, vol. 165(PA), pages 469-486.
    35. Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.
    36. Sridhar Gogineni, 2010. "Oil and the Stock Market: An Industry Level Analysis," The Financial Review, Eastern Finance Association, vol. 45(4), pages 995-1010, November.
    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. Yuan, Ying & Wang, Haiying & Jin, Xiu, 2022. "Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19," International Review of Financial Analysis, Elsevier, vol. 83(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. Sheng Fang & Paul Egan, 2021. "Tail dependence between oil prices and China's A‐shares: Evidence from firm‐level data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1469-1487, January.
    2. You, Wanhai & Guo, Yawei & Zhu, Huiming & Tang, Yong, 2017. "Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression," Energy Economics, Elsevier, vol. 68(C), pages 1-18.
    3. Qin Zhang & Jin Boon Wong, 2022. "Do oil shocks impact stock liquidity?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 472-491, March.
    4. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    5. Aviral Kumar Tiwari & Sangram Keshari Jena & Satish Kumar & Erik Hille, 2022. "Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach," Annals of Operations Research, Springer, vol. 315(1), pages 429-461, August.
    6. Huiming Zhu & Xianfang Su & Yawei Guo & Yinghua Ren, 2016. "The Asymmetric Effects of Oil Price Shocks on the Chinese Stock Market: Evidence from a Quantile Impulse Response Perspective," Sustainability, MDPI, vol. 8(8), pages 1-19, August.
    7. Chen, Chun-Da & Cheng, Chiao-Ming & Demirer, Rıza, 2017. "Oil and stock market momentum," Energy Economics, Elsevier, vol. 68(C), pages 151-159.
    8. Mishra, Shekhar & Mishra, Sibanjan, 2021. "Are Indian sectoral indices oil shock prone? An empirical evaluation," Resources Policy, Elsevier, vol. 70(C).
    9. Yuan, Ying & Wang, Haiying & Jin, Xiu, 2022. "Pandemic-driven financial contagion and investor behavior: Evidence from the COVID-19," International Review of Financial Analysis, Elsevier, vol. 83(C).
    10. Ferreiro Javier Ojea, 2019. "Structural change in the link between oil and the European stock market: implications for risk management," Dependence Modeling, De Gruyter, vol. 7(1), pages 53-125, January.
    11. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    12. Chang, Bisharat Hussain & Sharif, Arshian & Aman, Ameenullah & Suki, Norazah Mohd & Salman, Asma & Khan, Syed Abdul Rehman, 2020. "The asymmetric effects of oil price on sectoral Islamic stocks: New evidence from quantile-on-quantile regression approach," Resources Policy, Elsevier, vol. 65(C).
    13. Ramzi Benkraiem & Thi hong van Hoang & Amine Lahiani & Anthony Miloudi, 2018. "Crude oil and equity markets in major European countries: New evidence," Economics Bulletin, AccessEcon, vol. 38(4), pages 2094-2110.
    14. Smyth, Russell & Narayan, Paresh Kumar, 2018. "What do we know about oil prices and stock returns?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 148-156.
    15. Liu, Bing-Yue & Fan, Ying & Ji, Qiang & Hussain, Nazim, 2022. "High-dimensional CoVaR network connectedness for measuring conditional financial contagion and risk spillovers from oil markets to the G20 stock system," Energy Economics, Elsevier, vol. 105(C).
    16. Mo, Xuan & Su, Zhi & Yin, Libo, 2019. "Can the skewness of oil returns affect stock returns? Evidence from China’s A-Share markets," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    17. Yin, Libo & Feng, Jiabao & Liu, Li & Wang, Yudong, 2019. "It's not that important: The negligible effect of oil market uncertainty," International Review of Economics & Finance, Elsevier, vol. 60(C), pages 62-84.
    18. Yonghong Jiang & Jinqi Mu & He Nie & Lanxin Wu, 2022. "Time‐frequency analysis of risk spillovers from oil to BRICS stock markets: A long‐memory Copula‐CoVaR‐MODWT method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3386-3404, July.
    19. Liu, Zhenhua & Zhang, Huiying & Ding, Zhihua & Lv, Tao & Wang, Xu & Wang, Deqing, 2022. "When are the effects of economic policy uncertainty on oil–stock correlations larger? Evidence from a regime-switching analysis," Economic Modelling, Elsevier, vol. 114(C).
    20. Seiji Harikae & James S. Dyer & Tianyang Wang, 2021. "Valuing Real Options in the Volatile Real World," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 171-189, January.

    More about this item

    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:wly:jfutmk:v:41:y:2021:i:10:p:1655-1673. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    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.