IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v76y2021icp1-39.html
   My bibliography  Save this article

Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis

Author

Listed:
  • Huang, Jionghao
  • Li, Ziruo
  • Xia, Xiaohua

Abstract

This paper aims to investigate whether oil volatility risks could diffuse through the linkage of industry returns and even further contribute to global crisis throughout the stock market. To highlight such sectoral financial interconnectedness which may serve as a key channel for oil volatility diffusion, we first apply the partial cross-quantilogram (PCQ) approach to detect the directional predictability between returns of 26 industries in China's stock market across different quantiles. We construct the corresponding network to provide a more comprehensive picture of such sectoral interconnection, which is shown to vary prominently under different market states and lag order specifications. Utilizing the spatial autoregressive (SAR) model for panel data, we further assess the possibility of the oil volatility risk diffusion by decomposing the aggregate effect of oil volatility shocks into direct shocks, and indirect shocks transmitting through the estimated network linkage of industries. The empirical results point to the significantly heterogeneous pattern of oil volatility risk diffusion among networks with different lag selections under various market states. Considering the financial linkage of industries within 5 traded days under extreme market states, there exist significant indirect effects contributing to larger oil volatility shocks on industry returns, which confirms risk contagion effects of monthly oil volatilities. It indicates that the network linkage of financial assets might be an important diffusion mechanism for oil volatility risks, which should not be neglected in the research of the oil-stock nexus.

Suggested Citation

  • Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
  • Handle: RePEc:eee:reveco:v:76:y:2021:i:c:p:1-39
    DOI: 10.1016/j.iref.2021.04.034
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S105905602100099X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2021.04.034?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. Marchese, Malvina & Kyriakou, Ioannis & Tamvakis, Michael & Di Iorio, Francesca, 2020. "Forecasting crude oil and refined products volatilities and correlations: New evidence from fractionally integrated multivariate GARCH models," Energy Economics, Elsevier, vol. 88(C).
    2. Ahmed, Abdullahi D. & Huo, Rui, 2021. "Volatility transmissions across international oil market, commodity futures and stock markets: Empirical evidence from China," Energy Economics, Elsevier, vol. 93(C).
    3. Caporale, Guglielmo Maria & Menla Ali, Faek & Spagnolo, Nicola, 2015. "Oil price uncertainty and sectoral stock returns in China: A time-varying approach," China Economic Review, Elsevier, vol. 34(C), pages 311-321.
    4. Singhal, Shelly & Ghosh, Sajal, 2016. "Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models," Resources Policy, Elsevier, vol. 50(C), pages 276-288.
    5. Rajeev Dhawan & Karsten Jeske, 2008. "Energy Price Shocks and the Macroeconomy: The Role of Consumer Durables," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1357-1377, October.
    6. Geng, Jiang-Bo & Du, Ya-Juan & Ji, Qiang & Zhang, Dayong, 2021. "Modeling return and volatility spillover networks of global new energy companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    7. Baumöhl, Eduard & Kočenda, Evžen & Lyócsa, Štefan & Výrost, Tomáš, 2018. "Networks of volatility spillovers among stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1555-1574.
    8. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    9. Donald W. Jones, Paul N. Leiby and Inja K. Paik, 2004. "Oil Price Shocks and the Macroeconomy: What Has Been Learned Since 1996," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-32.
    10. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    11. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2015. "Systemic Risk and Stability in Financial Networks," American Economic Review, American Economic Association, vol. 105(2), pages 564-608, February.
    12. Lutz Kilian, 2014. "Oil Price Shocks: Causes and Consequences," Annual Review of Resource Economics, Annual Reviews, vol. 6(1), pages 133-154, October.
    13. Daron Acemoglu & Vasco M. Carvalho & Asuman Ozdaglar & Alireza Tahbaz‐Salehi, 2012. "The Network Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 80(5), pages 1977-2016, September.
    14. Brunetti, Celso & Harris, Jeffrey H. & Mankad, Shawn & Michailidis, George, 2019. "Interconnectedness in the interbank market," Journal of Financial Economics, Elsevier, vol. 133(2), pages 520-538.
    15. Hedi Arouri, Mohamed El & Khuong Nguyen, Duc, 2010. "Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade," Energy Policy, Elsevier, vol. 38(8), pages 4528-4539, August.
    16. Bernard Herskovic & Bryan Kelly & Hanno Lustig & Stijn Van Nieuwerburgh, 2020. "Firm Volatility in Granular Networks," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4097-4162.
    17. Robert B. Barsky & Lutz Kilian, 2004. "Oil and the Macroeconomy Since the 1970s," Journal of Economic Perspectives, American Economic Association, vol. 18(4), pages 115-134, Fall.
    18. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    19. Stanimira Milcheva & Bing Zhu, 2018. "Asset pricing, spatial linkages and contagion in real estate stocks," Journal of Property Research, Taylor & Francis Journals, vol. 35(4), pages 271-295, October.
    20. Chen, Shiu-Sheng, 2010. "Do higher oil prices push the stock market into bear territory?," Energy Economics, Elsevier, vol. 32(2), pages 490-495, March.
    21. Dutta, Anupam & Nikkinen, Jussi & Rothovius, Timo, 2017. "Impact of oil price uncertainty on Middle East and African stock markets," Energy, Elsevier, vol. 123(C), pages 189-197.
    22. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    23. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    24. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    25. Kilian, Lutz & Zhou, Xiaoqing, 2018. "Modeling fluctuations in the global demand for commodities," Journal of International Money and Finance, Elsevier, vol. 88(C), pages 54-78.
    26. Gupta, Rangan & Modise, Mampho P., 2013. "Does the source of oil price shocks matter for South African stock returns? A structural VAR approach," Energy Economics, Elsevier, vol. 40(C), pages 825-831.
    27. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
    28. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    29. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    30. Yudong Wang & Li Liu, 2016. "Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging," Empirical Economics, Springer, vol. 50(4), pages 1481-1509, June.
    31. Lutz Kilian & Cheolbeom Park, 2009. "The Impact Of Oil Price Shocks On The U.S. Stock Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(4), pages 1267-1287, November.
    32. Andrew Patton & Dimitris Politis & Halbert White, 2009. "Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White," Econometric Reviews, Taylor & Francis Journals, vol. 28(4), pages 372-375.
    33. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    34. Mishra, Shekhar & Sharif, Arshian & Khuntia, Sashikanta & Meo, Muhammad Saeed & Rehman Khan, Syed Abdul, 2019. "Does oil prices impede Islamic stock indices? Fresh insights from wavelet-based quantile-on-quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 292-304.
    35. Fang, Chung-Rou & You, Shih-Yi, 2014. "The impact of oil price shocks on the large emerging countries' stock prices: Evidence from China, India and Russia," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 330-338.
    36. Debarsy, Nicolas & Dossougoin, Cyrille & Ertur, Cem & Gnabo, Jean-Yves, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 21-45.
    37. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    38. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    39. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    40. Patrick J. Kehoe & Andrew Atkeson, 1999. "Models of Energy Use: Putty-Putty versus Putty-Clay," American Economic Review, American Economic Association, vol. 89(4), pages 1028-1043, September.
    41. 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).
    42. Michael Weber & Ali Ozdagli, 2016. "Monetary Policy Through Production Networks: Evidence from the Stock Market," 2016 Meeting Papers 148, Society for Economic Dynamics.
    43. Finn, Mary G, 2000. "Perfect Competition and the Effects of Energy Price Increases on Economic Activity," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 32(3), pages 400-416, August.
    44. Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
    45. Zhu, Hui-Ming & Li, Rong & Li, Sufang, 2014. "Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 208-223.
    46. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.
    47. Yan‐ran Ma & Qiang Ji & Jiaofeng Pan, 2019. "Oil financialization and volatility forecast: Evidence from multidimensional predictors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(6), pages 564-581, September.
    48. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    49. Boldanov, Rustam & Degiannakis, Stavros & Filis, George, 2016. "Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 209-220.
    50. Michael Weber & Ali Ozdagli, 2016. "Monetary Policy Through Production Networks: Evidence from the Stock Market," 2016 Meeting Papers 148, Society for Economic Dynamics.
    51. Dimitris Politis & Halbert White, 2004. "Automatic Block-Length Selection for the Dependent Bootstrap," Econometric Reviews, Taylor & Francis Journals, vol. 23(1), pages 53-70.
    52. Luo, Jiawen & Ji, Qiang & Klein, Tony & Todorova, Neda & Zhang, Dayong, 2020. "On realized volatility of crude oil futures markets: Forecasting with exogenous predictors under structural breaks," Energy Economics, Elsevier, vol. 89(C).
    53. Sadorsky, Perry, 1999. "Oil price shocks and stock market activity," Energy Economics, Elsevier, vol. 21(5), pages 449-469, October.
    54. Han, Liyan & Lv, Qiuna & Yin, Libo, 2019. "The effect of oil returns on the stock markets network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    55. Jones, Charles M & Kaul, Gautam, 1996. "Oil and the Stock Markets," Journal of Finance, American Finance Association, vol. 51(2), pages 463-491, June.
    56. Steven Kou & Xianhua Peng & Haowen Zhong, 2018. "Asset Pricing with Spatial Interaction," Management Science, INFORMS, vol. 64(5), pages 2083-2101, May.
    57. Asgharian, Hossein & Hess, Wolfgang & Liu, Lu, 2013. "A spatial analysis of international stock market linkages," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4738-4754.
    58. 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.
    59. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    60. Apergis, Nicholas & Miller, Stephen M., 2009. "Do structural oil-market shocks affect stock prices?," Energy Economics, Elsevier, vol. 31(4), pages 569-575, July.
    61. Luo, Xingguo & Qin, Shihua, 2017. "Oil price uncertainty and Chinese stock returns: New evidence from the oil volatility index," Finance Research Letters, Elsevier, vol. 20(C), pages 29-34.
    62. Viviana Fernandez, 2011. "Spatial linkages in international financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 11(2), pages 237-245.
    63. Bakas, Dimitrios & Triantafyllou, Athanasios, 2019. "Volatility forecasting in commodity markets using macro uncertainty," Energy Economics, Elsevier, vol. 81(C), pages 79-94.
    64. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    65. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    66. Aloui, Chaker & Nguyen, Duc Khuong & Njeh, Hassen, 2012. "Assessing the impacts of oil price fluctuations on stock returns in emerging markets," Economic Modelling, Elsevier, vol. 29(6), pages 2686-2695.
    67. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
    68. Cong, Rong-Gang & Wei, Yi-Ming & Jiao, Jian-Lin & Fan, Ying, 2008. "Relationships between oil price shocks and stock market: An empirical analysis from China," Energy Policy, Elsevier, vol. 36(9), pages 3544-3553, September.
    69. Rajeev Dhawan & Karsten Jeske, 2008. "Energy Price Shocks and the Macroeconomy: The Role of Consumer Durables," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(7), pages 1357-1377, October.
    70. Shin, Yongcheol & Schmidt, Peter, 1992. "The KPSS stationarity test as a unit root test," Economics Letters, Elsevier, vol. 38(4), pages 387-392, April.
    71. 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.
    72. Zhang, Yue-Jun & Yao, Ting & He, Ling-Yun & Ripple, Ronald, 2019. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 302-317.
    73. Zhang, Chuanguo & Chen, Xiaoqing, 2011. "The impact of global oil price shocks on China’s stock returns: Evidence from the ARJI(-ht)-EGARCH model," Energy, Elsevier, vol. 36(11), pages 6627-6633.
    74. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.
    75. Wei, Yanfeng & Guo, Xiaoying, 2017. "Oil price shocks and China's stock market," Energy, Elsevier, vol. 140(P1), pages 185-197.
    76. Bassam Fattouh & Lavan Mahadeva, 2013. "OPEC: What Difference Has It Made?," Annual Review of Resource Economics, Annual Reviews, vol. 5(1), pages 427-443, June.
    77. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    78. Kim, In-Moo & Loungani, Prakash, 1992. "The role of energy in real business cycle models," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 173-189, April.
    79. Basher, Syed Abul & Sadorsky, Perry, 2016. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," Energy Economics, Elsevier, vol. 54(C), pages 235-247.
    80. Awartani, Basel & Aktham, Maghyereh & Cherif, Guermat, 2016. "The connectedness between crude oil and financial markets: Evidence from implied volatility indices," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 56-69.
    81. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    82. Balli, Faruk & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain & de Bruin, Anne, 2019. "Spillover network of commodity uncertainties," Energy Economics, Elsevier, vol. 81(C), pages 914-927.
    83. Miller, J. Isaac & Ratti, Ronald A., 2009. "Crude oil and stock markets: Stability, instability, and bubbles," Energy Economics, Elsevier, vol. 31(4), pages 559-568, July.
    84. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    85. Ramaprasad Bhar & Biljana Nikolova, 2009. "Oil Prices and Equity Returns in the BRIC Countries," The World Economy, Wiley Blackwell, vol. 32(7), pages 1036-1054, July.
    86. 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.
    87. Ma, Feng & Zhang, Yaojie & Huang, Dengshi & Lai, Xiaodong, 2018. "Forecasting oil futures price volatility: New evidence from realized range-based volatility," Energy Economics, Elsevier, vol. 75(C), pages 400-409.
    88. Tiwari, Aviral Kumar & Trabelsi, Nader & Alqahtani, Faisal & Hammoudeh, Shawkat, 2019. "Analysing systemic risk and time-frequency quantile dependence between crude oil prices and BRICS equity markets indices: A new look," Energy Economics, Elsevier, vol. 83(C), pages 445-466.
    89. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    90. Reboredo, Juan C. & Ugolini, Andrea, 2016. "Quantile dependence of oil price movements and stock returns," Energy Economics, Elsevier, vol. 54(C), pages 33-49.
    91. Silva, Thiago Christiano & Alexandre, Michel da Silva & Tabak, Benjamin Miranda, 2018. "Bank lending and systemic risk: A financial-real sector network approach with feedback," Journal of Financial Stability, Elsevier, vol. 38(C), pages 98-118.
    92. Herrera, Ana María & Hu, Liang & Pastor, Daniel, 2018. "Forecasting crude oil price volatility," International Journal of Forecasting, Elsevier, vol. 34(4), pages 622-635.
    93. Boubaker, Heni & Raza, Syed Ali, 2017. "A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets," Energy Economics, Elsevier, vol. 64(C), pages 105-117.
    94. 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.
    95. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    96. Chen, Na & Jin, Xiu & Zhuang, Xintian & Yuan, Ying, 2020. "Spatial pricing with multiple risk transmission channels and specific factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    97. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    98. Zhou, Zhongbao & Jiang, Yong & Liu, Yan & Lin, Ling & Liu, Qing, 2019. "Does international oil volatility have directional predictability for stock returns? Evidence from BRICS countries based on cross-quantilogram analysis," Economic Modelling, Elsevier, vol. 80(C), pages 352-382.
    99. Edelstein, Paul & Kilian, Lutz, 2009. "How sensitive are consumer expenditures to retail energy prices?," Journal of Monetary Economics, Elsevier, vol. 56(6), pages 766-779, September.
    100. An, Yang & Sun, Mei & Gao, Cuixia & Han, Dun & Li, Xiuming, 2018. "Analysis of the impact of crude oil price fluctuations on China’s stock market in different periods—Based on time series network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1016-1031.
    101. 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.
    102. Meng, Fanyi & Liu, Li, 2019. "Analyzing the economic sources of oil price volatility: An out-of-sample perspective," Energy, Elsevier, vol. 177(C), pages 476-486.
    103. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    104. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
    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. Bin Mo & Juan Meng & Guannan Wang, 2023. "Risk Dependence and Risk Spillovers Effect from Crude Oil on the Chinese Stock Market and Gold Market: Implications on Portfolio Management," Energies, MDPI, vol. 16(5), pages 1-17, February.
    2. Tong Fang & Deyu Miao & Zhi Su & Libo Yin, 2023. "Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 872-904, July.
    3. Mehmet Selman Colak & Sumeyra Korkmaz & Huseyin Ozturk & Muhammed Hasan Yilmaz, 2024. "It Is Not Your Risk but It Is Your Problem: A Spatial Analysis of Emerging Market Credit Default Swap Premia," CBT Research Notes in Economics 2406, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    4. Zhang, Yan & Xu, Yushi & Zhu, Xintong & Huang, Jionghao, 2024. "Coal price shock propagation through sectoral financial interconnectedness in China's stock market: Quantile coherency network modelling and shock decomposition analysis," Journal of Commodity Markets, Elsevier, vol. 34(C).
    5. Chen, Baifan & Huang, Jionghao & Liu, Danhe & Xia, Xiaohua, 2024. "Time-frequency return connectedness between Chinese coal futures and international stock indices," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 316-333.
    6. Chen, Bin-xia & Sun, Yan-lin, 2023. "Extreme risk contagion between international crude oil and China's energy-intensive sectors: New evidence from quantile Granger causality and spillover methods," Energy, Elsevier, vol. 285(C).
    7. Huang, Jionghao & Chen, Baifan & Xu, Yushi & Xia, Xiaohua, 2023. "Time-frequency volatility transmission among energy commodities and financial markets during the COVID-19 pandemic: A Novel TVP-VAR frequency connectedness approach," Finance Research Letters, Elsevier, vol. 53(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. Zhang, Yan & Xu, Yushi & Zhu, Xintong & Huang, Jionghao, 2024. "Coal price shock propagation through sectoral financial interconnectedness in China's stock market: Quantile coherency network modelling and shock decomposition analysis," Journal of Commodity Markets, Elsevier, vol. 34(C).
    2. Stavros Degiannakis & George Filis & Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, , vol. 39(5), pages 85-130, September.
    3. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. 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.
    5. Das, Debojyoti & Kannadhasan, M., 2020. "The asymmetric oil price and policy uncertainty shock exposure of emerging market sectoral equity returns: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 563-581.
    6. Xiao, Jihong & Zhou, Min & Wen, Fengming & Wen, Fenghua, 2018. "Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index," Energy Economics, Elsevier, vol. 74(C), pages 777-786.
    7. Hanif, Waqas & Hadhri, Sinda & El Khoury, Rim, 2024. "Quantile spillovers and connectedness between oil shocks and stock markets of the largest oil producers and consumers," Journal of Commodity Markets, Elsevier, vol. 34(C).
    8. Xiao, Jihong & Hu, Chunyan & Ouyang, Guangda & Wen, Fenghua, 2019. "Impacts of oil implied volatility shocks on stock implied volatility in China: Empirical evidence from a quantile regression approach," Energy Economics, Elsevier, vol. 80(C), pages 297-309.
    9. 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.
    10. Ziadat, Salem Adel & McMillan, David G. & Herbst, Patrick, 2022. "Oil shocks and equity returns during bull and bear markets: The case of oil importing and exporting nations," Resources Policy, Elsevier, vol. 75(C).
    11. Babak Fazelabdolabadi, 2019. "Uncertainty and energy-sector equity returns in Iran: a Bayesian and quasi-Monte Carlo time-varying analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    12. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    13. 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.
    14. Zhifang He & Jiaqi Chen & Fangzhao Zhou & Guoqing Zhang & Fenghua Wen, 2022. "Oil price uncertainty and the risk‐return relation in stock markets: Evidence from oil‐importing and oil‐exporting countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 1154-1172, January.
    15. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2019. "Quantile relationship between oil and stock returns: Evidence from emerging and frontier stock markets," Energy Policy, Elsevier, vol. 134(C).
    16. Zhenhua Liu & Zhihua Ding & Tao Lv & Jy S. Wu & Wei Qiang, 2019. "Financial factors affecting oil price change and oil-stock interactions: a review and future perspectives," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 207-225, January.
    17. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    18. Zhu, Huiming & Huang, Hui & Peng, Cheng & Yang, Yan, 2016. "Extreme dependence between crude oil and stock markets in Asia-Pacific regions: Evidence from quantile regression," Economics Discussion Papers 2016-46, Kiel Institute for the World Economy (IfW Kiel).
    19. 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).
    20. Wen, Danyan & Wang, Gang-Jin & Ma, Chaoqun & Wang, Yudong, 2019. "Risk spillovers between oil and stock markets: A VAR for VaR analysis," Energy Economics, Elsevier, vol. 80(C), pages 524-535.

    More about this item

    Keywords

    Partial cross-quantilogram causality; Sectoral financial linkage; Network diffusion; Oil volatility risk;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • 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
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:reveco:v:76:y:2021:i:c:p:1-39. 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/inca/620165 .

    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.