IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v68y2020ics1057521918305179.html
   My bibliography  Save this article

Identifying influential energy stocks based on spillover network

Author

Listed:
  • Wang, Ze
  • Gao, Xiangyun
  • An, Haizhong
  • Tang, Renwu
  • Sun, Qingru

Abstract

This study investigates the influential energy stocks in the China stock market between 2005.1.4 and 2018.4.3. The influential energy stock is defined as a stock whose fluctuations could lead to the rises and falls of many other stocks in the energy sector, which have attracted much attention from investors and policymakers. To achieve this objective, the BEKK-GARCH model is used to capture the volatility spillover among energy stocks, the more spillover correlations a stock has the more influential it is. Furthermore, complex network theory is introduced to give more specific and precise quantifications of the stock influence. Validity testing of the methods shows that the PageRank algorithm is the most suitable method for identifying influential energy stocks. The results reveal the time-varying features of influential energy stocks, which indicate the weak momentum effect and strong reversal effect of the China stock market. Furthermore, most of the top-10 influential energy stocks are belong to the industry of power and utilities, and the investors are suggested to make reverse trading strategies around the influential electricity stocks. Moreover, petroleum exploitation and petroleum processing are the most two influential subindustries, and the policymakers are suggested to pay much attention to prevent the aggregate risks of the oil stocks which belong to these two subindustries.

Suggested Citation

  • Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:finana:v:68:y:2020:i:c:s1057521918305179
    DOI: 10.1016/j.irfa.2018.11.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521918305179
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2018.11.004?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. Shahbaz, Muhammad & Khan, Saleheen & Tahir, Mohammad Iqbal, 2013. "The dynamic links between energy consumption, economic growth, financial development and trade in China: Fresh evidence from multivariate framework analysis," Energy Economics, Elsevier, vol. 40(C), pages 8-21.
    2. Jalil, Abdul & Feridun, Mete, 2011. "The impact of growth, energy and financial development on the environment in China: A cointegration analysis," Energy Economics, Elsevier, vol. 33(2), pages 284-291, March.
    3. 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.
    4. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    5. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    6. 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.
    7. He, Yongxiu & Xu, Yang & Pang, Yuexia & Tian, Huiying & Wu, Rui, 2016. "A regulatory policy to promote renewable energy consumption in China: Review and future evolutionary path," Renewable Energy, Elsevier, vol. 89(C), pages 695-705.
    8. Li, Xiao-Ming & Zou, Li-Ping, 2008. "How do policy and information shocks impact co-movements of China's T-bond and stock markets?," Journal of Banking & Finance, Elsevier, vol. 32(3), pages 347-359, March.
    9. Richard D. F. Harris & Anirut Pisedtasalasai, 2006. "Return and Volatility Spillovers Between Large and Small Stocks in the UK," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1556-1571, November.
    10. Allaudeen Hameed & Randall Morck & Jianfeng Shen & Bernard Yeung, 2015. "Information, Analysts, and Stock Return Comovement," The Review of Financial Studies, Society for Financial Studies, vol. 28(11), pages 3153-3187.
    11. Schreiber, Irene & Müller, Gernot & Klüppelberg, Claudia & Wagner, Niklas, 2012. "Equities, credits and volatilities: A multivariate analysis of the European market during the subprime crisis," International Review of Financial Analysis, Elsevier, vol. 24(C), pages 57-65.
    12. Zhang, Guofu & Du, Ziping, 2017. "Co-movements among the stock prices of new energy, high-technology and fossil fuel companies in China," Energy, Elsevier, vol. 135(C), pages 249-256.
    13. Christoffersen, Peter & Errunza, Vihang & Jacobs, Kris & Jin, Xisong, 2014. "Correlation dynamics and international diversification benefits," International Journal of Forecasting, Elsevier, vol. 30(3), pages 807-824.
    14. Galariotis, Emilios C. & Krokida, Styliani-Iris & Spyrou, Spyros I., 2016. "Herd behavior and equity market liquidity: Evidence from major markets," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 140-149.
    15. Huang, Shupei & An, Haizhong & Huang, Xuan & Jia, Xiaoliang, 2018. "Co-movement of coherence between oil prices and the stock market from the joint time-frequency perspective," Applied Energy, Elsevier, vol. 221(C), pages 122-130.
    16. 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.
    17. Syriopoulos, Theodore & Makram, Beljid & Boubaker, Adel, 2015. "Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 7-18.
    18. Shahbaz, Muhammad & Hye, Qazi Muhammad Adnan & Tiwari, Aviral Kumar & Leitão, Nuno Carlos, 2013. "Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 109-121.
    19. MacDonald, Ronald & Sogiakas, Vasilios & Tsopanakis, Andreas, 2018. "Volatility co-movements and spillover effects within the Eurozone economies: A multivariate GARCH approach using the financial stress index," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 17-36.
    20. Bing-Yue Liu & Qiang Ji & Ying Fan, 2017. "A new time-varying optimal copula model identifying the dependence across markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 437-453, March.
    21. Chunxia, Yang & Xueshuai, Zhu & Luoluo, Jiang & Sen, Hu & He, Li, 2016. "Study on the contagion among American industries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 601-612.
    22. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    23. Richard D. F. Harris & Anirut Pisedtasalasai, 2006. "Return and Volatility Spillovers Between Large and Small Stocks in the UK," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(9‐10), pages 1556-1571, November.
    24. Longstaff, Francis A., 2010. "The subprime credit crisis and contagion in financial markets," Journal of Financial Economics, Elsevier, vol. 97(3), pages 436-450, September.
    25. Jovanovic, Franck & Schinckus, Christophe, 2016. "Breaking down the barriers between econophysics and financial economics," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 256-266.
    26. Dhaene, Jan & Linders, Daniël & Schoutens, Wim & Vyncke, David, 2012. "The Herd Behavior Index: A new measure for the implied degree of co-movement in stock markets," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 357-370.
    27. Tamer Kulaksizoglu, 2015. "Lag Order and Critical Values of the Augmented Dickey–Fuller Test: A Replication," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(6), pages 1010-1010, September.
    28. 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.
    29. Taufiq Choudhry & Hao Wu, 2008. "Forecasting ability of GARCH vs Kalman filter method: evidence from daily UK time-varying beta," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(8), pages 670-689.
    30. Eom, Cheoljun & Park, Jong Won, 2017. "Effects of common factors on stock correlation networks and portfolio diversification," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 1-11.
    31. Yaron Leitner, 2005. "Financial Networks: Contagion, Commitment, and Private Sector Bailouts," Journal of Finance, American Finance Association, vol. 60(6), pages 2925-2953, December.
    32. Sui, Guo & Li, Huajiao & Feng, Sida & Liu, Xueyong & Jiang, Meihui, 2018. "Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1501-1512.
    33. Yuanyuan Zhang & Taufiq Choudhry, 2015. "Forecasting the daily dynamic hedge ratios by GARCH models: evidence from the agricultural futures markets," The European Journal of Finance, Taylor & Francis Journals, vol. 21(4), pages 376-399, March.
    34. 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.
    35. Chen, Duanbing & Lü, Linyuan & Shang, Ming-Sheng & Zhang, Yi-Cheng & Zhou, Tao, 2012. "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1777-1787.
    36. Lee, Chien-Chiang & Chang, Chun-Ping & Chen, Pei-Fen, 2008. "Energy-income causality in OECD countries revisited: The key role of capital stock," Energy Economics, Elsevier, vol. 30(5), pages 2359-2373, September.
    37. Bekiros, Stelios D., 2014. "Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 58-69.
    38. Wen, Xiaoqian & Guo, Yanfeng & Wei, Yu & Huang, Dengshi, 2014. "How do the stock prices of new energy and fossil fuel companies correlate? Evidence from China," Energy Economics, Elsevier, vol. 41(C), pages 63-75.
    39. 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.
    40. Pradhan, Rudra P. & Arvin, Mak B. & Ghoshray, Atanu, 2015. "The dynamics of economic growth, oil prices, stock market depth, and other macroeconomic variables: Evidence from the G-20 countries," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 84-95.
    41. Cho, Sungjun & Hyde, Stuart & Nguyen, Ngoc, 2015. "Time-varying regional and global integration and contagion: Evidence from style portfolios," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 109-131.
    42. Lucey, Brian M. & Vigne, Samuel A. & Ballester, Laura & Barbopoulos, Leonidas & Brzeszczynski, Janusz & Carchano, Oscar & Dimic, Nebojsa & Fernandez, Viviana & Gogolin, Fabian & González-Urteaga, Ana , 2018. "Future directions in international financial integration research - A crowdsourced perspective," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 35-49.
    43. Gupta, Rakesh & Guidi, Francesco, 2012. "Cointegration relationship and time varying co-movements among Indian and Asian developed stock markets," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 10-22.
    44. Bouri, Elie & de Boyrie, Maria E. & Pavlova, Ivelina, 2017. "Volatility transmission from commodity markets to sovereign CDS spreads in emerging and frontier countries," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 155-165.
    45. Zhou, Xiangyi & Zhang, Weijin & Zhang, Jie, 2012. "Volatility spillovers between the Chinese and world equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 247-270.
    46. Zhiyuan Pan, 2014. "Modelling tail dependence between energy market and stock markets in the BRIC countries," Applied Economics Letters, Taylor & Francis Journals, vol. 21(11), pages 789-794, July.
    47. Sun, Qingru & Gao, Xiangyun & Wen, Shaobo & Chen, Zhihua & Hao, Xiaoqing, 2018. "The transmission of fluctuation among price indices based on Granger causality network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 36-49.
    48. Sagarika Mishra & Sandip Dhole, 2015. "Stock Price Comovement: Evidence from India," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(5), pages 893-903, September.
    49. Zhang, Wei & Wang, Guanying & Wang, Xingchun & Xiong, Xiong & Lei, Xuan, 2018. "Profitability of reversal strategies: A modified version of the Carhart model in China," Economic Modelling, Elsevier, vol. 69(C), pages 26-37.
    50. Gao, Xiangyun & Fang, Wei & An, Feng & Wang, Yue, 2017. "Detecting method for crude oil price fluctuation mechanism under different periodic time series," Applied Energy, Elsevier, vol. 192(C), pages 201-212.
    51. Reboredo, Juan C., 2015. "Is there dependence and systemic risk between oil and renewable energy stock prices?," Energy Economics, Elsevier, vol. 48(C), pages 32-45.
    52. Ye Fan & Zhicheng Zhang & Xiaoli Zhao & Haitao Yin, 2018. "Interaction between Industrial Policy and Stock Price Volatility: Evidence from China’s Power Market Reform," Sustainability, MDPI, vol. 10(6), pages 1-19, May.
    53. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Volatility spillovers across stock index futures in Asian markets: Evidence from range volatility estimators," Finance Research Letters, Elsevier, vol. 17(C), pages 158-166.
    54. Kazemilari, Mansooreh & Mardani, Abbas & Streimikiene, Dalia & Zavadskas, Edmundas Kazimieras, 2017. "An overview of renewable energy companies in stock exchange: Evidence from minimal spanning tree approach," Renewable Energy, Elsevier, vol. 102(PA), pages 107-117.
    55. Caloia, Francesco Giuseppe & Cipollini, Andrea & Muzzioli, Silvia, 2018. "Asymmetric semi-volatility spillover effects in EMU stock markets," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 221-230.
    56. Gounopoulos, Dimitrios & Molyneux, Philip & Staikouras, Sotiris K. & Wilson, John O.S. & Zhao, Gang, 2013. "Exchange rate risk and the equity performance of financial intermediaries," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 271-282.
    57. Franck Jovanovic & Christophe Schinckus, 2016. "Breaking down the Barriers between Econophysics and Financial Economics," Post-Print hal-03538922, HAL.
    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. 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.
    60. Choudhry, Taufiq & Jayasekera, Ranadeva, 2012. "Comparison of efficiency characteristics between the banking sectors of US and UK during the global financial crisis of 2007–2011," International Review of Financial Analysis, Elsevier, vol. 25(C), pages 106-116.
    61. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Intra- and inter-regional return and volatility spillovers across emerging and developed markets: Evidence from stock indices and stock index futures," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 96-114.
    62. Yuanyuan Zhang & Taufiq Choudhry, 2017. "Forecasting the Daily Time‐Varying Beta of European Banks During the Crisis Period: Comparison Between GARCH Models and the Kalman Filter," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(8), pages 956-973, December.
    63. Zhang, Bo & Qu, Xue & Meng, Jing & Sun, Xudong, 2017. "Identifying primary energy requirements in structural path analysis: A case study of China 2012," Applied Energy, Elsevier, vol. 191(C), pages 425-435.
    64. Zhang, Dayong, 2017. "Oil shocks and stock markets revisited: Measuring connectedness from a global perspective," Energy Economics, Elsevier, vol. 62(C), pages 323-333.
    65. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    66. Redouane Elkamhi & Denitsa Stefanova, 2015. "Dynamic Hedging and Extreme Asset Co-movements," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 743-790.
    67. 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.
    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. Huang, Xiaohong & Huang, Shupei, 2020. "Identifying the comovement of price between China's and international crude oil futures: A time-frequency perspective," International Review of Financial Analysis, Elsevier, vol. 72(C).
    2. 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).
    3. Gao, Yang & Li, Yangyang & Zhao, Chengjie & Wang, Yaojun, 2022. "Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    4. Li, Jingyu & Liu, Ranran & Yao, Yanzhen & Xie, Qiwei, 2022. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19," Resources Policy, Elsevier, vol. 77(C).
    5. Wang, Xiaoxuan & Gao, Xiangyun & Wu, Tao & Sun, Xiaotian, 2022. "Dynamic multiscale analysis of causality among mining stock prices," Resources Policy, Elsevier, vol. 77(C).
    6. Tian, Tingting & Lai, Kee-hung & Wong, Christina W.Y., 2022. "Connectedness mechanisms in the “Carbon-Commodity-Finance” system: Investment and management policy implications for emerging economies," Energy Policy, Elsevier, vol. 169(C).
    7. Huang, Chuangxia & Deng, Yunke & Yang, Xiaoguang & Cao, Jinde & Yang, Xin, 2021. "A network perspective of comovement and structural change: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 76(C).
    8. Hu, Yunchao & Lu, Guibin & Gao, Wenyu, 2022. "A study on China’s systemically important financial institutions based on multi-time scale causality networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    9. Guannan Wang & Juan Meng & Bin Mo, 2023. "Dynamic Volatility Spillover Effects and Portfolio Strategies among Crude Oil, Gold, and Chinese Electricity Companies," Mathematics, MDPI, vol. 11(4), pages 1-25, February.
    10. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    11. Chen, Weidong & Xiong, Shi & Chen, Quanyu, 2022. "Characterizing the dynamic evolutionary behavior of multivariate price movement fluctuation in the carbon-fuel energy markets system from complex network perspective," Energy, Elsevier, vol. 239(PA).
    12. Gao, Yang & Li, Yangyang & Wang, Yaojun, 2021. "Risk spillover and network connectedness analysis of China’s green bond and financial markets: Evidence from financial events of 2015–2020," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    13. Xi, Xian & Gao, Xiangyun & Zhou, Jinsheng & Zheng, Huiling & Ding, Jiazheng & Si, Jingjian, 2021. "Uncovering the impacts of structural similarity of financial indicators on stock returns at different quantile levels," International Review of Financial Analysis, Elsevier, vol. 76(C).
    14. Sun, Qingru & Gao, Xiangyun & An, Haizhong & Guo, Sui & Liu, Xueyong & Wang, Ze, 2021. "Which time-frequency domain dominates spillover in the Chinese energy stock market?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    15. Jingjian, Si & Xiangyun, Gao & Jinsheng, Zhou & Anjian, Wang & Xiaotian, Sun & Yiran, Zhao & Hongyu, Wei, 2023. "The impact of oil price shocks on energy stocks from the perspective of investor attention," Energy, Elsevier, vol. 278(PB).
    16. Deng, Jing & Zheng, Huike & Xing, Xiaoyun, 2023. "Dynamic spillover and systemic importance analysis of global clean energy companies: A tail risk network perspective," Finance Research Letters, Elsevier, vol. 55(PB).
    17. Xing, Xiaoyun & Xu, Zihan & Chen, Ying & Ouyang, WenPei & Deng, Jing & Pan, Huanxue, 2023. "The impact of the Russia–Ukraine conflict on the energy subsector stocks in China: A network-based 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, Weiping & Zhuang, Xintian & Wu, Dongmei, 2020. "Spatial connectedness of volatility spillovers in G20 stock markets: Based on block models analysis," Finance Research Letters, Elsevier, vol. 34(C).
    2. Zhang, Weiping & Zhuang, Xintian & Lu, Yang & Wang, Jian, 2020. "Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework," International Review of Financial Analysis, Elsevier, vol. 71(C).
    3. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    4. Zhang, Weiping & Zhuang, Xintian & Lu, Yang, 2020. "Spatial spillover effects and risk contagion around G20 stock markets based on volatility network," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    5. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les & Xu, Danyang, 2021. "Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 55-81.
    6. Yizhuo Zhang & Rui Chen & Ding Ma, 2020. "A Weighted and Directed Perspective of Global Stock Market Connectedness: A Variance Decomposition and GERGM Framework," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    7. Yarovaya, Larisa & Brzeszczyński, Janusz & Goodell, John W. & Lucey, Brian & Lau, Chi Keung Marco, 2022. "Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    8. Sun, Qingru & Gao, Xiangyun & An, Haizhong & Guo, Sui & Liu, Xueyong & Wang, Ze, 2021. "Which time-frequency domain dominates spillover in the Chinese energy stock market?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    9. Ki-Hong Choi & Ron P. McIver & Salvatore Ferraro & Lei Xu & Sang Hoon Kang, 2021. "Dynamic volatility spillover and network connectedness across ASX sector markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 45(4), pages 677-691, October.
    10. Muhammad Niaz Khan & Suzanne G. M. Fifield & Nongnuch Tantisantiwong & David M. Power, 2022. "Changes in co-movement and risk transmission between South Asian stock markets amidst the development of regional co-operation," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 36(1), pages 87-117, March.
    11. 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.
    12. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    13. 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.
    14. Fu Qiao & Yan Yan, 2020. "How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19," Papers 2007.07487, arXiv.org.
    15. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    16. Liu, Zhenhua & Shi, Xunpeng & Zhai, Pengxiang & Wu, Shan & Ding, Zhihua & Zhou, Yuqin, 2021. "Tail risk connectedness in the oil-stock nexus: Evidence from a novel quantile spillover approach," Resources Policy, Elsevier, vol. 74(C).
    17. Qu, Fang & Chen, Yufeng & Zheng, Biao, 2021. "Is new energy driven by crude oil, high-tech sector or low-carbon notion? New evidence from high-frequency data," Energy, Elsevier, vol. 230(C).
    18. Mbarki, Imen & Khan, Muhammad Arif & Karim, Sitara & Paltrinieri, Andrea & Lucey, Brian M., 2023. "Unveiling commodities-financial markets intersections from a bibliometric perspective," Resources Policy, Elsevier, vol. 83(C).
    19. Stavros Degiannakis, George Filis, and Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    20. Gogolin, Fabian & Kearney, Fearghal & Lucey, Brian M. & Peat, Maurice & Vigne, Samuel A., 2018. "Uncovering long term relationships between oil prices and the economy: A time-varying cointegration analysis," Energy Economics, Elsevier, vol. 76(C), pages 584-593.

    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:finana:v:68:y:2020:i:c:s1057521918305179. 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/620166 .

    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.