Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v479y2017icp265-278.html
   My bibliography  Save this article

Features of spillover networks in international financial markets: Evidence from the G20 countries

Author

Listed:
  • Liu, Xueyong
  • An, Haizhong
  • Li, Huajiao
  • Chen, Zhihua
  • Feng, Sida
  • Wen, Shaobo
Abstract
The objective of this study is to investigate volatility spillover transmission systematically in stock markets across the G20 countries. To achieve this objective, we combined GARCH-BEKK model with complex network theory using the linkages of spillovers. GARCH-BEKK model was used to capture volatility spillover between stock markets. Then, an information spillover network was built. The data encompass the main stock indexes from 19 individual countries in the G20. To consider the dynamic spillover, the full data set was divided into several sub-periods. The main contribution of this paper is considering the volatility spillover relationships as the edges of a complex network, which can capture the propagation path of volatility spillovers. The results indicate that the volatility spillovers among the stock markets of the G20 countries constitute a holistic associated network, another finding is that Korea acts a role of largest sender in long-term, while Brazil is the largest long-term recipient in the G20 spillover network.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:479:y:2017:i:c:p:265-278
    DOI: 10.1016/j.physa.2017.03.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117302315
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2017.03.016?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. Ben Rejeb, Aymen & Arfaoui, Mongi, 2016. "Financial market interdependencies: A quantile regression analysis of volatility spillover," Research in International Business and Finance, Elsevier, vol. 36(C), pages 140-157.
    2. Todd E. Clark & Stephen J. Terry, 2010. "Time Variation in the Inflation Passthrough of Energy Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1419-1433, October.
    3. Lee, Bong-Soo & Rui, Oliver Meng & Wang, Steven Shuye, 2004. "Information transmission between the NASDAQ and Asian second board markets," Journal of Banking & Finance, Elsevier, vol. 28(7), pages 1637-1670, July.
    4. Jebabli, Ikram & Arouri, Mohamed & Teulon, Frédéric, 2014. "On the effects of world stock market and oil price shocks on food prices: An empirical investigation based on TVP-VAR models with stochastic volatility," Energy Economics, Elsevier, vol. 45(C), pages 66-98.
    5. Keating, John W. & Valcarcel, Victor J., 2015. "The Time-Varying Effects Of Permanent And Transitory Shocks To Real Output," Macroeconomic Dynamics, Cambridge University Press, vol. 19(3), pages 477-507, April.
    6. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    7. 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.
    8. Liu, Li & Wang, Yudong, 2014. "Cross-correlations between spot and futures markets of nonferrous metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 20-30.
    9. Weber, Enzo, 2013. "Simultaneous stochastic volatility transmission across American equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(1), pages 53-60.
    10. Zhang, Bing & Li, Xiao-Ming & He, Fei, 2014. "Testing the evolution of crude oil market efficiency: Data have the conn," Energy Policy, Elsevier, vol. 68(C), pages 39-52.
    11. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    12. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    13. An, Feng & Gao, Xiangyun & Guan, Jianhe & Li, Huajiao & Liu, Qian, 2016. "An evolution analysis of executive-based listed company relationships using complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 276-285.
    14. Bentes, Sonia R., 2015. "Forecasting volatility in gold returns under the GARCH, IGARCH and FIGARCH frameworks: New evidence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 355-364.
    15. 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.
    16. Jin Guo, 2015. "Causal relationship between stock returns and real economic growth in the pre- and post-crisis period: evidence from China," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 12-31, January.
    17. Reboredo, Juan C., 2014. "Volatility spillovers between the oil market and the European Union carbon emission market," Economic Modelling, Elsevier, vol. 36(C), pages 229-234.
    18. John Beirne & Guglielmo Maria Caporale & Marianne Schulze-Ghattas & Nicola Spagnolo, 2013. "Volatility Spillovers and Contagion from Mature to Emerging Stock Markets," Review of International Economics, Wiley Blackwell, vol. 21(5), pages 1060-1075, November.
    19. 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.
    20. Wang, Gang-Jin & Xie, Chi & Jiang, Zhi-Qiang & Eugene Stanley, H., 2016. "Who are the net senders and recipients of volatility spillovers in China’s financial markets?," Finance Research Letters, Elsevier, vol. 18(C), pages 255-262.
    21. Hisashi Tanizaki & Shigeyuki Hamori, 2009. "Volatility transmission between Japan, UK and USA in daily stock returns," Empirical Economics, Springer, vol. 36(1), pages 27-54, February.
    22. Kanokwan Chancharoenchai & Sel Dibooglu, 2006. "Volatility Spillovers and Contagion During the Asian Crisis: Evidence from Six Southeast Asian Stock Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 42(2), pages 4-17, April.
    23. Yuying Yang & Chang Liu & Xiaolei Sun & Jianping Li, 2015. "Spillover effect of international crude oil market on tanker market," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(4/5/6), pages 257-277.
    24. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    25. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    26. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    27. 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.
    28. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2011. "Structural changes and volatility transmission in crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4317-4324.
    29. Cardona, Laura & Gutiérrez, Marcela & Agudelo, Diego A., 2017. "Volatility transmission between US and Latin American stock markets: Testing the decoupling hypothesis," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 115-127.
    30. Go Tamakoshi & Shigeyuki Hamori, 2013. "Volatility and mean spillovers between sovereign and banking sector CDS markets: a note on the European sovereign debt crisis," Applied Economics Letters, Taylor & Francis Journals, vol. 20(3), pages 262-266, February.
    31. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
    32. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    33. Uechi, Lisa & Akutsu, Tatsuya & Stanley, H. Eugene & Marcus, Alan J. & Kenett, Dror Y., 2015. "Sector dominance ratio analysis of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 488-509.
    34. Jian Zhang & Dongxiang Zhang & Juan Wang & Yue Zhang, 2013. "Volatility Spillovers between Equity and Bond Markets: Evidence from G7 and BRICS," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 205-217, December.
    35. An, Haizhong & Zhong, Weiqiong & Chen, Yurong & Li, Huajiao & Gao, Xiangyun, 2014. "Features and evolution of international crude oil trade relationships: A trading-based network analysis," Energy, Elsevier, vol. 74(C), pages 254-259.
    36. Liu, Xiangli & Cheng, Siwei & Wang, Shouyang & Hong, Yongmiao & Li, Yi, 2008. "An empirical study on information spillover effects between the Chinese copper futures market and spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 899-914.
    37. Lean Yu & Jingjing Li & Ling Tang, 2015. "Dynamic volatility spillover effect analysis between carbon market and crude oil market: a DCC-ICSS approach," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(4/5/6), pages 242-256.
    38. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    39. 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.
    40. Yiuman Tse, 1999. "Price discovery and volatility spillovers in the DJIA index and futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(8), pages 911-930, December.
    41. Li, Hong & Majerowska, Ewa, 2008. "Testing stock market linkages for Poland and Hungary: A multivariate GARCH approach," Research in International Business and Finance, Elsevier, vol. 22(3), pages 247-266, September.
    42. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    43. 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.
    44. Sohrab Rafiq, 2014. "What Do Energy Prices Tell Us About UK Inflation?," Economica, London School of Economics and Political Science, vol. 81(322), pages 293-310, April.
    45. Khalfaoui, R. & Boutahar, M. & Boubaker, H., 2015. "Analyzing volatility spillovers and hedging between oil and stock markets: Evidence from wavelet analysis," Energy Economics, Elsevier, vol. 49(C), pages 540-549.
    46. Stavarek, Daniel & Heryan, Tomas, 2012. "Day of the week effect in central European stock markets," MPRA Paper 38431, University Library of Munich, Germany.
    47. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2013. "Intraday volatility spillovers between spot and futures indices: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1795-1802.
    48. Yen-Hsien Lee & Ya-Ling Huang & Chun-Yu Wu, 2014. "Dynamic Correlations and Volatility Spillovers between Crude Oil and Stock Index Returns: The Implications for Optimal Portfolio Construction," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 327-336.
    49. Lo Duca, Marco & Stracca, Livio, 2015. "Worth the hype? The effect of G20 summits on global financial markets," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 192-217.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    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. An, Pengli & Li, Huajiao & Zhou, Jinsheng & Li, Yang & Sun, Bowen & Guo, Sui & Qi, Yajie, 2020. "Volatility spillover of energy stocks in different periods and clusters based on structural break recognition and network method," Energy, Elsevier, vol. 191(C).
    4. 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.
    5. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    6. 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).
    7. 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).
    8. 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.
    9. 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.
    10. Afees A. Salisu & Kazeem Isah, 2017. "Modeling the spillovers between stock market and money market in Nigeria," Working Papers 023, Centre for Econometric and Allied Research, University of Ibadan.
    11. 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).
    12. Cardona, Laura & Gutiérrez, Marcela & Agudelo, Diego A., 2017. "Volatility transmission between US and Latin American stock markets: Testing the decoupling hypothesis," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 115-127.
    13. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    14. Imran Yousaf & Shoaib Ali & Wing-Keung Wong, 2020. "Return and Volatility Transmission between World-Leading and Latin American Stock Markets: Portfolio Implications," JRFM, MDPI, vol. 13(7), pages 1-19, July.
    15. An, Sufang & Gao, Xiangyun & An, Haizhong & An, Feng & Sun, Qingru & Liu, Siyao, 2020. "Windowed volatility spillover effects among crude oil prices," Energy, Elsevier, vol. 200(C).
    16. Khalfaoui, Rabeh, 2018. "Oil–gold time varying nexus: A time–frequency analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 86-104.
    17. Burak Korkusuz & David G. McMillan & Dimos Kambouroudis, 2023. "Complex network analysis of volatility spillovers between global financial indicators and G20 stock markets," Empirical Economics, Springer, vol. 64(4), pages 1517-1537, April.
    18. 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.
    19. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    20. 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.

    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:phsmap:v:479:y:2017:i:c:p:265-278. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.