IDEAS home Printed from https://ideas.repec.org/p/ind/igiwpp/2015-020.html
   My bibliography  Save this paper

Analyzing the impact of global financial crisis on the interconnectedness of Asian stock markets using network science

Author

Listed:
  • Jitendra Aswani

    (Indira Gandhi Institute of Development Research)

Abstract

As importance of Asian Stock Markets (ASM) has increased after the globalization, it is become significant to know how this network of ASM behaves on the onset of financial crises. For this study, the Global Financial Crisis is considered whose origin was in the developed country, US, unlike the Asian crisis of 1997. To evaluate the impact of financial crisis on the ASM, network theory is used as a tool here. Network modeling of stock markets is useful as it can help to avert the spillover of crises by preventing the stock markets which are highly connected in the network. In this empirical work, weekly indices data from 2000-2013 for fifteen stock markets is used, which is further partitioned into three periods: pre, during and post crisis. This study shows how 13 important stock markets in Asia namely, India, Bangladesh, Philippines, China, Japan, Indonesia, Malaysia, Singapore, Hong Kong, Pakistan, South Korea and Thailand are connected to each other and how India, Japan, Hong Kong and Korea stock market appeared as the systemically important stock markets from them. Introduction of the US stock market into this network gives insight how the US stock market might had connected to systemically important markets which resulted into spread of crisis in the Asian region. Furthermore, using Kruskal algorithm spread of contagion is explained like how it first hit the Hong Kong stock market and from there it proceeds to the other systemic important stock markets like a virus. Addition to that, we quantified the network behavior in the form of metrics such as adjacency matrix, clustering coefficient, degree of nodes and Minimum Spanning Tree (MST), and on the basis of these some of the important questions like which stock markets are highly connected in Asia which if affected can induce the crises in the other stock markets of region are answered. This study can be used for the portfolio optimization as well as for policy making for which network analysis should be conducted on a regular basis.

Suggested Citation

  • Jitendra Aswani, 2015. "Analyzing the impact of global financial crisis on the interconnectedness of Asian stock markets using network science," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2015-020, Indira Gandhi Institute of Development Research, Mumbai, India.
    • Handle: RePEc:ind:igiwpp:2015-020
    as

    Download full text from publisher

    File URL: http://www.igidr.ac.in/pdf/publication/WP-2015-020.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Karolyi, G Andrew & Stulz, Rene M, 1996. "Why Do Markets Move Together? An Investigation of U.S.-Japan Stock Return Comovements," Journal of Finance, American Finance Association, vol. 51(3), pages 951-986, July.
    2. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    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. Siahaan, Andysah Putera Utama & , Rusiadi & Nasution, Muhammad Dharma Tuah Putra & Aryza, Solly, 2018. "Dependence of Poverty Dependence on Indonesian Economic Fundamentals," INA-Rxiv rntey, Center for Open Science.

    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. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    2. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    3. Mun, Kyung-Chun, 2005. "Contagion and impulse response of international stock markets around the 9-11 terrorist attacks," Global Finance Journal, Elsevier, vol. 16(1), pages 48-68, August.
    4. Gagnon, Louis & Karolyi, G. Andrew, 2009. "Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 953-986, August.
    5. Julien Chevallier & Florian Ielpo, 2013. "Volatility spillovers in commodity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 20(13), pages 1211-1227, September.
    6. Pais, Amelia & Stork, Philip A., 2011. "Contagion risk in the Australian banking and property sectors," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 681-697, March.
    7. Cotter, John & Longin, Francois, 2006. "Implied correlation from VaR," MPRA Paper 3506, University Library of Munich, Germany.
    8. Albuquerque, Rui & Ramadorai, Tarun & Watugala, Sumudu W., 2015. "Trade credit and cross-country predictable firm returns," Journal of Financial Economics, Elsevier, vol. 115(3), pages 592-613.
    9. Albuquerque, Rui & Vega, Clara, 2006. "Asymmetric Information in the Stock Market: Economic News and Co-movement," CEPR Discussion Papers 5598, C.E.P.R. Discussion Papers.
    10. David McMillan & Isabel Ruiz & Alan Speight, 2010. "Correlations and spillovers among three euro rates: evidence using realised variance," The European Journal of Finance, Taylor & Francis Journals, vol. 16(8), pages 753-767.
    11. Maximilian-Benedikt Herwarth Kohn & Pedro L. Valls Pereira, 2017. "Speculative bubbles and contagion: Analysis of volatility’s clusters during the DotCom bubble based on the dynamic conditional correlation model," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1411453-141, January.
    12. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 373-401, June.
    13. Thomas J. Flavin & Ekaterini Panopoulou, 2010. "Detecting Shift And Pure Contagion In East Asian Equity Markets: A Unified Approach," Pacific Economic Review, Wiley Blackwell, vol. 15(3), pages 401-421, August.
    14. Jin, Xiaoye & An, Ximeng, 2016. "Global financial crisis and emerging stock market contagion: A volatility impulse response function approach," Research in International Business and Finance, Elsevier, vol. 36(C), pages 179-195.
    15. Reboredo, Juan C., 2012. "Do food and oil prices co-move?," Energy Policy, Elsevier, vol. 49(C), pages 456-467.
    16. Samarakoon, Lalith P., 2017. "Contagion of the eurozone debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 49(C), pages 115-128.
    17. Schmitt, Noemi & Westerhoff, Frank, 2014. "Speculative behavior and the dynamics of interacting stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 262-288.
    18. Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 287-309, March.
    19. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    20. Mohamed El Hedi Arouri & Mondher Bellalah & Duc Khuong Nguyen, 2010. "The comovements in international stock markets: new evidence from Latin American emerging countries," Applied Economics Letters, Taylor & Francis Journals, vol. 17(13), pages 1323-1328.

    More about this item

    Keywords

    Financial Crisis; Stock Markets; Networks; Minimum Spanning Tree;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G1 - Financial Economics - - General Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • P34 - Political Economy and Comparative Economic Systems - - Socialist Institutions and Their Transitions - - - Finance

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ind:igiwpp:2015-020. 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: Shamprasad M. Pujar (email available below). General contact details of provider: https://edirc.repec.org/data/igidrin.html .

    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.