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Inter- and intra-regional analysis on spillover effects across international stock markets

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  • Lau, Chi Keung Marco
  • Sheng, Xin

Abstract

This paper examines the inter- and intra-regional spillover effects across international stock markets in London, Paris, Frankfurt, Toronto, New York, Tokyo, Shanghai, Hong Kong, and Mumbai by using both symmetric and asymmetric causality tests. The obtained results show that the inter-regional spillover effect in daytime returns is stronger and more frequent than the intra-regional one. The asymmetric spillover effect is evident for price shocks originating from Asian markets. In addition, the empirical results show that the Shanghai stock market is the least integrated of all nine markets considered.

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  • Lau, Chi Keung Marco & Sheng, Xin, 2018. "Inter- and intra-regional analysis on spillover effects across international stock markets," Research in International Business and Finance, Elsevier, vol. 46(C), pages 420-429.
    • Handle: RePEc:eee:riibaf:v:46:y:2018:i:c:p:420-429
    DOI: 10.1016/j.ribaf.2018.04.013
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    Cited by:

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    2. Hasan Fehmi Baklaci & Tezer Yelkenci, 2022. "Cross-time-frequency analysis of volatility linkages in global currency markets: an extended framework," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(2), pages 267-314, June.
    3. Hazar Altinbas, 2020. "Examining Time-Varying Integrity And Interrelationships Among Global Stock Markets," International Journal of Economic Sciences, International Institute of Social and Economic Sciences, vol. 9(1), pages 1-24, June.
    4. Baklaci, Hasan Fehmi & Aydoğan, Berna & Yelkenci, Tezer, 2020. "Impact of stock market trading on currency market volatility spillovers," Research in International Business and Finance, Elsevier, vol. 52(C).
    5. Paolo Massimo Buscema & Francesca Della Torre & Giulia Massini & Guido Ferilli & Pier Luigi Sacco, 2023. "Reconstructing the Emergent Organization of Information Flows in International Stock Markets: A Computational Complex Systems Approach," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 49-89, June.
    6. Moinak Maiti & Darko Vukovic & Yaroslav Vyklyuk & Zoran Grubisic, 2022. "BRICS Capital Markets Co-Movement Analysis and Forecasting," Risks, MDPI, vol. 10(5), pages 1-13, April.

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    More about this item

    Keywords

    Spillover effects; Asymmetric spillover effects; Information transmission mechanisms; Market efficiency;
    All these keywords.

    JEL classification:

    • 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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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