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Price and Volatility Spillovers in the Case of Stock Markets Located in Different Time Zones

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  • Joanna Olbrys

Abstract

This paper investigates the interdependence of price volatility across the U.S. stock market and two emerging markets: Poland and Hungary. Using daily data for countries located in different time zones, we point out the problems caused by the presence of nonsynchronous trading effects. To address this problem we use open-to-close logarithmic returns of major stock market indexes. The asymmetric impact of good and bad news is described by a multivariate exponential general autoregressive conditional heteroskedastic model. We investigate the sample from May 2004 to December 2011. The evidence is that the U.S. prices spill over to other markets. Our results show no pronounced volatility spillovers among the three examined markets. Moreover, we observe the presence of negative asymmetry in the case of all markets.

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Bibliographic Info

Article provided by M.E. Sharpe, Inc. in its journal Emerging Markets Finance and Trade.

Volume (Year): 49 (2013)
Issue (Month): S2 (March)
Pages: 145-157

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Handle: RePEc:mes:emfitr:v:49:y:2013:i:s2:p:145-157

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Web page: http://mesharpe.metapress.com/link.asp?target=journal&id=111024

Related research

Keywords: asymmetry effect; market friction; multivariate EGARCH model. nonsynchronous trading; price and volatility spillovers;

References

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  1. David Büttner & Bernd Hayo, 2008. "EMU-related News and Financial Markets in the Czech Republic, Hungary and Poland," MAGKS Papers on Economics 200815, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  2. Evzen Kocenda & Jan Hanousek, 2010. "Foreign News and Spillovers in Emerging European Stock Markets," William Davidson Institute Working Papers Series wp983, William Davidson Institute at the University of Michigan.
  3. Janusz Brzeszczynski & Aleksander Welfe, 2007. "Are There Benefits from Trading Strategy Based on the Returns Spillovers to the Emerging Stock Markets?: Evidence from Poland," Emerging Markets Finance and Trade, M.E. Sharpe, Inc., vol. 43(4), pages 74-92, August.
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  13. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
  14. Eduard Baumöhl & Tomáš Výrost, 2010. "Stock Market Integration: Granger Causality Testing with Respect to Nonsynchronous Trading Effects," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 60(5), pages 414-425, December.
  15. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-44.
  16. Andre Carvalhal & Beatriz Vaz de Melo Mendes, 2008. "Evaluating the Forecast Accuracy of Emerging Market Stock Returns," Emerging Markets Finance and Trade, M.E. Sharpe, Inc., vol. 44(1), pages 21-40, January.
  17. Tse, Yiuman & Wu, Chunchi & Young, Allan, 2003. "Asymmetric information transmission between a transition economy and the U.S. market: evidence from the Warsaw Stock Exchange," Global Finance Journal, Elsevier, vol. 14(3), pages 319-332, December.
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