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Switching Volatility in Private International Equity Markets

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  • Susmel, Raul

Abstract

This paper analyzes the behavior of time-varying volatility when structural changes are allowed in international stock markets. A model developed by Hamilton and Susmel (1994), the switching autoregressive conditional heteroskedastic (SWARCH) model, which is a more general specification than the popular ARCH model, is used. An exponential SWARCH model is fitted to eight series of weekly returns from international stock markets. Evidence is found for switching volatility for the US, Canada, the UK, and Japan. Under the SWARCH model, it is found that ARCH and asymmetric effects are reduced when a switching regime structure is allowed. The switching model is used to date volatility states in international stock markets. These states are compared and it is concluded that domestic volatility states tend to be independent of foreign volatility states, with the exception of Japan and the UK, and the US and Canada. For these two pairs of series, evidence is found for common volatility states. Copyright @ 2000 by John Wiley & Sons, Ltd. All rights reserved.

Suggested Citation

  • Susmel, Raul, 2000. "Switching Volatility in Private International Equity Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 5(4), pages 265-283, October.
  • Handle: RePEc:ijf:ijfiec:v:5:y:2000:i:4:p:265-83
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    Cited by:

    1. Christiansen, Charlotte, 2008. "Level-ARCH short rate models with regime switching: Bivariate modeling of US and European short rates," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 925-948, December.
    2. Kim, Kyungwon, 2013. "Modeling financial crisis period: A volatility perspective of Credit Default Swap market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 4977-4988.
    3. Kamel Malik Bensafta, 2014. "A Regional Analysis of Markets Uncertainty Spillover," Working Papers halshs-01203692, HAL.
    4. Raggi, Davide & Bordignon, Silvano, 2012. "Long memory and nonlinearities in realized volatility: A Markov switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
    5. Kim Hiang Liow & Qing Ye, 2014. "Switching volatility and cross-market linkages in public property markets," Journal of Property Research, Taylor & Francis Journals, vol. 31(4), pages 287-314, December.
    6. Baele, Lieven, 2005. "Volatility Spillover Effects in European Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(02), pages 373-401, June.
    7. Charfeddine, Lanouar, 2016. "Breaks or long range dependence in the energy futures volatility: Out-of-sample forecasting and VaR analysis," Economic Modelling, Elsevier, vol. 53(C), pages 354-374.
    8. Brunetti, Celso & Scotti, Chiara & Mariano, Roberto S. & Tan, Augustine H.H., 2008. "Markov switching GARCH models of currency turmoil in Southeast Asia," Emerging Markets Review, Elsevier, vol. 9(2), pages 104-128, June.
    9. Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
    10. Charfeddine, Lanouar, 2014. "True or spurious long memory in volatility: Further evidence on the energy futures markets," Energy Policy, Elsevier, vol. 71(C), pages 76-93.
    11. Krause, Timothy & Tse, Yiuman, 2013. "Volatility and return spillovers in Canadian and U.S. industry ETFs," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 244-259.
    12. repec:ipg:wpaper:2014-503 is not listed on IDEAS
    13. Colavecchio, Roberta & Funke, Michael, 2009. "Volatility dependence across Asia-Pacific onshore and offshore currency forwards markets," Journal of Asian Economics, Elsevier, vol. 20(2), pages 174-196, March.
    14. Neda Todorova & Michael Soucek & Eduardo Roca, 2015. "Volatility spillovers from international commodity markets to the Australian equity market," Discussion Papers in Finance finance:201505, Griffith University, Department of Accounting, Finance and Economics.
    15. Blazej Mazur & Mateusz Pipien, 2012. "On the empirical importance of periodicity in the volatility of financial time series," NBP Working Papers 124, Narodowy Bank Polski, Economic Research Department.
    16. Jarl G. Kallberg & Paolo Pasquariello, 2005. "An Examination of the Asian Crisis: Regime Shifts in Currency and Equity Markets," The Journal of Business, University of Chicago Press, vol. 78(1), pages 169-212, January.
    17. George Karathanassis & Vasilios Sogiakas, 2010. "Spill over effects of futures contracts initiation on the cash market: a regime shift approach," Review of Quantitative Finance and Accounting, Springer, vol. 34(1), pages 95-143, January.
    18. Neanidis, Kyriakos C. & Savva, Christos S., 2013. "Macroeconomic uncertainty, inflation and growth: Regime-dependent effects in the G7," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 81-92.
    19. Arago-Manzana, Vicent & Fernandez-Izquierdo, Maria Angeles, 2007. "Influence of structural changes in transmission of information between stock markets: A European empirical study," Journal of Multinational Financial Management, Elsevier, vol. 17(2), pages 112-124, April.
    20. Abounoori, Esmaiel & Elmi, Zahra (Mila) & Nademi, Younes, 2016. "Forecasting Tehran stock exchange volatility; Markov switching GARCH approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 264-282.
    21. Ritab Al-Khouri & Abdulkhader Abdallah, 2012. "Market liberalization and volatility of returns in emerging markets: The case of Qatar Exchange (QSC)," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing, vol. 5(2), pages 106-115, June.
    22. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to evaluate an Early Warning System ?," Working Papers halshs-00450050, HAL.
    23. Błażej Mazur & Mateusz Pipień, 2012. "On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(2), pages 95-116, June.

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