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Deterministic Seasonal Volatility in a Small and Integrated Stock Market: The Case of Sweeden


  • Berg, L.


Using daily data for the Swedish stock market for almost the last two decades no distinct and firm deterministic seasonal pattern for the conditional volatility for the Swedish stock market has been found. The daily turnover in the Swedish stock market has an impact on and eliminates to some extent seasonal patterns in conditional volatility. The daily turnover is a proxy variable used to test the mixture distribution model. According to this model the conditional variance of returns will display a GARCH-pattern of behaviour if the number of trades on the stock market during a day are serially correlated. We can also conclude that a feedback from the US stock market to the conditional volatility in the Swedish market exists, and trading days particularly after holidays has a positive impact on the conditional volatility. The test of the model's s mean equation indicates that the Swedish stock market seems to become more and more information efficient, at least in its weak form, if the 1990's are compared with the 1980's.

Suggested Citation

  • Berg, L., 2000. "Deterministic Seasonal Volatility in a Small and Integrated Stock Market: The Case of Sweeden," Papers 2000:9, Uppsala - Working Paper Series.
  • Handle: RePEc:fth:uppaal:2000:9

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    References listed on IDEAS

    1. Bollerslev, Tim & Ghysels, Eric, 1996. "Periodic Autoregressive Conditional Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(2), pages 139-151, April.
    2. Tim Bollerslev & Robert J. Hodrick, 1992. "Financial Market Efficiency Tests," NBER Working Papers 4108, National Bureau of Economic Research, Inc.
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    4. Hansson, Bjorn & Hordahl, Peter, 1997. " Changing Risk Premia: Evidence from a Small Open Economy," Scandinavian Journal of Economics, Wiley Blackwell, vol. 99(2), pages 335-350, June.
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    7. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    8. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    9. Jose Montalvo, 1999. "Volume versus GARCH effects reconsidered: an application to the Spanish Government Bond Futures Market," Applied Financial Economics, Taylor & Francis Journals, vol. 9(5), pages 469-475.
    10. Lennart Berg & Johan Lyhagen, 1998. "Short and long-run dependence in Swedish stock returns," Applied Financial Economics, Taylor & Francis Journals, vol. 8(4), pages 435-443.
    11. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
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    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions


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