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Some distributional properties of monthly stock returns in Sweden 1919-1990

Author

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  • Per Frennberg

    (Department of Economics, University of Lund, Sweden)

  • Björn Hansson

    (Department of Economics, University of Lund, Sweden)

Abstract

This paper examines the distributional properties of a newly constructed dataset oj monthly returns on the Swedish stock market. The standard assumptions that stock returns are log-normally distributed, serially independent, non-seasonal and homoscedastic are all rejected by data. Swedish stock returns are more likely to belong to a peaked and fat-tailed distribution, with positive first order autocorrelation, strong seasonality and changing volatility over time. These results are well in line with what has been reported from other national stock markets. Our major conclusion is that, given the failure of data to meet the usual distributional assumptions in finance, it may be worthwhile to pay more attention to modeling both the return generating process and the volatility generating process for the market index, instead of simply assuming a strict random walk model.

Suggested Citation

  • Per Frennberg & Björn Hansson, 1993. "Some distributional properties of monthly stock returns in Sweden 1919-1990," Finnish Economic Papers, Finnish Economic Association, vol. 6(2), pages 108-122, Autumn.
  • Handle: RePEc:fep:journl:v:6:y:1993:i:2:p:108-122
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    References listed on IDEAS

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    1. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
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    Cited by:

    1. Waldenström, Daniel, 2014. "Swedish Stock and Bond Returns, 1856–2012," Working Paper Series 1027, Research Institute of Industrial Economics.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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