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Forecasting Volatility Stock Return: Evidence from the Nordic Stock Exchanges

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Listed:
  • Nikolaos Dritsakis
  • Georgios Savvas

Abstract

The purpose of this study is to explore the volatility and secondary effects in the four Nordic stock exchanges of Norway: Oslo B?rs Linked all-share index AXLT Denmark: OMX Copenhagen 20, Sweden: OMX Stockholm 30 and Finland: OMX Helsinki 25. Keeping in mind that there is an ARCH effect in the returns of the four stock exchanges, we move on to the evaluation to the evaluation of models ARCH (q), GARCH (p, q) kai GARCH-M (p, q). Evaluating the parameters became possible through the use of the maximum likelihood method using the BHHH algorithm of (Berndt et al., 1974) and the three distributions (normal, t-Student, and the Generalized normal distribution GED). The results of this study indicate model ARMA(0,1)-GARCH-M(1,1) with t-student distribution as the appropriate one to describe the returns of the all Nordic stock exchanges except that of Sweden, where model ARMA(0,3)-GARCH-M(1,1) describes it best. Lastly, for forecasting the models ARMA(0,1)-GARCH-M(1,1) and ARMA(0,3)-GARCH-M(1,1) of the current stock exchanges we use both the dynamic and static process. The results of this study indicate that the static process forecasts better than the corresponding dynamic.

Suggested Citation

  • Nikolaos Dritsakis & Georgios Savvas, 2017. "Forecasting Volatility Stock Return: Evidence from the Nordic Stock Exchanges," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(2), pages 15-31, February.
    • Handle: RePEc:ibn:ijefaa:v:9:y:2017:i:2:p:15-31
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    References listed on IDEAS

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    More about this item

    Keywords

    stock returns; GARCH models; forecasting volatility; Nordic stock exchanges; BHHH algorithm;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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