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Forecasting the Spanish Stock Market Returns with Fractional and Non-Fractional Models

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  • Guglielmo Maria Caporale
  • Juncal Cunado
  • Luis A. Gil-Alana

Abstract

Problem statement: The content of this note was to assess the forecasting accuracy of various models of the Spanish stock market returns. Approach: We use daily data on the IBEX 35 for the time period January 4th, 2001-March 28th, 2006 and employ both fractional and non-fractional models. Results: The results on the prediction errors for the out-of-sample forecasts indicate that the fractional models outperform the non-fractional ones. Conclusion: Standard forecasting criteria suggest that the ARFIMA (1, d, 0) model with d = -0.017 and the AR (1) coefficient equal to 0.068 is the best specification for this series. That implies that the stock market prices display a very small degree of mean reversion behavior.

Suggested Citation

  • Guglielmo Maria Caporale & Juncal Cunado & Luis A. Gil-Alana, 2011. "Forecasting the Spanish Stock Market Returns with Fractional and Non-Fractional Models," American Journal of Economics and Business Administration, Science Publications, vol. 3(4), pages 586-588, December.
    • Handle: RePEc:abk:jajeba:ajebasp.2011.586.588
    DOI: 10.3844/ajebasp.2011.586.588
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    References listed on IDEAS

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    1. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
    2. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    3. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2002. "Fractional integration and mean reversion in stock prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(3), pages 599-609.
    4. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
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