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Measuring the forecasting accuracy of models: evidence from industrialised countries

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  • Athanasios Koulakiotis
  • Apostolos Dasilas

Abstract

This paper uses the approach suggested by Akrigay (1989), Tse and Tung (1992) and Dimson and Marsh (1990) to examine the forecasting accuracy of stock price index models for industrialised markets. The focus of this paper is to compare the Mean Absolute Percentage Error (MAPE) of three models, that is, the Random Walk model, the Single Exponential Smoothing model and the Conditional Heteroskedastic model with the MAPE of the benchmark Naive Forecast 1 case. We do not evidence that a single model to provide better forecasting accuracy results compared to other models.

Suggested Citation

  • Athanasios Koulakiotis & Apostolos Dasilas, 2009. "Measuring the forecasting accuracy of models: evidence from industrialised countries," International Journal of Monetary Economics and Finance, Inderscience Enterprises Ltd, vol. 2(1), pages 44-57.
    • Handle: RePEc:ids:ijmefi:v:2:y:2009:i:1:p:44-57
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    References listed on IDEAS

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    1. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    2. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
    3. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
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