Comparison of forecasting methods with an application to predicting excess equity premium

Cheng Hsiao, Shui Ki Wan*

*Corresponding author for this work

    Research output: Contribution to journalJournal articlepeer-review

    2 Citations (Scopus)
    27 Downloads (Pure)


    This paper reviews various forecast methods including combination using theoretically optimal weights and those under model selection approaches. In addition, we suggest two modified simple averaging forecast combination methods - a mean corrected and a mean and scale corrected method. We conclude that due to the fact that real data is usually subject to structural breaks, rolling forecasting scheme has a better performance than fixed window and continuously updating scheme. In addition, methods that use less information appear to perform better than methods using all the sample information about the covariance structure of the available forecasts. The mean and scale corrected simple average approach yield smaller mean squared forecast error than the three widely used regression approaches suggested by Granger and Ramanathan [11].

    Original languageEnglish
    Pages (from-to)1235-1246
    Number of pages12
    JournalMathematics and Computers in Simulation
    Issue number7
    Early online date1 Apr 2010
    Publication statusPublished - Mar 2011

    Scopus Subject Areas

    • Theoretical Computer Science
    • Computer Science(all)
    • Numerical Analysis
    • Modelling and Simulation
    • Applied Mathematics

    User-Defined Keywords

    • Forecast combination


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