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    The random walk as a forecasting benchmark: drift or no drift?

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    Fulltext not available
    Authors
    Moosa, I.
    Burns, Kelly
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    Moosa, I. and Burns, K. 2016. The random walk as a forecasting benchmark: drift or no drift? Applied Economics. 48 (43): pp. 4131-4142.
    Source Title
    Applied Economics
    DOI
    10.1080/00036846.2016.1153788
    ISSN
    0003-6846
    School
    Curtin Graduate School of Business
    URI
    http://hdl.handle.net/20.500.11937/51456
    Collection
    • Curtin Research Publications
    Abstract

    We examine the proposition that the random walk without drift is more powerful in predicting exchange rates than the random walk with drift. It is demonstrated that there is no theoretical reason why the random walk without drift always outperforms the random walk with drift and that this is an empirical issue. The results show that while the random walk without drift can outperform the random walk with drift in terms of the RMSE, it fails to do so in terms of the ability to predict the direction of change, measures that take into account magnitude and direction, and in terms of profitability. If the drift factor is allowed to change over time by estimating the model in time-varying parameter terms, the random walk with drift performs even better.

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      The Messe-Rogoff puzzle has been a debatable topic since 1983 when Richard Meese and Kenneth Rogoff demonstrated that no exchange rate model can outperform the random walk in out-of-sample forecasting. This finding been ...
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