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dc.contributor.authorMoosa, I.
dc.contributor.authorBurns, Kelly
dc.date.accessioned2017-03-24T11:53:18Z
dc.date.available2017-03-24T11:53:18Z
dc.date.created2017-03-23T06:59:48Z
dc.date.issued2016
dc.identifier.citationMoosa, I. and Burns, K. 2016. The random walk as a forecasting benchmark: drift or no drift? Applied Economics. 48 (43): pp. 4131-4142.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/51456
dc.identifier.doi10.1080/00036846.2016.1153788
dc.description.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.

dc.publisherRoutledge
dc.titleThe random walk as a forecasting benchmark: drift or no drift?
dc.typeJournal Article
dcterms.source.volume48
dcterms.source.number43
dcterms.source.startPage4131
dcterms.source.endPage4142
dcterms.source.issn0003-6846
dcterms.source.titleApplied Economics
curtin.departmentCurtin Graduate School of Business
curtin.accessStatusFulltext not available


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