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Nonlinearity In Exchange Rates: Evidence From African Economies
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In an effort to assess the predictive ability of exchange rate models when data on African countries is sampled, this paper studies nonlinear modelling and prediction of the nominal exchange rate series of the United States dollar to currencies of thirty-eight African states using the smooth transition autoregressive (STAR) model. A three step analysis is undertaken. One, it investigates nonlinearity in all nominal exchange rate series examined using a chain of credible statistical in-sample tests. Significantly, evidence of nonlinear exponential STAR (ESTAR) dynamics is detected across all series. Two, linear models are provided another chance to make it right by shuffling to data on African countries to investigate their predictive power against the tough random walk without drift model. Linear models again failed significantly. Lastly, the predictive ability of nonlinear models against both the random walk without drift and the corresponding linear models is investigated. Nonlinear models display useful forecasting gains over all contending models. 

Place, publisher, year, edition, pages
2016. , 59 p.
Keyword [en]
Nominal Exchange Rates, Linear Models, Random Walk Model, Smooth Transition Autoregressive Model, Linearity Tests, Unit Root Tests, Forecast Evaluation.
National Category
URN: urn:nbn:se:uu:diva-297055OAI: diva2:942430
Educational program
Master Programme in Statistics
2016-06-02, F332, Kyrkogårdsgatan 10, 753 13, Uppsala, 14:15 (English)
Available from: 2016-11-24 Created: 2016-06-21 Last updated: 2016-11-24Bibliographically approved

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Jobe, Ndey Isatou
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