Forecasting the UK/US exchange rate with divisia monetary models and neural networks

Research output: Contribution to journalArticle

Abstract

This paper compares the UK/US exchange rate forecasting performance of linear and nonlinear models based on monetary fundamentals, to a random walk (RW) model. Structural breaks are identified and taken into account. The exchange rate forecasting framework is also used for assessing the relative merits of the official Simple Sum and the weighted Divisia measures of money. Overall, there are four main findings. First, the majority of the models with fundamentals are able to beat the RW model in forecasting the UK/US exchange rate. Second, the most accurate forecasts of the UK/US exchange rate are obtained with a nonlinear model. Third, taking into account structural breaks reveals that the Divisia aggregate performs better than its Simple Sum counterpart. Finally, Divisia-based models provide more accurate forecasts than Simple Sum-based models provided they are constructed within a nonlinear framework.
Original languageEnglish
Pages (from-to)127-152
Number of pages26
JournalScottish Journal of Political Economy
Volume58
Issue number1
Early online date10 Dec 2010
DOIs
Publication statusPublished - Feb 2012

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