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Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks

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  • Rakesh K. Bissoondeeal
  • Michail Karoglou
  • Alicia M. Gazely

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.

Suggested Citation

  • Rakesh K. Bissoondeeal & Michail Karoglou & Alicia M. Gazely, 2011. "Forecasting The Uk/Us Exchange Rate With Divisia Monetary Models And Neural Networks," Scottish Journal of Political Economy, Scottish Economic Society, vol. 58(1), pages 127-152, February.
    • Handle: RePEc:bla:scotjp:v:58:y:2011:i:1:p:127-152
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    File URL: http://hdl.handle.net/10.1111/j.1467-9485.2010.00538.x
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    2. Somayeh Kokabisaghi & Mohammadesmaeil Ezazi & Reza Tehrani & Nourmohammad Yaghoubi, 2019. "Sanction or Financial Crisis? An Artificial Neural Network-Based Approach to model the impact of oil price volatility on Stock and industry indices," Papers 1912.04015, arXiv.org, revised Sep 2020.
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    5. Mustafa Ozer & Veysel Inal & Mustafa Kirca, 0. "The Relationship Between the Health Services Price Index and The Real Effective Exchange Rate Index in Turkey: A Frequency Domain Causality Analysis," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(36), pages 21-41, June.

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