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FORECASTING THE UK/US EXCHANGE RATE WITH DIVISIA MONETARY MODELS AND NEURAL NETWORKS
Author(s) -
Bissoondeeal Rakesh K.,
Karoglou Michail,
Gazely Alicia M.
Publication year - 2011
Publication title -
scottish journal of political economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.4
H-Index - 46
eISSN - 1467-9485
pISSN - 0036-9292
DOI - 10.1111/j.1467-9485.2010.00538.x
Subject(s) - divisia index , exchange rate , economics , econometrics , divisia monetary aggregates index , nonlinear system , simple (philosophy) , aggregate (composite) , monetary policy , mathematics , macroeconomics , central bank , statistics , philosophy , physics , materials science , epistemology , quantum mechanics , quantitative easing , energy (signal processing) , energy intensity , composite material
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.