An evaluation of UK risky money: an artificial intelligence approach. (22nd May 2009)

• Record Type: Journal Article
• Authors: Binner, Jane M.; Gazely, Alicia M.; Kendall, Graham
• Is Part Of: Global business & economics review. Volume 11:Number 1(2009)
• Page Start: 1
• Page End: 18
• Publication Date: 2009-05-22
• Subjects: risky money index -- artificial intelligence: inflation forecasting -- neural networks: evolution strategies -- Bank of England -- Divisia index -- interest rates; Economics -- Periodicals; International economic relations -- Periodicals; 330.5
• Languages: English
• ISSNs: 1097-4954

Abstract

In this paper we compare the performance of three indices in an inflation forecasting experiment. The evidence not only suggests that an evolved neural network is superior to traditionally trained networks in the majority of cases, but also that a risky money index performs at least as well as the Bank of England Divisia index when combined with interest rate information. Notably, the provision of long-term interest rates improves the out-of-sample forecasting performance of the Bank of England Divisia index in all cases examined.