CO-EVOLVING NEURAL NETWORKS WITH EVOLUTIONARY STRATEGIES: A NEW APPLICATION TO DIVISIA MONEY

Jane M. Binner, Graham Kendall and Alicia Gazely

A chapter in Applications of Artificial Intelligence in Finance and Economics, 2004, pp 127-143 from Emerald Group Publishing Limited

Abstract: This work applies state-of-the-art artificial intelligence forecasting methods to provide new evidence of the comparative performance of statistically weighted Divisia indices vis-à-vis their simple sum counterparts in a simple inflation forecasting experiment. We develop a new approach that uses co-evolution (using neural networks and evolutionary strategies) as a predictive tool. This approach is simple to implement yet produces results that outperform stand-alone neural network predictions. Results suggest that superior tracking of inflation is possible for models that employ a Divisia M2 measure of money that has been adjusted to incorporate a learning mechanism to allow individuals to gradually alter their perceptions of the increased productivity of money. Divisia measures of money outperform their simple sum counterparts as macroeconomic indicators.

Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-9053(04)19005-1

DOI: 10.1016/S0731-9053(04)19005-1

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