SEARCHING FOR DIVISIA/INFLATION RELATIONSHIPS WITH THE AGGREGATE FEEDFORWARD NEURAL NETWORK

Abstract

Divisia component data is used in the training of an Aggregate Feedforward Neural Network (AFFNN), a general-purpose connectionist system designed to assist with data mining activities. The neural network is able to learn the money-price relationship, defined as the relationships between the rate of growth of the money supply and inflation. Learned relationships are expressed in terms of an automatically generated series of human-readable and machine-executable rules, shown to meaningfully and accurately describe inflation in terms of the original values of the Divisia component dataset.

Citation

Schmidt, V.A. and Binner, J.M. (2004), "SEARCHING FOR DIVISIA/INFLATION RELATIONSHIPS WITH THE AGGREGATE FEEDFORWARD NEURAL NETWORK", Binner, J.M., Kendall, G. and Chen, S.-H. (Ed.) Applications of Artificial Intelligence in Finance and Economics (Advances in Econometrics, Vol. 19), Emerald Group Publishing Limited, Leeds, pp. 225-241. https://doi.org/10.1016/S0731-9053(04)19009-9