The Performance of Immune Based Neural Network with Financial Time Series Prediction

Abstract

This paper presents the use of immune based neural networks which include multilayer perceptron and functional neural network for the prediction of financial time series signals. Extensive simulations for the prediction of one and five steps ahead of stationary and non-stationary time series were performed which indicate that immune based neural networks in most cases demonstrated advantages in capturing chaotic movement in the financial signals with an improvement in the profit return and rapid convergence over multilayer perceptrons