Year: 2015
Type: article
Abstract: This paper presents the use of immune-based neural networks that include multilayer perceptron (MLP) 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 MLPs.
Source: Cogent Engineering
Authors: Dhiya Al-Jumeily, Abir J. Hussain
Institution: Liverpool John Moores University
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,165
OpenAlex ID: W1973565866