Financial time series forecasting with a bio-inspired fuzzy model

Authors:
José Luis Aznarte;JesúS Alcalá-Fdez;Antonio Arauzo-Azofra;José Manuel BeníTez
Affiliations:
Center for Energy and Processes (CEP), Mines ParisTECH, Sophia Antipolis, France;Department of Computer Science and Artificial Intelligence, University of Granada, Spain;Department of Civil Engineering, University of Córdoba, Spain;Department of Computer Science and Artificial Intelligence, University of Granada, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

In general, times series forecasting is considered as a highly complex problem, which is particularly true for financial time series. In this paper, a fuzzy model evolved through a bio-inspired algorithm is proposed to produce accurate models for the prediction of these time series. The performance of this model is compared to that of a group of state-of-the-art statistical models. A thorough experimental study is designed and carry out in order to assess the merits of the proposal. The experimental results allow us to state that our proposal forecasts consistently outperform the other considered methods.