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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 2 Issue 1 pp. 21-28 , 2012

An entropy-LVQ system for S & P500 downward shifts forecasting Pages 21-28 Right click to download the paper Download PDF

Authors: Salim Lahmiri

DOI: 10.5267/j.msl.2011.10.006

Keywords: Forecasting, Loss limit, Neural networks, Stock market

Abstract: The purpose of this paper is to predict the S & P500 down moves with technical analysis indicators using learning vector quantization (LVQ) neural networks and probabilistic neural networks (PNN). In addition, entropy-based input selection technique is employed to improve the prediction accuracies. The out-of-sample simulations show that LVQ outperforms PNN. In addition, the Entropy-LVQ system achieved higher accuracy in comparison with the literature.

How to cite this paper
Lahmiri, S. (2012). An entropy-LVQ system for S & P500 downward shifts forecasting.Management Science Letters , 2(1), 21-28.

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Journal: Management Science Letters | Year: 2012 | Volume: 2 | Issue: 1 | Views: 2935 | Reviews: 0

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