Abstract
In this study, we apply the popular artificial intelligence optimization algorithm– particle swarm optimization (PSO) to search the coefficients of ARMA. Furthermore, this paper proposes a novel hybrid model named Winters-PSOARMA, which integrates the advantages of the Holt-Winters, ARMA and PSO procedures. One case of opening price trend in Shenzhen Stock Market is selected to test the proposed model, and the conventional Winters-ARMA model is chose to compare using the same data series. The forecasting precision MAPE shows that our proposed model is a more effective procedure than Winters-ARMA.
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© 2012 Springer-Verlag Berlin Heidelberg
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Liao, J., Wang, H., Zhu, S. (2012). Winters-ARMA Model Based on PSO and Its Application to Opening Price Trend in Shenzhen Stock Market. In: Qu, X., Yang, Y. (eds) Information and Business Intelligence. IBI 2011. Communications in Computer and Information Science, vol 267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29084-8_39
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DOI: https://doi.org/10.1007/978-3-642-29084-8_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29083-1
Online ISBN: 978-3-642-29084-8
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