A fusion ANFIS model for forecasting EPS of leading industries in Taiwan

Author

Wei, Liang-ying

Author_Institution

Dept. of Inf. Manage., Yuanpei Univ., Hsinchu, Taiwan

Volume

1

fYear

2011

fDate

10-13 July 2011

Firstpage

1

Lastpage

4

Abstract

Earnings per share (EPS) is often regarded as a major indicator for investors to purchase stocks. The traditional approach is to use a conventional linear time series model for EPS prediction. However, the results would be in doubt when the forecasting problems are nonlinear. For this reason, this paper proposes a fusion forecasting model that incorporates an autoregressive model into an adaptive network-based fuzzy inference system (ANFIS) To illustrate the proposed model, 15-quarter EPS data are employed. The experimental results indicate that the proposed model outperforms the listing models.

Keywords

adaptive systems; autoregressive processes; forecasting theory; fuzzy reasoning; purchasing; stock markets; time series; EPS forecasting; Taiwan; adaptive network-based fuzzy inference system; autoregressive model; earnings per share; fusion ANFIS model; linear time series model; stock purchasing; Adaptation models; Adaptive systems; Autoregressive processes; Data models; Forecasting; Predictive models; Time series analysis; Adaptive network-based fuzzy inference system; Autoregressive model; Earning per share;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics (ICMLC), 2011 International Conference on

Conference_Location

Guilin

ISSN

2160-133X

Print_ISBN

978-1-4577-0305-8

Type

conf

DOI

10.1109/ICMLC.2011.6016700

Filename

6016700