Complex System Analysis on Voter Stochastic System and Jump Time Effective Neural Network of Stock Market

DOI

10.1080/18756891.2015.1061397How to use a DOI?

Keywords

Prediction, financial time series, voter interacting system, random jump time effective neural network, detrended fluctuation analysis, rescaled range analysis

Abstract

The finite-range voter system, one of stochastic particle systems, is applied to model a financial price process for further description and investigation of fluctuations of Shanghai Composite Index. For different parameter values of the intensity and the range , we investigate the statistical behaviors of the simulation data for this financial model. Then we develop the random jump time effective neural network model to forecast the fluctuations of Shanghai Composite Index. Moreover, we compare the two models by analyzing the returns and the absolute returns of Shanghai Composite Index, the simulation data and the predictive data through Detrended Fluctuation Analysis and classic Rescaled Range Analysis.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Jun Wang
AU  - Huopo Pan
AU  - Yiduan Wang
AU  - Hongli Niu
PY  - 2015
DA  - 2015/08/01
TI  - Complex System Analysis on Voter Stochastic System and Jump Time Effective Neural Network of Stock Market
JO  - International Journal of Computational Intelligence Systems
SP  - 787
EP  - 795
VL  - 8
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2015.1061397
DO  - 10.1080/18756891.2015.1061397
ID  - Wang2015
ER  -