Stock Prediction Based on Phase Space Reconstruction and Echo State Networks
In this paper a synthetic model for stock prediction is proposed based on phase space reconstruction, Echo State Networks (ESN) and Moving Average Convergence/Divergence (MACD). In this model, time series data is reconstructed in phase space before feeding to the ESN. Guided by the MACD strategy, st...
Main Authors: | Huaguang Zhang, Jiuzhen Liang, Zhilei Chai |
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Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2013-03-01
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Series: | Journal of Algorithms & Computational Technology |
Online Access: | https://doi.org/10.1260/1748-3018.7.1.87 |
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