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Automatic stock market forecasting system based on extended language template model

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Indexed by:期刊论文

Date of Publication:2011-01-01

Journal:Journal of Information and Computational Science

Included Journals:EI、Scopus

Volume:8

Issue:1

Page Number:112-118

ISSN No.:15487741

Abstract:Time-series forecasting is an important research area in several domains. Recently, natural networks have been very successfully applied in time series to improve multivariate prediction ability. Several neural network models have already been developed for the market prediction. Some are applied to predicting the change of future interest rate and exchange rate; some are applied to recognizing certain price patterns that are characteristic of future price changes. This paper presents a neural network model for technical analysis of stock market, and its application to a buying and selling timing prediction system for stock index of Japan. This paper also describes a natural language generation system using Language Template Model to express prediction information of CSI 300 Index in natural language for non-expert users. This system has evolved to be one of the most comprehensive grammars of English for prediction expressions. The residuals deal with references, appendix, acknowledges, etc. ? 2011 Binary Information Press.

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