On-demand forecasting of stock prices using a real-time predictor

被引：23

作者：

Wang, YF ^{[1
]}

机构：

[1] Chang Gung Inst Technol, Dept Informat Management, Taoyuan, Taiwan

来源：

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 2003年 / 15卷 / 04期

关键词：

stock price prediction; gray theory; fuzzy theory; stochastic prediction;

D O I：

10.1109/TKDE.2003.1209017

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a fuzzy stochastic prediction method for real-time predicting of stock prices. A complete contrast to the crisp stochastic method, it requires a fuzzy linguistic summary approach to computing parameters. This approach, which is found to be better than the gray prediction method, can eliminate outliers and limit the data to a normal condition for prediction, with a comparatively very small deviation of 4.5 percent.

引用

页码：1033 / 1037

页数：5

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