The prediction of the financial time series based on correlation dimension

被引：0
|
作者：
Feng, C [1 ]
Ji, GR
Zhao, WC
Nian, R
机构：
[1] Ocean Univ China, Coll Informat Sci & Engn, Qingdao 266003, Peoples R China
[2] Qingdao Univ Sci & Technol, Coll Automat & Elect Engn, Qingdao 266042, Peoples R China
来源：
ADVANCES IN NATURAL COMPUTATION, PT 1, PROCEEDINGS | 2005年 / 3610卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we firstly analysis the chaotic characters of three sets of the financial time series (Hang Sheng Index (HIS), Shanghai Stock Index and US gold price) based on the phase space reconstruction. But when we adopt the feedforward neural networks to predict those time series, we found this method run short of a criterion in selecting the training set, so we present a new method: using correlation dimension (CD) as the criterion. By the experiments, the method is proved effective.
引用
收藏
页码：1256 / 1265
页数：10
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