An application of independent component analysis in the arbitrage pricing theory

被引:3
|
作者
Yip, F [1 ]
Xu, L [1 ]
机构
[1] Chinese Univ Hong Kong, Dept Comp Sci & Engn, Shatin, Hong Kong, Peoples R China
关键词
D O I
10.1109/IJCNN.2000.861471
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Arbitrage Pricing Theory is a normative equilibrium theory, the theory infers that there may be a multitude of risk factors driving asset returns. Broadly speaking, three approaches can be used to identify these factors, they are fundamental model, macroeconomic model and statistical model. In the traditional approach, the statistical model applies principal components analysis (PCA) to decompose covariance matrix of asset returns. In this paper, we will (i) Discuss the relationship between macroeconomic variables and statistical factors. (ii) Apply independent component analysis (ICA) and a newly proposed ICA factor selection criterion in statistical model. Using ICA as a plug-in of statistical model, Experiments have shown that it fives a better indication of the underlying structure of stock market than PCA by using the same number of components.
引用
收藏
页码:279 / 284
页数:6
相关论文
共 50 条