DocumentCode
1679548
Title
The prediction performance of independent factor models
Author
Chan, Lai-Wan
Author_Institution
Comput. Sci. & Eng. Dept., Chinese Univ. of Hong Kong, Shatin, China
Volume
3
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
2515
Lastpage
2520
Abstract
In the literature, independent component analysis (ICA) has been proposed to construct factor models in finance. According to the basic principle, the factors extracted using ICA are expected to be independent of each other. This factor model is hence called the independent factor model, in contrast to the traditional factor models which assumes uncorrelated factors. We analyze and compare the performance of the independent factor model and the traditional factor model based on the prediction ability of the factors. Two examples are given to show that the independent factor model would reduce loss if we have good predictability on one of the factors. On the contrary, the uncorrelated factor model may not benefit from an accurate factor prediction
Keywords
finance; forecasting theory; probability; finance; independent factor models; prediction ability; prediction performance; Accuracy; Computer science; Electronics packaging; Equations; Finance; Independent component analysis; Performance analysis; Portfolios; Predictive models; Security;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007539
Filename
1007539
Link To Document