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 :
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