Modeling macroeconomic indexes from S&P 500 stocks via arbitrage pricing theory and temporary factor analysis

Author

Tan, Lili ; Xu, Lei

Author_Institution

Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, China

Volume

3

fYear

2001

fDate

2001

Firstpage

1844

Abstract

A macroeconomic prediction model in two steps has been suggested by Xu (2001). First, the APT model on security returns is built based on a so-called temporal factor analysis of factors underlying the returns, with the observation noise and temporal relation taken into consideration. Second, a regression between the macroeconomic indexes and the basic factors is analyzed. In this paper, such a model has been examined via several US macroeconomic indexes from S&P 500 stocks, compared with the results obtained using PCA and ICA

Keywords

financial data processing; neural nets; statistical analysis; APT model; ICA; PCA; S&P 500 stocks; US macroeconomic indexes; arbitrage pricing theory; macroeconomic index modeling; macroeconomic prediction model; neural nets; observation noise; regression; temporal factor analysis; temporal relation; temporary factor analysis; underlying factors; Computer science; Councils; Economic forecasting; Independent component analysis; Macroeconomics; Partial response channels; Predictive models; Pricing; Principal component analysis; Security;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.938443

Filename

938443