Pattern recognition of the term structure using independent component analysis

Edmond Haocun WU, Leung Ho Philip YU

Research output: Contribution to journalArticles

Abstract

Term structure is a useful curve describing some financial asset as a function of time to maturity or expiration. In this paper, we propose to use Independent Component Analysis (ICA) to model the term structure of multiple yield curves. The idea is that we first employ ICA to decompose the multivariate time series, then we suggest two ICA methods for dimension reduction and pattern recognition of the term structure. We also compare the results by using an alternative method, Principal Component Analysis (PCA). The empirical studies suggest that the proposed ICA approaches outperform PCA methods in modeling the term structure. This model can be used in financial time series analysis as well as related financial applications. Copyright © 2006 World Scientific Publishing Co Pte Ltd.
Original languageEnglish
Pages (from-to)173-188
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume20
Issue number2
DOIs
Publication statusPublished - 2006

Citation

Wu, E. H., & Yu, P. L. H. (2006). Pattern recognition of the term structure using independent component analysis. International Journal of Pattern Recognition and Artificial Intelligence, 20(2), 173-188. doi: 10.1142/S0218001406004594

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