Abstract
Volatility modelling of asset returns is an important aspect for many financial applications, e.g., option pricing and risk management. GARCH models are usually used to model the volatility processes of financial time series. However, multivariate GARCH modelling of volatilities is still a challenge due to the complexity of parameters estimation. To solve this problem, we suggest using Independent Component Analysis (ICA) for transforming the multivariate time series into statistically independent time series. Then, we propose the ICA-GARCH model which is computationally efficient to estimate the volatilities. The experimental results show that this method is more effective to model multivariate time series than existing methods, e.g., PCA-GARCH.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Alexander, C.O.: Orthogonal GARCH. In: Alexander, C.O. (ed.) Mastering Risk. Financial Times, vol. 2. Prentice Hall, Englewood Cliffs (2001)
Bollerslev, T.: Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics 31(3), 307–327 (1986)
Comon, P.: Independent component analysis: a new concept? Signal Processing 36, 287–314 (1994)
Engle, R.F.: Autoregressive conditional heteroscedasticity with estimates of the variance of the U. K. inflation. Econometrica 50(4), 987–1008 (1982)
Hyvarinen, A.: Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks 10(3), 626–634 (1999)
Hyvarinen, A., Oja, E.: A fast fixed-point algorithm for independent component analysis. Neural Computation 9, 1483–1492 (1997)
Wong, A.S.K., Vlaar, P.J.G.: modelling time-varying correlations of financial markets, WO Research Memoranda (discontinued) 739, Netherlands Central Bank, Research Department (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, E.H.C., Yu, P.L.H. (2005). Volatility Modelling of Multivariate Financial Time Series by Using ICA-GARCH Models. In: Gallagher, M., Hogan, J.P., Maire, F. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2005. IDEAL 2005. Lecture Notes in Computer Science, vol 3578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11508069_74
Download citation
DOI: https://doi.org/10.1007/11508069_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26972-4
Online ISBN: 978-3-540-31693-0
eBook Packages: Computer ScienceComputer Science (R0)