Multivariate volatility models are widely used in Finance to capture both volatility clustering and contemporaneous correlation of asset return vectors. Here we focus on multivariate GARCH models. In this common model class it is assumed that the covariance of the error distribution follows a time dependent process conditional on information which is generated by the history of the process. To provide a particular example, we consider a system of exchange rates of two currencies measured against the US Dollar (USD), namely the Deutsche Mark (DEM) and the British Pound Sterling (GBP). for this process we compare the dynamic properties of the bivariate model with univariate GARCH specifications where cross sectional dependencies are ignored. Moreover, we illustrate the scope of the bivariate model by ex-ante forecasts of bivariate exchange rate densities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Bibliography
Baba, Y., Engle, R.F., Kraft, D.F., and Kroner, K.F. (1990). Multivariate Simultaneous Generalized ARCH, mimeo, Department of Economics, University of California, San Diego.
Berndt, E.K., Hall B.H., Hall, R.E., and Hausman, J.A. (1974). Estimation and Inference in Nonlinear Structural Models, Annals of Economic and Social Measurement 3/4: 653-665.
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroscedasticity, Journal of Econometrics 31: 307-327.
Bollerslev, T. (1990). Modeling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized ARCH Approach, Review of Economics and Statistics 72: 498-505.
Bollerslev, T. and Engle, R.F. (1993). Common Persistence in Conditional Variances, Econo-metrica 61: 167-186.
Bollerslev, T., Engle, R.F. and Nelson, D.B. (1994). GARCH Models, in: Engle, R.F., and McFadden, D.L. (eds.) Handbook of Econometrics, Vol. 4, Elsevier, Amsterdam, 2961-3038.
Bollerslev, T., Engle, R.F. and Wooldridge, J.M. (1988). A Capital Asset Pricing Model with Time-Varying Covariances, Journal of Political Economy 96: 116-131.
Bollerslev, T. and Wooldridge, J.M. (1992). Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time-Varying Covariances, Econometric Reviews, 11: 143-172.
Cecchetti, S.G., Cumby, R.E. and Figlewski, S. (1988). Estimation of the Optimal Futures Hedge, Review of Economics and Statistics 70: 623-630.
Comte, F. and Lieberman, O. (2000). Asymptotic Theory for Multivariate GARCH Pro-cesses, Manuscript, Universities Paris 6 and Paris 7.
Engle, R.F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation. Econometrica 50: 987-1008.
Engle, R.F., Ito, T. and Lin, W.L. (1990). Meteor Showers or Heat Waves? Heteroskedastic Intra-Daily Volatility in the Foreign Exchange Market, Econometrica 58: 525-542.
Engle, R.F. and Kroner, K.F. (1995). Multivariate Simultaneous Generalized ARCH, Econo-metric Theory 11: 122-150.
Hafner, C.M. and Herwartz, H. (1998). Structural Analysis of Portfolio Risk using Beta Impulse Response Functions, Statistica Neerlandica 52: 336-355.
Hamao, Y., Masulis, R.W. and Ng, V.K. (1990). Correlations in Price Changes and Volatility across International Stock Markets, Review of Financial Studies 3: 281-307.
Jeantheau, T. (1998). Strong Consistency of Estimators for Multivariate ARCH Models, Econometric Theory 14: 70-86.
Lütkepohl, H. (1996). Handbook of Matrices, Wiley, Chichester.
Nelson, D.B. (1991). Conditional Heteroskedasticity in Asset Returns: A New Approach, Econometrica 59: 347-370.
Tay, A. and Wallis, K. (2000). Density forecasting: A Survey, Journal of Forecasting 19: 235-254.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Berlin Heidelberg
About this chapter
Cite this chapter
Fengler, M.R., Herwartz, H. (2009). Multivariate Volatility Models. In: Härdle, W.K., Hautsch, N., Overbeck, L. (eds) Applied Quantitative Finance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69179-2_15
Download citation
DOI: https://doi.org/10.1007/978-3-540-69179-2_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69177-8
Online ISBN: 978-3-540-69179-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)