Paper Info
Title
Comparison of BEKK GARCH and DCC GARCH models: an empirical study
Abstract
Modeling volatility and co-volatility of a few zero-coupon bonds is a fundamental element in the field of fix-income risk evaluation. Multivariate GARCH model (MGARCH), an extension of the well-known univariate GARCH, is one of the most useful tools in modeling the co-movement of multivariate time series with time-varying covariance matrix. Grounded on the review of various formulations of multivariate GARCH model, this paper estimates two MGARCH models, BEKK and DCC form, respectively, based on the data of three AAA-rated Euro zero-coupon bonds with different maturities (6 months/1 year/2 years). Post-model diagnostics indicates satisfying fitting performance of these estimated MGARCH models. Moreover, this paper provides comparison on the goodness of fit and forecasting performances of these forms by adopting the mean absolute error (MAE) criterion. Throughout this application, the conclusion can be drawn that significant fitting and forecasting performances originate from the trade-off between parsimony and flexibility of the MGARCH models.
Year
DOI
Venue
2010
10.1007/978-3-642-17313-4_10
ADMA (2)
Keywords
Field
DocType
post-model diagnostics,multivariate time series,multivariate garch model,dcc form,significant fitting,bekk garch,zero-coupon bond,mgarch model,estimated mgarch model,dcc garch model,fitting performance,empirical study,aaa-rated euro,mean absolute error,covariance matrix,quasi maximum likelihood,garch model,zero coupon bonds,satisfiability,goodness of fit,volatility
Econometrics,Computer science,Multivariate statistics,Covariance matrix,Autoregressive conditional heteroskedasticity,Univariate,Statistics,Volatility (finance),Goodness of fit,Empirical research,Zero-coupon bond
Conference
Volume
Issue
ISSN
6441
PART 2
0302-9743
ISBN
Citations 
PageRank 
3-642-17312-8
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Yiyu Huang100.34
Wenjing Su281.56
Xiang Li311011.84