2010 | 5 | 1 | 39-55
Article title

Empirical Analysis of Volatility and Co-movements in Serbian Frontier Financial Market: MGARCH Approach

Title variants
Languages of publication
This article presents an empirical calculation of volatility and co-movements for selected securities listed at the Belgrade Stock Exchange ( It applied multivariate GARCH (MGARCH) models to the analysis of comovements in the Serbian frontier financial market. For the empirical work, bivariate and trivariate versions of the restricted BEKK, DVEC, and CCC models were used. Empirical results showed that MGARCH models overcome the usual concept of the time invariant correlation coefficient. Additionaly, the results show that the conditional variances and covariances between returns on the Serbian financial market exhibit significant changes over time.
Physical description
  • Belgrade Banking Academy, Faculty for Banking, Insurance and Finance, Union University
  • Altay-Salih, A., Pinar M., Leyffer S. 2003. "Constrained Nonlinear Programming for Volatility Estimation with GARCH Models".
  • Baur, D. 2004. "A Flexible Dynamic Correlation Model". Working Paper.
  • Bauwens, L., Laurent S. and Rombouts J. V. K. 2006. "Multivariate GARCH models: A Survey". Journal of Applied Econometrics: 79-109
  • Bollerslev, T. 1986. "Generalized Autoregressive Conditional Heteroskedasticity", Journal of Econometrics 31:307-327.[WoS][Crossref]
  • Bollerslev T., R. F. Engle, and J. M. Wooldridge. 1988. "A Capital Asset Pricing Model with Time-Varying Covariances", Journal of Political Economy 96 (1): 116-131.[Crossref]
  • Brooks, C. 2002. Introductory Econometrics for Finance. Cambridge University Press
  • Brooks, C., Burke S., Persand G. 2003. "Multivariate GARCH Models: Software Choice and Estimation Issues". Journal of Applied Econometrics 18: 725-234.[WoS][Crossref]
  • De Goeij, P., Marquering W. 2004. "Modeling the Conditional Covariance Between Stock and Bond Returns: A Multivariate GARCH Approach". Journal of Financial Econometrics 2 (4): 531-564[Crossref]
  • Franke, J., Härdle W., Hafner C. 2005. Introduction to Statistics of Financial Markets.
  • Minović, J. Z. 2007a. "Univariate GARCH models: theoretical survey and application", BALCOR 07, Proceedings of International Conference, Zlatibor, Serbia.
  • Minović, J. 2007b. "Application of multivariate GARCH models in Serbian financial market analysis", Proceedings of International Conference, International Scientific Conference, Faculty of Economics, Belgrade, Serbia.
  • Minović J. Z. 2007c. "Multivariate GARCH models: Theoretical Survey and Model Application", M. Sc. Thesis. University of Belgrade, Faculty of Economics, Belgrade, Serbia.
  • Tsay, R. S. 2005. Analysis of Financial Time Series, Wiley, New Jersey.
  • Tse, Y. K. 2000. "A test for constant correlations in a multivariate GARCH model". Journal of Econometrics 98: 107-127.
  • Tse, Y. K. 2002. "Residual-based diagnostics for conditional heteroscedasticity models". Econometrics Journal 5: 358-373.[Crossref]
  • Tse, Y. K., and Tsui A. K. C. 1999. "A note on diagnosing multivariate conditional heteroscedasticity models". Journal of time series analysis 20 (6): 679-691.
  • Vogelvang, B. 2005. Econometrics: Theory and Applications with EViews. Prentice Hall.
  • Wang, M. and Yao Q. 2005. "Modelling multivariate volatilities: An ad hoc method".
  • Yang, W., David E. A. 2004. "Multivariate GARCH hedge ratios and hedging effectiveness in Australian futures market". Accounting and Finance 45: 301-321.
  • Zivot, E. and Wang J. 2006. Modelling Financial Time Series with S-PLUS. Springer.
  • Quantitative Micro Software. 2005. EViews 5 User's Guide
  • Official the Belgrade stock exchange web site
  • Brokerage web site
Document Type
Publication order reference
YADDA identifier
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.