Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-29T00:25:31.588Z Has data issue: false hasContentIssue false

ON THE STATIONARITY OF DYNAMIC CONDITIONAL CORRELATION MODELS

Published online by Cambridge University Press:  06 May 2016

Jean-David Fermanian*
Affiliation:
Crest-Ensae
Hassan Malongo
Affiliation:
Amundi & Univ. Paris Dauphine
*
*Address correspondence to Jean-David Fermanian, 3 avenue Pierre Larousse, 92245 Malakoff cedex, France, e-mail: [email protected].
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

We provide conditions for the existence and the uniqueness of strictly stationary solutions of the usual Dynamic Conditional Correlation GARCH models (DCC-GARCH). The proof is based on Tweedie’s (1988) criteria, after having rewritten DCC-GARCH models as nonlinear Markov chains. We also study the existence of their moments and discuss the tightness of our sufficient conditions.

Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2016 

Footnotes

We thank C. Francq and J.-M. Zakoïan for their valuable remarks and discussions. Moreover, we are grateful to Eric Renault and two anonymous referees, who have proposed a number of ways of improving the article. Finally, the authors thank the Labex “Ecodec” for its support.

References

REFERENCES

Aielli, G.P. (2013) Dynamic Conditional Correlation: on properties and estimation. Journal of Business & Economic Statistics 31, 282299.CrossRefGoogle Scholar
Billio, M. & Caporin, M. (2005) Multivariate Markov switching dynamic conditional correlation GARCH representations for contagion analysis. Statistical Methods & Applications 14, 145161.CrossRefGoogle Scholar
Billio, M., Caporin, M. & Gobbo, M. (2006) Flexible dynamic conditional correlation multivariate GARCH for asset allocation. Applied Financial Economics Letters 2, 123130.CrossRefGoogle Scholar
Bollerslev, T. (1990) Modeling the Coherence in Short Run Nominal Exchange Rates: A Multivariate generalized ARCH Model. The Review of Economics and Statistics 72, 498505.Google Scholar
Bougerol, P. & Picard, N. (1992) Stationarity of GARCH processes and of some nonnegative time series. Journal of Econometrics 52, 17141729.Google Scholar
Boussama, F., Fuchs, F. & Stelzer, R. (2011) Stationarity and Geometric Ergodicity of BEKK Multivariate GARCH Models. Stochastic Processes and their Applications 121, 23312360.CrossRefGoogle Scholar
Cappiello, L., Engle, R.F. & Sheppard, K. (2006) Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics 4, 537572.CrossRefGoogle Scholar
Caporin, M. & McAleer, M. (2013) Ten Things You Should Know about the Dynamic Conditional Correlation Representation. Econometrics 1, 115126.CrossRefGoogle Scholar
Comte, F. & Lieberman, O. (2003) Asymptotic theory for multivariate GARCH processes. Journal of Multivariate Analysis 84, 6184.CrossRefGoogle Scholar
Donald, S.G., Imbens, G.W. & Newey, W.K. (2003) Empirical likelihood estimation and consistent tests with conditional moment restrictions. Journal of Econometrics 117, 5593.CrossRefGoogle Scholar
Douc, R., Moulines, E. & Stoffer, D. (2014) Nonlinear Time Series. Chapman & Hall.CrossRefGoogle Scholar
Engle, R.F. & Kroner, F.K. (1995) Multivariate simultaneous generalized ARCH. Econometric Theory 11, 122150.CrossRefGoogle Scholar
Engle, R.F. & Sheppard, K. (2001) Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH. Working Paper 2001-15, University of California at San Diego.CrossRefGoogle Scholar
Engle, R.F. (2002) Dynamic conditional correlation: a simple class of multivariate GARCH models. Journal of Business and Economic Statistics 20, 339350.CrossRefGoogle Scholar
Fermanian, J.-D. & Malongo, H. (2013) On the link between instantaneous volatilities, switching regime probabilities and correlation dynamics. Working paper Crest.Google Scholar
Francq, C. & Zakoïan, J.-M. (2010) GARCH models. Wiley.CrossRefGoogle Scholar
Franses, P.H. & Hafner, C.M. (2009) A generalized dynamic conditional correlation model: Simulation and application to many assets. Econometric Reviews 28, 612631.Google Scholar
Higham, N.J. (2008) Functions of Matrices. SIAM.Google Scholar
Kasch, M. & Caporin, M. (2013) Volatility threshold dynamic conditional correlations: An international analysis. Journal of Financial Econometrics 11, 706742.CrossRefGoogle Scholar
Ling, S. (1999) On the probabilistic properties of a double threshold ARMA conditional heteroskedastic model. Journal of Applied Probability 36, 688705.CrossRefGoogle Scholar
Ling, S. & McAleer, M. (2003) Asymptotic theory for a vector ARMA-GARCH model. Econometric Theory 19, 280310.CrossRefGoogle Scholar
Lütkepohl, H. (1996) Handbook of Matrices. Wiley.Google Scholar
Newey, W.K. (1997) Convergence rates and asymptotic normality for series estimators. Journal of Econometrics 79, 147168.Google Scholar
Otranto, E. & Bauwens, L. (2015) Modeling the dependence of conditional correlations on volatility. Journal of Business & Economic Statistics. Available online.Google Scholar
Pelletier, D. (2006) Regime Switching for Dynamic Correlations. Journal of Econometrics 131(1–2), 445473.CrossRefGoogle Scholar
Serre, D. (2010) Matrices: Theory and Applications. GTM 216, Springer.Google Scholar
Tse, Y.K. & Tsui, A.K.C. (2002) A multivariate GARCH model with time-varying correlations. Journal of Business and Economic Statistics 20, 351362.CrossRefGoogle Scholar
Tweedie, R.L. (1988) Invariant measure for Markov chains with no irreductibility assumptions. Journal of Applied Probability 25A, 275285.CrossRefGoogle Scholar