Multivariate normal mixture GARCH

Arbeitspapier

We present a multivariate generalization of the mixed normal GARCH model proposed in Haas, Mittnik, and Paolella (2004a). Issues of parametrization and estimation are discussed. We derive conditions for covariance stationarity and the existence of the fourth moment, and provide expressions for the dynamic correlation structure of the process. These results are also applicable to the single-component multivariate GARCH(p, q) model and simplify the results existing in the literature. In an application to stock returns, we show that the disaggregation of the conditional (co)variance process generated by our model provides substantial intuition, and we highlight a number of findings with potential significance for portfolio selection and further financial applications, such as regime-dependent correlation structures and leverage effects.

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• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CFS Working Paper ; No. 2006/09

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Construction and Estimation ; General Financial Markets: General (includes Measurement and Data) ; Portfolio Choice; Investment Decisions
• Subject: Conditional Volatility ; Regime-dependent Correlations ; Leverage Effect ; Multivariate GARCH ; Second-order Dependence

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Haas, Markus ; Mittnik, Stefan ; Paolella, Marc S.
• Event: Veröffentlichung
• (who): Goethe University Frankfurt, Center for Financial Studies (CFS)
• (where): Frankfurt a. M.
• (when): 2006

Further information

• Handle: http://hdl.handle.net/10419/25475
• URN: urn:nbn:de:hebis:30-26004