Markus Haas (Institute of Statistics, University of Munich) Stefan Mittnik (Institute of Statistics, University of Munich, Center for Financial Studies, Frankfurt, and Ifo Institute for Economic Research, Munich) Marc S. Paolella (Swiss Banking Institute, University of Zurich)
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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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Publisher Info
Paper provided by Center for Financial Studies in its series CFS Working Paper Series with number
2006/09.
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data) G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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