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STRONG CONSISTENCY OF ESTIMATORS FOR MULTIVARIATE ARCH MODELS

445 citations0/0 files storedEconometric Theory

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Financial Risk and Volatility Modeling Stochastic processes and financial applications Advanced Statistical Methods and Models

Abstract

This paper deals with the asymptotic properties of quasi-maximum likelihood estimators for multivariate heteroskedastic models. For a general model, we give conditions under which strong consistency can be obtained; unlike in the current literature, the assumptions on the existence of moments of the error term are weak, and no study of the various derivatives of the likelihood is required. Then, for a particular model, the multivariate GARCH model with constant correlation, we describe the set of parameters where these conditions hold.

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References

1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1995Multivariate Simultaneous Generalized ARCH 1997The variation of certain speculative prices 1992ARCH modeling in finance 1988A Capital Asset Pricing Model with Time-Varying Covariances 1990Stationarity and Persistence in the GARCH(1,1) Model 1994Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator

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