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Mixed normal conditional heteroskedasticity

Haas, Markus; Mittnik, Stefan; Paolella, Marc S. - Center for Financial Studies - 2002

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the...

Persistent link: https://www.econbiz.de/10010958539

Estimation and testing of dynamic models with generalised hyperbolic innovations

Mencia, Javier F.; Sentana, Enrique - London School of Economics (LSE) - 2004

null hypotheses of multivariate normal and Student t innovations, and decompose them into skewness and kurtosis components …

Persistent link: https://www.econbiz.de/10010884659

Non-Extensitivity versus informative moments for financial models: a unifying framework and empirical results

Herrmann, Klaus - 2009

generalize the notion of GARCH processes in an information-theoretic sense and are able to capture skewness and kurtosis better …

Persistent link: https://www.econbiz.de/10010299757

Robust performance hypothesis testing with smooth functions of population moments

Ledoit, Olivier; Wolf, Michael - 2018

Applied researchers often want to make inference for the difference of a given performance measure for two investment strategies. In this paper, we consider the class of performance measures that are smooth functions of population means of the underlying returns; this class is very rich and...

Persistent link: https://www.econbiz.de/10011969216

Fourth moments of multivariate GARCH processes

Hafner, Christian M. - 2000

provided for the kurtosis and co-kurtosis between components. An impulse response function for kurtosis and co-kurtosis is … defined that allows to analyse the expectation of the (co-)kurtosis conditional on an initial shock. For a bivariate exchange … rate series, these functions indicate that there is a trade-off between conditional variance and conditional kurtosis: the …

Persistent link: https://www.econbiz.de/10010310227

Mixed normal conditional heteroskedasticity

Haas, Markus; Mittnik, Stefan; Paolella, Marc S. - 2002

Persistent link: https://www.econbiz.de/10010317385

Fourth moments of multivariate GARCH processes

HAFNER, Christian - Center for Operations Research and Econometrics (CORE), … - 2001

provided for the kurtosis and co-kurtosis between components. Applications of the results include the definition of impulse … response functions for kurtosis and co-kurtosis, the derivation of the spectral density matrix of the squares and crossproducts …

Persistent link: https://www.econbiz.de/10005008403

Non-Extensitivity versus informative moments for financial models: a unifying framework and empirical results

Herrmann, Klaus - Wirtschafts- und Sozialwissenschaftliche Fakultät, … - 2009

generalize the notion of GARCH processes in an information-theoretic sense and are able to capture skewness and kurtosis better …

Persistent link: https://www.econbiz.de/10008493567

Testing for Changes in the Unconditional Variance of Financial Time Series

Sansó, Andreu; Aragó, Vicent; Carrion, Josep Lluís - Departament d'Economia Aplicada, Facultat de Ciències … - 2003

Inclan and Tiao (1994) proposed a test for the detection of changes of the unconditional variance which has been used in financial time series analysis. In this article we show some serious drawbacks for using this test with this type of data. Specifically, it su.ers important size distortions...

Persistent link: https://www.econbiz.de/10005773037

Uncertainty in Second Moments: Implications for Portfolio Allocation

Cho, David Daewhan - Econometric Society - 2004

This paper investigates the uncertainty in variance and covariance of asset returns. It is commonly believed that these second moments can be estimated very accurately. However, time varying volatility and nonnormality of asset returns can lead to imprecise variance estimates. Using CRSP value...

Persistent link: https://www.econbiz.de/10005130241