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Stationarity and invertibility of a dynamic correlation matrix

McAleer, Michael - 2017 - Revised: September 2017

the stationarity and invertibility conditions of the DCC model. The derivation of DCC from a vector random coefficient … than the returns shocks. The derivation of the regularity conditions, especially stationarity and invertibility, should … than returns shocks, as well as the associated stationarity and invertibility conditions. …

Persistent link: https://www.econbiz.de/10011715983

Weighted temporal utility

Gerber, Anke; Rohde, Kirsten I. M. - 2013

We propose a novel utility representation for preferences over risky timed outcomes. The weighted temporal utility model generalizes many well known utility functions for intertemporal decision making under risk. A decision maker with a weighted temporal utility function can have time consistent...

Persistent link: https://www.econbiz.de/10010224796

A one line derivation of DCC : application of a vector random coefficient moving average process

Hafner, Christian M.; McAleer, Michael - 2014 - Revised: July 2014

stationarity and invertibility conditions. The derivation of DCC from a vector random coefficient moving average process raises …

Persistent link: https://www.econbiz.de/10010374571

Maximum likelihood estimation for correctly specified generalized autoregressive score models : feedback effects, contraction conditions and asymptotic properties

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

The strong consistency and asymptotic normality of the maximum likelihood estimator in observation-driven models usually requires the study of the model both as a filter for the time-varying parameter and as a data generating process (DGP) for observed data. The probabilistic properties of the...

Persistent link: https://www.econbiz.de/10010364739

Maximum likelihood estimation for generalized autoregressive score models

Blasques, Francisco; Koopman, Siem Jan; Lucas, André - 2014

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series models driven by the score function of the predictive likelihood. This class of nonlinear dynamic models includes both new and existing observation driven time series models....

Persistent link: https://www.econbiz.de/10010250505

A stochastic recurrence equation approach to stationarity and phi-mixing of a class of nonlinear ARCH models

Blasques, Francisco; Nientker, Marc - 2017

This article generalises the results of Sadi and Zakoian (2006) to a considerably larger class of nonlinear ARCH models with discontinuities, leverage e ects and robust news impact curves. We propose a new method of proof for the existence of a strictly stationary and phi-mixing solution....

Persistent link: https://www.econbiz.de/10011699508

Consumption and wealth in the long run : an integrated unobserved component approach

Gardberg, Malin; Pozzi, Lorenzo - 2018 - Revision: September 2018

has been suggested in the literature recently - the non-stationarity of the standard "cay" variable cannot be dealt with …

Persistent link: https://www.econbiz.de/10011844588

Dynamic partial correlation models

D'Innocenzo, Enzo; Lucas, André - 2022

recurrence equations, we establish stationarity, ergodicity, and filter invertibility in the multivariate setting using …

Persistent link: https://www.econbiz.de/10013375366

Why frequency matters for unit root testing

Boswijk, Herman Peter; Klaassen, Franc - 2004 - Rev.

It is generally believed that for the power of unit root tests, only the time span and not the observation frequency matters. In this paper we show that the observation frequency does matter when the high-frequency data display fat tails and volatility clustering, as is typically the case for...

Persistent link: https://www.econbiz.de/10011342578