ERGODICITY, MIXING, AND EXISTENCE OF MOMENTS OF A CLASS OF MARKOV MODELS WITH APPLICATIONS TO GARCH AND ACD MODELS

By Mika Meitz, Pentti Saikkonen. Econometric Theory, 2008

114 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b1eada0606ec9f5d8c5fe23a17d42e7532e7e0a3

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Citations in the corpus

Autoregressive Conditional Duration Models in Finance: A Survey of the Theoretical and Empirical Literature (2008, background): “Conditions for β-mixing and existence of moments for nonlinear ACD structures have been investigated by Meitz and Saikkonen (2004) for the first order case.”
PARAMETER ESTIMATION IN NONLINEAR AR–GARCH MODELS (2011, unknown): “Specifically, part (a) of Proposition 1 of Meitz and Saikkonen (2008c) now applies with r = 2, and thus the validity of Assumption DGP with r = 2 follows from Theorem 1 of the same paper (cf. the verification of Assumption DGP above).”
ASYMPTOTIC THEORY FOR A FACTOR GARCH MODEL (2009, background): “Hence, by Meitz and Saikkonen (2004) we also have that fytg is geometrically ergodic and Ejytjr < 1.”
Stability of nonlinear AR‐GARCH models (2008, unknown): “Then the analysis can be reduced to that of the process Yt which is a Markov chain and one can employ the ideas in Cline and Pu (1998) and Lu (1998) to show irreducibility and aperiodicity.”
MODELING MULTIPLE REGIMES IN FINANCIAL VOLATILITY WITH A FLEXIBLE COEFFICIENT GARCH(1,1) MODEL (2009, methodology): “Finally, the FCGARCH model is encapsulated in the general nonlinear specification of Meitz and Saikkonen (2004).”
Mixing properties of ARCH and time-varying ARCH processes (2011, background): “Related results on mixing for GARCH(p, q) processes can be found in [8, 25, 26, 35] (for an excellent review) and [14, 27] (where mixing of ‘nonlinear’ GARCH(p, q) processes is also considered).”
ECONOMETRIC ANALYSIS OF VOLATILITY COMPONENT MODELS (2014, background): “Note that Yt is irreducible if and only if Φ(Z) and Θ(Z) have no common roots and all the roots to Φ(Z) lie outside the unit circle (see Meyn and Caines (1991), Kristensen (2009)).”
GARCH Models (2010, unknown): “Recently, Meitz and Saikkonen (2008a, 2008b) showed mixing properties under mild moment assumptions for a general class of first-order Markov models, and applied their results to the GARCH(1, 1).”
Copula Methods for Forecasting Multivariate Time Series (2013, unknown): “Results for general classes of univariate nonlinear processes are presented in Carrasco and Chen (2002) and Meitz and Saikkonen (2008), however similar results for the multivariate case are not yet available.”