STATIONARY ARCH MODELS: DEPENDENCE STRUCTURE AND CENTRAL LIMIT THEOREM

By Liudas Giraitis, Piotr Kokoszka, Remigijus Leipus. Econometric Theory, 2000

277 citations recorded by the source corpus.

Subfields: Finance, Mathematical Physics, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/0355279cab010537482ca4a112ffd797deeb22b5

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Citations in the corpus

Rosenthal-type inequalities for the maximum of partial sums of stationary processes and examples (2011, background): “Theorem 6 applies to the case where (Xi)i∈Z has an ARCH(∞) structure as described by Giraitis et al. (2000), that is Xn = σnηn, with σ 2 n = c+ ∞∑ j=1 cjX 2 n−j , (49) where (ηn)n∈Z is a sequence of i.i.d. centered random variables such that E(η 2 0) = 1, and where c ≥ 0, cj ≥ 0, and ∑ j≥1 cj < 1.”
An Introduction to Univariate GARCH Models (2006, methodology): “The ARCH(∞) representation is useful in considering properties of ARCH and GARCH models such as the existence of moments and long memory; see Giraitis et al. (2000) .”
Quantile spectral analysis for locally stationary time series (2014, background): “Li’s concept was extended by Hagemann (2011), Dette et al.”
Stationarity, Mixing, Distributional Properties and Moments of GARCH(p, q)-Processes (2009, methodology): “This was shown by Giraitis et al. (2000) for m = 2 and observed to extend to hold for general m ≥ 1 by Giraitis et al. (2006).”
Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model (2004, background): “An important related study by Giraitis, Kokoszka and Leipus (2000) (henceforth, GKL) studies the squared process {u2t} itself, and some of our results”
Inequality Constraints in the Fractionally Integrated GARCH Model (2006, background): “ˆ (1) i = ‚ 2 (1)ˆ (1) ii2 + (‚(1) + fi)(igii1) for i ‚ 3 ( 16 )”
A Bernstein type inequality and moderate deviations for weakly dependent sequences (2009, unknown): “Then for all positive sequences an with an → 0 and annγ/(2−γ) → ∞, {σ−1n Sn} satisfies (1.4) with the good rate function I(t) = t2/2.”
Microeconomic Models for Long Memory in the Volatility of Financial Time Series (2001, methodology): “This statistic has uniformly higher power than the KPSS statistic and is less sensitive to the choice of the order q than Lo’s statistic (see Giraitis et al. forthcoming and Kirman and Teyssiere forthcoming). Giraitis et al. (forthcoming) have also shown that this statistic can be used in the detect”
On the Autocorrelation Properties of Long‐Memory GARCH Processes (2004, background): “Finally, it is worth mentioning that Giraitis et al. (2000) have recently studied the properties of infinite-order ARCH processes.”
Robust estimates for GARCH models (2008, background): “see Bollerslev (1986), Nelson (1990), Bougerol and Picard (1992) and Giraitis, Kokoszka and Leipus (2000) .”