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A necessary and sufficient condition for the strict stationarity of a family of GARCH processes
Meitz, Mika - Economics Institute for Research (SIR), … - 2005
We consider a family of GARCH(1,1) processes introduced in He and Teräsvirta (1999a). This family contains various … popular GARCH models as special cases. A necessary and sufficient condition for the existence of a strictly stationary …
Persistent link: https://www.econbiz.de/10005423819
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A note on the geometric ergodicity of a nonlinear AR–ARCH model
Meitz, Mika; Saikkonen, Pentti - İktisat Bölümü, İktisadi ve İdari Bilimler Fakültesi - 2010
This note studies the geometric ergodicity of nonlinear autoregressive models with conditionally heteroskedastic errors. A nonlinear autoregression of order p (AR(p)) with the conditional variance specified as the conventional linear autoregressive conditional heteroskedasticity model of order q...
Persistent link: https://www.econbiz.de/10008543442
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Stability of nonlinear AR-GARCH models
Meitz, Mika; Saikkonen, Pentti - Department of Economics, Oxford University - 2007
generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. Conditions under which the model is stable in the …
Persistent link: https://www.econbiz.de/10004977882
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Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models
Meitz, Mika; Saikkonen, Pentti - Department of Economics, Oxford University - 2007
heteroskedasticity (GARCH) and autoregressive conditional duration (ACD) models with possibly complicated non-linear structures. The …
Persistent link: https://www.econbiz.de/10005047884
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Asymptotic Inference in Multiple-Threshold Nonlinear Time Series Models
Li, Dong; Ling, Shiqing; Zakoian, Jean-Michel - Centre de Recherche en Économie et Statistique … - 2013
This paper investigates a class of multiple-threshold models, called Multiple Threshold Double AR (MTDAR) models. A sufficient condition is obtained for the existence and uniqueness of a strictly stationary and ergodic solution to the first-order MTDAR model. We study the Quasi-Maximum...
Persistent link: https://www.econbiz.de/10010747015
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GARCH models without positivity constraints: Exponential or log GARCH?
Francq, Christian; Wintenberger, Olivier; Zakoïan, … - In: Journal of Econometrics 177 (2013) 1, pp. 34-46
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on …, existence of moments, tails) of the EGARCH model, which are already known, with those of an asymmetric version of the log-GARCH …. The quasi-maximum likelihood estimation of the log-GARCH parameters is shown to be strongly consistent and asymptotically …
Persistent link: https://www.econbiz.de/10011052251
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GARCH models without positivity constraints: Exponential or Log GARCH?
Zakoïan, Jean-Michel; Wintenberger, Olivier; Francq, … - Université Paris-Dauphine (Paris IX) - 2013
This paper provides a probabilistic and statistical comparison of the log-GARCH and EGARCH models, which both rely on …, existence of moments, tails) of the EGARCH model, which are already known, with those of an asymmetric version of the log-GARCH …. The quasi-maximum likelihood estimation of the log-GARCH parameters is shown to be strongly consistent and asymptotically …
Persistent link: https://www.econbiz.de/10011072512
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An ARCH model without intercept
Hafner, Christian M.; Preminger, Arie - In: Economics Letters 129 (2015) C, pp. 13-17
While theory of autoregressive conditional heteroskedasticity (ARCH) models is well understood for strictly stationary processes, some recent interest has focused on the nonstationary case. In the classical model including a positive intercept parameter, the volatility process diverges to...
Persistent link: https://www.econbiz.de/10011263447
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Forecasting chaotic systems : the role of local Lyapunov exponents.
Guegan, Dominique; Leroux, Justin - Centre d'Économie de la Sorbonne, Université Paris 1 … - 2008
We propose a novel methodology for forecasting chaotic systems which is based on the nearest-neighbor predictor and improves upon it by incorporating local Lyapunov exponents to correct for its inevitable bias. Using simulated data, we show that gains in prediction accuracy can be substantial....
Persistent link: https://www.econbiz.de/10005670880
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Local Lyapunov exponents: Zero plays no role in Forecasting chaotic systems
Guégan, Dominique; Leroux, Justin - Institut d'Économie Appliquée, HEC Montréal (École … - 2008
We propose a novel methodology for forecasting chaotic systems which uses information on local Lyapunov exponents (LLEs) to improve upon existing predictors by correcting for their inevitable bias. Using simulated data on the nearest-neighbor predictor, we show that accuracy gains can be...
Persistent link: https://www.econbiz.de/10005784548