Results 201 to 210 of about 1,495 (237)

Limit Theory for Explosive Autoregression Under Conditional Heteroskedasticity

SSRN Electronic Journal, 2017
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Generalized Autoregressive Conditional Heteroskedasticity in Credit Risk Measurement

2009 International Conference on Management and Service Science, 2009
This paper presents a modified model for Chinese credit risk management. The model is based on KMV model with consideration of Generalized Autoregressive Conditional Heteroskedasticit (GARCH). Data used in this research are from the balance sheet and the Chinese stock market. T-tests and ROC curves are employed to analyze the data, examining the model.
ChengQi Ou, Charlene Xie, Jun Xu, YunLiang Hu   +3 more
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Adaptive Test for Periodicity in Autoregressive Conditional Heteroskedastic Processes

Communications in Statistics - Simulation and Computation, 2010
This article is concerned with the periodicity testing problem in Autoregressive Conditional Heteroskedastic (ARCH) process. Adaptive locally asymptotically optimal test is derived, when the innovation density is unspecified but symmetric satisfying only some general technical assumptions, for the null hypothesis of classical ARCH process against an ...
M. Bentarzi, M. Merzougui
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EFFICIENT IV ESTIMATION FOR AUTOREGRESSIVE MODELS WITH CONDITIONAL HETEROSKEDASTICITY

Econometric Theory, 2002
This paper analyzes autoregressive time series models where the errors are assumed to be martingale difference sequences that satisfy an additional symmetry condition on their fourth-order moments. Under these conditions quasi maximum likelihood estimators of the autoregressive parameters are no longer efficient in the generalized method of ...
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Generalized instrumental variables estimation of autoregressive conditional heteroskedastic models

Economics Letters, 1991
Abstract This paper considers an alternative to maximum likelihood (ML) estimation of the autoregressive conditional heteroskedastic (ARCH) model introduced in Engle (1982). Specifically, the analysis demonstrates that Hansen's (1982) generalized method of moments (GMM) procedure can be applied for estimation of ARCH models.
Robert W. Rich, Jennie Raymond, J.S. Butler   +2 more
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Stepwise local influence in generalized autoregressive conditional heteroskedasticity models

Journal of Applied Statistics, 2014
Detection of outliers or influential observations is an important work in statistical modeling, especially for the correlated time series data. In this paper we propose a new procedure to detect patch of influential observations in the generalized autoregressive conditional heteroskedasticity (GARCH) model.
Lei Shi, Md. Mostafizur Rahman, Wen Gan, Jianhua Zhao   +3 more
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Indirect estimation of randomized generalized autoregressive conditional heteroskedastic models

Journal of Statistical Computation and Simulation, 2014
The class of generalized autoregressive conditional heteroskedastic (GARCH) models can be used to describe the volatility with less parameters than autoregressive conditional heteroskedastic (ARCH)-type models, their distributions are heavy-tailed, with time-dependent conditional variance, and are able to model clustering of volatility.
J.M. Sampaio, P.A. Morettin
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Nonlinear models for autoregressive conditional heteroskedasticity [PDF]

, 2011
This paper contains a brief survey of nonlinear models of autore- gressive conditional heteroskedasticity. The models in question are parametric nonlinear extensions of the original model by Engle (1982). After presenting the individual models, linearity testing and parameter estimation are discussed.
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Testing for multivariate autoregressive conditional heteroskedasticity using wavelets

Computational Statistics & Data Analysis, 2006
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Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model

SSRN Electronic Journal, 2008
In this paper, we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new double smooth transition conditional correlation (DSTCC) GARCH model extends the smooth transition conditional correlation (STCC) GARCH model of Silvennoinen and Terasvirta (2005) by including another variable according to which the ...
Silvennoinen, Annastiina, Terasvirta, Timo   +1 more
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