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A negative binomial integer‐valued GARCH model
Author(s) -
Zhu Fukang
Publication year - 2011
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2010.00684.x
Subject(s) - overdispersion , mathematics , quasi likelihood , negative binomial distribution , poisson distribution , count data , autocorrelation , generalization , autoregressive conditional heteroskedasticity , statistics , binomial test , integer (computer science) , poisson regression , econometrics , computer science , mathematical analysis , programming language , population , demography , sociology , volatility (finance)
This article discusses the modelling of integer‐valued time series with overdispersion and potential extreme observations. For the problem, a negative binomial INGARCH model, a generalization of the Poisson INGARCH model, is proposed and stationarity conditions are given as well as the autocorrelation function. For estimation, we present three approaches with the focus on the maximum likelihood approach. Some results from numerical studies are presented and indicate that the proposed methodology performs better than the Poisson and double Poisson model‐based methods.