Aknouche, Abdelhakim and Scotto, Manuel (2022): A multiplicative thinningbased integervalued GARCH model.

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Abstract
In this paper we introduce a multiplicative integervalued time series model, which is defined as the product of a unitmean integervalued independent and identically distributed (iid) sequence, and an integervalued dependent process. The latter is defined as a binomial thinning operation of its own past and of the past of the observed process. Furthermore, it combines some features of the integervalued GARCH (INGARCH), the autoregressive conditional duration (ACD), and the integer autoregression (INAR) processes. The proposed model is semiparametric and is able to parsimoniously generate very high overdispersion, persistence, and heavytailedness. The dynamic probabilistic structure of the model is first analyzed. In addition, parameter estimation is considered by using a twostage weighted least squares estimate (2SWLSE), consistency and asymptotic normality (CAN) of which are established under mild conditions. Applications of the proposed formulation to simulated and actual count time series data are provided.
Item Type:  MPRA Paper 

Original Title:  A multiplicative thinningbased integervalued GARCH model 
English Title:  A multiplicative thinningbased integervalued GARCH model 
Language:  English 
Keywords:  Integervalued time series, INAR model, INGARCH model, multiplicative error model (MEM), ACD model, twostage weighted least squares. 
Subjects:  C  Mathematical and Quantitative Methods > C0  General > C01  Econometrics C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C25  Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions ; Probabilities 
Item ID:  112475 
Depositing User:  Prof. Abdelhakim Aknouche 
Date Deposited:  21 Mar 2022 09:50 
Last Modified:  21 Mar 2022 09:50 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/112475 