Threshold-asymmetric volatility models for integer-valued time series

被引：2

作者：

Kim, Deok Ryun ^{[1
,2
]}

Yoon, Jae Eun ^{[1
]}

Hwang, Sun Young ^{[1
]}

机构：

[1] Sookmyung Womens Univ, Dept Stat, Cheongpa Ro 47 Gil 100, Seoul 04310, South Korea

[2] Int Vaccine Inst, Seoul, South Korea

来源：

COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | 2019年 / 26卷 / 03期

基金：

新加坡国家研究基金会;

关键词：

count data; integer-valued time series; threshold integer-valued ARCH; volatility; ZERO-INFLATED POISSON; COUNT DATA;

D O I：

10.29220/CSAM.2019.26.3.295

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This article deals with threshold-asymmetric volatility models for over-dispersed and zero-inflated time series of count data. We introduce various threshold integer-valued autoregressive conditional heteroscedasticity (ARCH) models as incorporating over-dispersion and zero-inflation via conditional Poisson and negative binomial distributions. EM-algorithm is used to estimate parameters. The cholera data from Kolkata in India from 2006 to 2011 is analyzed as a real application. In order to construct the threshold-variable, both local constant mean which is time-varying and grand mean are adopted. It is noted via a data application that threshold model as an asymmetric version is useful in modelling count time series volatility.

引用

页码：295 / 304

页数：10