Threshold-asymmetric volatility models for integer-valued time seriesopen access
- Authors
- Kim, Deok Ryun; Yoon, Jae Eun; Hwang, Sun Young
- Issue Date
- May-2019
- Publisher
- Korean Statistical Society
- Keywords
- Count data; Integer-valued time series; Threshold integer-valued ARCH; Volatility
- Citation
- Communications for Statistical Applications and Methods, v.26, no.3, pp 295 - 304
- Pages
- 10
- Journal Title
- Communications for Statistical Applications and Methods
- Volume
- 26
- Number
- 3
- Start Page
- 295
- End Page
- 304
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/1853
- DOI
- 10.29220/CSAM.2019.26.3.295
- ISSN
- 2287-7843
- Abstract
- 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. © 2019 The Korean Statistical Society, and Korean International Statistical Society.
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