Asymmetric beta-binomial GARCH models for time series with bounded support

Rui Zhang

Applied Mathematics and Computation, 2024, vol. 470, issue C

Abstract: In this paper, we introduce a new class of asymmetric beta-binomial generalized autoregressive conditional heteroscedastic (GARCH) models for bounded integer-valued time series, which can capture the asymmetric impact of positive and negative observations. We study the stationarity conditions of the process and derive the moment and covariance functions. Furthermore, we estimate the unknown parameters using the conditional maximum likelihood (CML) method. The asymptotic properties of the estimators are discussed, as well as their finite-sample performance. Finally, we illustrate the model to real time series data in the field of meteorology.

Keywords: Asymmetric model; Beta-binomial GARCH model; Bounded support; Parameter estimation; Positive and negative observation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:470:y:2024:i:c:s0096300324000286

DOI: 10.1016/j.amc.2024.128556

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