On the threshold innovation in quasi-likelihood for conditionally heteroscedastic time series. Issue 7 (12th August 2021)

• Record Type: Journal Article
• Authors: Yoon, Jae Eun; Hwang, Sun Young
• Is Part Of: Communications in statistics. Volume 50:Issue 7(2021)
• Page Start: 2042
• Page End: 2053
• Publication Date: 2021-08-12
• Subjects: ARCH -- Asymmetric errors -- Quasi-likelihood -- Threshold-innovation; Primary 62M10; Mathematical statistics -- Periodicals; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5
• DOI: 10.1080/03610918.2019.1593453
• Languages: English
• ISSNs: 0361-0918

Abstract

Abstract: This work considers conditionally heteroscedastic time series with possibly asymmetric errors (e.g., skewed t-distributions). Suppose that the error distribution is unknown and estimating functions, so called quasi-likelihood (QL) scores are employed to estimate parameters. The quasi-likelihood can be regarded as a special case of the Godambe's optimum estimating functions (see, e.g., Hwang and Basawa (2011 )). To capture asymmetry in errors, a threshold-innovation is newly suggested to construct an "optimum" quasi likelihood score. It is shown that the threshold innovation is "better" than the standard innovation especially when errors are asymmetrically distributed. A simulation study is reported and a real data analysis is illustrated.