Quasi-maximum likelihood estimator of Laplace (1, 1) for GARCH models

• Autorzy: Haiyan Xuan , Lixin Song , Muhammad Amin , Yongxia Shi
• Języki publikacji: EN

Abstrakty

EN

This paper studies the quasi-maximum likelihood estimator (QMLE) for the generalized autoregressive conditional heteroscedastic (GARCH) model based on the Laplace (1,1) residuals. The QMLE is proposed to the parameter vector of the GARCH model with the Laplace (1,1) firstly. Under some certain conditions, the strong consistency and asymptotic normality of QMLE are then established. In what follows, a real example with Laplace and normal distribution is analyzed to evaluate the performance of the QMLE and some comparison results on the performance are given. In the end the proofs of some theorem are presented.

Słowa kluczowe

EN

Asymptotic normality; GARCH model; Laplace (1,1); Quasi-maximum likelihood estimator; Strong consistency

Kategorie tematyczne

• 91G70: Statistical methods, econometrics
• 62M10: Time series, auto-correlation, regression, etc.

• Wydawca: De Gruyter Open
• Czasopismo: Open Mathematics
• Rocznik: 2017
• Tom: 15
• Numer: 1
• Strony: 1539-1548

Daty

wydano

2017-01-01

otrzymano

2017-04-20

zaakceptowano

2017-11-09

online

2017-12-29

Twórcy

autor

Haiyan Xuan

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autor

Lixin Song

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autor

Muhammad Amin

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autor

Yongxia Shi

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Identyfikatory

DOI

10.1515/math-2017-0131