Empirical Likelihood-Based Tests for Serial Correlation with Possible Infinite Variance

35 Pages Posted: 28 Sep 2021 Last revised: 2 Aug 2022

See all articles by Yawen Fan

Yawen Fan

Jiangxi University of Finance and Economics

Xiaohui Liu

Jiangxi University of Finance and Economics

Ting Luo

Jiangxi University of Finance and Economics

Yao Rao

The University of Liverpool

Hanqing Li

Jiangxi University of Finance and Economics

Abstract

It is well-known that the presence of serial correlation may result in an inefficient or even biased estimation in time series analysis. In this paper, we consider testing serial correlation when the model error follows a GARCH process which is frequently used in modelling financial data. Two empirical likelihood-based testing statistics are proposed to deal with possible infinite variance issues that may occur. Both statistics are shown to be chi-squared distributed asymptotically under mild conditions. Simulations confirm the good finite sample performance of both tests. Finally, to emphasize the importance of using our tests, we explore the impact of the exchange rate on the stock return using both monthly and daily data from eight countries.

Keywords: Empirical likelihood, GARCH process, Infinite variance, Serial correlation

Suggested Citation

Fan, Yawen and Liu, Xiaohui and Luo, Ting and Rao, Yao and Li, Hanqing, Empirical Likelihood-Based Tests for Serial Correlation with Possible Infinite Variance. Available at SSRN: https://ssrn.com/abstract=3932108

Yawen Fan

Jiangxi University of Finance and Economics ( email )

South Lushan Road
Nanchang, 330013
China

Xiaohui Liu

Jiangxi University of Finance and Economics ( email )

South Lushan Road
Nanchang, Jiangxi 330013
China

Ting Luo

Jiangxi University of Finance and Economics ( email )

South Lushan Road
Nanchang, Jiangxi 330013
China

Yao Rao (Contact Author)

The University of Liverpool ( email )

Chatham Street
The University of Liverpool
Liverpool, L69 7ZH
United Kingdom

Hanqing Li

Jiangxi University of Finance and Economics ( email )

South Lushan Road
Nanchang, Jiangxi 330013
China

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