Empirical likelihood based estimation for a class of functional coefficient ARCH-M models

Peixin Zhao, Yiping Yang and Xiaoshuang Zhou

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 5, 1217-1231

Abstract: A class of functional coefficient ARCH-M models are discussed in this paper. Based on empirical likelihood method, a weighted empirical likelihood estimation procedure is proposed for estimating the functional coefficients. Furthermore, the constructed empirical log-likelihood ratio is shown to be asymptotically chi-squared, and then the pointwise confidence intervals for functional coefficients are constructed. The proposed empirical likelihood estimation method can deal with the heteroscedasticity in ARCH-M model, and is more robust and effective. Some simulations are also undertaken to assess the finite sample performance of the proposed estimation procedure.

Date: 2020
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DOI: 10.1080/03610926.2018.1554139

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