True or spurious long memory in the cryptocurrency markets: evidence from a multivariate test and other Whittle estimation methods

被引：0

作者：

Ata Assaf

Luis Alberiko Gil-Alana

Khaled Mokni

机构：

[1] University of Balamand,Faculty of Business and Management

[2] Cyprus International Institute of Management (CIIM),Navarra Center for International Development

[3] University of Navara,College of Business Administration

[4] Northern Border University,Institut Supérieur de Gestion de Gabès

[5] Gabès University,undefined

来源：

Empirical Economics | 2022年 / 63卷

关键词：

Cryptocurrency markets; Multivariate long-memory tests; Spurious long memory; Cryptocurrency volatility; C12; C32;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

This paper applies a new proposed multivariate score-type test against spurious long memory to a group of cryptocurrency market returns. The test statistic developed by Sibbertsen et al. (J Econ 203(1): 33–49, 2018) is based on the multivariate local Whittle likelihood function and is proven to be consistent against the alternative two cases of random level shifts and smooth trends. We apply the test to the returns, absolute returns, and modified absolute returns. Overall, the recently developed test statistic fails to reject the null hypothesis of true long memory for most cryptocurrencies, except for the Stellar market. Therefore, applying the new test statistic supports the argument that the long memory in the cryptocurrency markets is real and is not a spurious one. Our results are further supported by applying other consistent local Whittle methods that allow for the estimation of the memory parameter by accounting for the presence of perturbations or low-frequency contaminations.

引用

页码：1543 / 1570

页数：27