Covid-19 impact on Cryptocurrencies market using Multivariate Time Series Models

【Author】 Nitithumbundit, Thanakorn; Chan, Jennifer S. K.

【Source】QUARTERLY REVIEW OF ECONOMICS AND FINANCE

【影响因子】4.324

【Abstract】The ever-growing volume of cryptocurrency transactions indicates the importance to understand the new cryptocurrency market. Many research works have demonstrated the unique features of cryptocurrency market compared to other asset markets. Under the impact of Covid-19, the cryptocurrency market may display more differential features. We analyse these differential features of the cryptocurrency market by studying their return persistence, return asymmetry, interdependency, and volatility spillover. The vector autoregressive moving average model with variance gamma innovations is proposed to capture these features before and during the pandemic outbreak. We consider four cryptocurrencies, namely Bitcoin, Ripple, Dash, and Litecoin which have top market capitalisation. For model estimation, we apply the computational efficient expectation/conditional maximisation algorithm. We interpret the results con-cerning their technological setups.(c) 2022 Board of Trustees of the University of Illinois. Published by Elsevier Inc. All rights reserved.

【Keywords】Mutlivariate skewed variance gamma; distribution; Vector ARMA model; Covid-19 impact; ECM algorithm; Cryptocurrencies

【发表时间】2022 NOV

【收录时间】2022-09-22

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-市场分析