加密货币的流行与其价格、回报和交易量之间的关系:结构断裂和比较分析

IF 0.2 Q4 BUSINESS, FINANCE
Mustafa Özyeşil
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引用次数: 0

摘要

在本研究中,通过时间序列分析,研究了加密货币的受欢迎程度与其价格、回报和交易量之间的关系。流行度变量是根据加密货币在互联网上被搜索的频率确定的。Vogelsang和Perron(1998)的结构断裂ADF单位根检验检验了序列的平稳性。根据测试结果,所有序列在水平值处都是平稳的。VAR分析和脉冲响应函数被执行以揭示系列之间的动态相互作用。根据脉冲响应测试结果,比特币的收益随着互联网上搜索数量的减少而下降,其价格和交易量呈波动过程。为了了解变量之间的因果关系,我们进行了格兰杰因果检验。通过三个不同的方程,采用普通最小二乘(OLS)方法进行回归分析。根据回归分析的结果,发现互联网搜索加密货币数量的增加对所有加密货币的价格,回报和交易量产生了积极影响。对价格和交易量影响最大的是比特币,而对回报影响最大的是莱特币。根据调查结果,受欢迎程度可以被认为是加密货币价格、回报和交易量的重要决定因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Relationship Between the Popularity of Cryptocurrencies and their Prices, Returns and Trading Volumes: A Structural Break and Comparative Analysis
In this study, the relationship between the popularity of cryptocurrencies and their price, return and trading volumes are examined through time series analysis. The popularity variable is determined according the frequency of cryptocurrencies being searched on the internet. Stationarity of series is examined by Vogelsang and Perron (1998) structural breaks ADF unit root test. According to the test results, all series are found to be stationary at level values. VAR analyses and impulse-response functions are performed to reveal dynamic interaction between the series. According to impulse - response test results, returns of BITCOIN decreased against a decreasing shock in the number searches on the internet and its price and trading volume followed a fluctuating course. In order to see the causality relationship between variables the Granger causality test is conducted. Regression analyses are performed using ordinary least squares (OLS) method through three different equations. According to the result of the regression analysis, an increase in the number of internet searches for cryptocurrencies was found to positively affect prices, returns and trading volumes of all cryptocurrencies. The highest impact on prices and trading volume is observed in BITCOIN, while the highest effect on returns is observed in LITECOIN. According to the findings, popularity can be considered an important determinant for price, returns and trading volumes of cryptocurrencies.
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