Causal relationships between cryptocurrencies: the effects of sampling interval and sample size

IF 0.7 4区经济学 Q3 ECONOMICS

Studies in Nonlinear Dynamics and Econometrics Pub Date : 2023-02-27 DOI:10.1515/snde-2022-0054

Nezire Köse, E. Ünal

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引用次数: 1

Abstract

Abstract For this paper, the relationship between seventeen popular cryptocurrencies was analyzed by multivariate Granger causality tests and simple linear regression, using data spanning the period 1 September 2020 to 8 December 2021. The novelty of this work is that it studies the effects of sampling interval and sample size in cryptocurrency markets, which can yield significantly different results. Minute-by-minute, hourly and daily data were collected to examine the Granger causality relationship between cryptocurrencies. It was found that all the currencies demonstrated a significant causality relationship when high frequency (such as minute-by-minute) data was used, in contrast to hourly and daily data. The bigger the sample size, the higher the probability of rejecting the null hypothesis. Hence, the null hypothesis for the Granger causality test can be rejected for minute-by-minute time series data because of too large a sample size. Granger causality test results for hourly and daily data indicated that Bitcoin, Ethereum Classic, and Neo were leading indicators among the cryptocurrencies included in the research. In addition, according to simple linear regression analysis, the short term marginal effect of Bitcoin plays an important role by creating significant impacts on other cryptocurrencies.

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加密货币之间的因果关系：采样间隔和样本量的影响

摘要在本文中，使用2020年9月1日至2021年12月8日期间的数据，通过多元Granger因果关系检验和简单线性回归分析了17种流行加密货币之间的关系。这项工作的新颖之处在于，它研究了加密货币市场中采样间隔和样本量的影响，这可能会产生显著不同的结果。逐分钟、每小时和每天收集数据，以检验加密货币之间的Granger因果关系。研究发现，与每小时和每日数据相比，当使用高频（如逐分钟）数据时，所有货币都表现出显著的因果关系。样本量越大，拒绝零假设的概率就越高。因此，对于逐分钟的时间序列数据，格兰杰因果关系检验的零假设可能会被拒绝，因为样本量太大。Granger每小时和每日数据的因果关系测试结果表明，比特币、以太坊经典和Neo是研究中加密货币的领先指标。此外，根据简单的线性回归分析，比特币的短期边际效应对其他加密货币产生了重大影响，从而发挥了重要作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Studies in Nonlinear Dynamics and Econometrics Multiple-

CiteScore

1.40

自引率

12.50%

发文量

期刊介绍： Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.