Long-range correlations in cryptocurrency markets: A multi-scale DFA approach

IF 2.8 3区物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY

Physica A: Statistical Mechanics and its Applications Pub Date : 2025-01-29 DOI:10.1016/j.physa.2025.130417

Huy Quoc Bui , Christophe Schinckus , Hamdan Al-Jaifi

{"title":"Long-range correlations in cryptocurrency markets: A multi-scale DFA approach","authors":"Huy Quoc Bui , Christophe Schinckus , Hamdan Al-Jaifi","doi":"10.1016/j.physa.2025.130417","DOIUrl":null,"url":null,"abstract":"<div><div>This article investigates the long-range correlations within the cryptocurrency market by investigating the Hurst exponents across multiple time scales for the log-returns of the top five cryptocurrencies (capturing over 70 % of the market capitalization) between 2017 and 2023. The study uncovers several notable insights. An overall analysis indicates the presence of persistent long-range correlations in four out of five cryptocurrencies, with only XRP displaying characteristics of a random walk. A closer look differentiates the dynamics between short-term and long-term scales, revealing that ETH uniquely maintaining a strong persistence in both, unlike the other cryptocurrencies, which show varying behaviors across these scales. Additionally, ETH and XRP show persistent effects in times of market volatility. This reflects temporal patterns within cryptocurrency markets, enhancing the understanding of market behaviour across varying conditions and timescales. Our findings suggest opportunities for using Hurst exponents as tools to monitor trend continuation or reversal, develop asset-specific strategies, and detect systemic risks during extreme market conditions, offering valuable insights for traders and policymakers navigating the cryptocurrency market's inherent volatility</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130417"},"PeriodicalIF":2.8000,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica A: Statistical Mechanics and its Applications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S037843712500069X","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

This article investigates the long-range correlations within the cryptocurrency market by investigating the Hurst exponents across multiple time scales for the log-returns of the top five cryptocurrencies (capturing over 70 % of the market capitalization) between 2017 and 2023. The study uncovers several notable insights. An overall analysis indicates the presence of persistent long-range correlations in four out of five cryptocurrencies, with only XRP displaying characteristics of a random walk. A closer look differentiates the dynamics between short-term and long-term scales, revealing that ETH uniquely maintaining a strong persistence in both, unlike the other cryptocurrencies, which show varying behaviors across these scales. Additionally, ETH and XRP show persistent effects in times of market volatility. This reflects temporal patterns within cryptocurrency markets, enhancing the understanding of market behaviour across varying conditions and timescales. Our findings suggest opportunities for using Hurst exponents as tools to monitor trend continuation or reversal, develop asset-specific strategies, and detect systemic risks during extreme market conditions, offering valuable insights for traders and policymakers navigating the cryptocurrency market's inherent volatility

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Physica A: Statistical Mechanics and its Applications 物理-物理：综合

CiteScore

7.20

自引率

9.10%

发文量

852

审稿时长

6.6 months

期刊介绍： Physica A: Statistical Mechanics and its Applications Recognized by the European Physical Society Physica A publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems by studying the statistical properties of their microscopic constituents. Applications of the techniques of statistical mechanics are widespread, and include: applications to physical systems such as solids, liquids and gases; applications to chemical and biological systems (colloids, interfaces, complex fluids, polymers and biopolymers, cell physics); and other interdisciplinary applications to for instance biological, economical and sociological systems.