Physica A: Statistical Mechanics and its Applications最新文献

{"title":"Traffic safety evaluation for mixed traffic flow caused by degradation of connected automated vehicles","authors":"Mengya Zhang ,&nbsp;Nobuhiro Uno ,&nbsp;Xiaoguang Yang","doi":"10.1016/j.physa.2025.130353","DOIUrl":"10.1016/j.physa.2025.130353","url":null,"abstract":"<div><div>The mixed traffic flow, characterized by the coexistence of different vehicle types such as human-driven vehicles (HDVs) and connected automated vehicles (CAVs), presents new challenges in terms of traffic safety, particularly due to the degradation effect observed when CAVs follow HDVs. Understanding the traffic risks associated with different car-following modes in mixed traffic flow is essential for ensuring an efficient and safe transportation system. This study aims to assess the traffic risks by considering the heterogeneity of vehicle types and their corresponding car-following behaviors. First, an improved Intelligent driver model (IDM), CACC model, and ACC model are established to describe the driving behaviors of HDVs, normal CAVs (NCAVs), and degraded CAVs (DCAVs), respectively, while considering perception-reaction time (PRT). Second, three kinds of surrogated safety measures of the collision risk, namely time-based indicator, space-based indicator, and deceleration-based indicator, are introduced for quantifying the collision risks on highways. Finally, the impact of PRT, the penetration rate of CAVs, and the platoon intensity on the safety of mixed traffic flow are evaluated based on a numerical simulation. The results indicate that the influence of different car-following modes on the safety of mixed traffic flow is closely related to the PRT of CAVs and the platoon intensity. The stability of mixed traffic flows with DCAVs following HDVs is not superior to that of fully HDVs. When the proportion of DCAVs reaches its maximum, the safety of the platoon is at its worst. Increasing platoon intensity and penetration rate can reduce accident risk, with the effect of penetration rate being more significant than that of platoon intensity.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130353"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143160754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Information cocooning and polarization of opinions in a mobile population","authors":"Dong Jiang ,&nbsp;Qionglin Dai ,&nbsp;Haihong Li ,&nbsp;Junzhong Yang","doi":"10.1016/j.physa.2024.130322","DOIUrl":"10.1016/j.physa.2024.130322","url":null,"abstract":"<div><div>Information cocooning, referring to the phenomena that individuals become trapped in self-imposed cocoons by only encountering and accepting information that aligns with their own opinions, may hinder the normal dissemination of information. Numerous studies focused on how information cocoons emerge and how to avoid their disadvantages. In previous works, it is usually assumed that individuals are well-mixed in a population or located statically on certain regular or complex networks. Here, we explore the phenomena of information cocooning and opinion polarization among individuals who exhibit directional migration, favoring movement towards neighbors with similar opinions. In scenarios without migration, the social radius is a pivotal parameter that influences the development of various opinion dynamics, including neutral consensus, radicalization, and polarization. When directional migration is introduced, information cocooning can occur, leading to the fragmentation of the population into distinct opinion clusters that are spatially distant from one another. Within each cluster, radicalization of opinions is a common phenomenon. However, when considering the population as a whole, opinion dynamics may encompass polarization and consensus. We investigate the impact of the social radius and migration speed on the formation of information cocooning. We find that, the number of opinion clusters decreases with the increase of social radius. Moreover, a small social radius leads to more opinion clusters but milder opinions, whereas large ones result in less number of opinion clusters with more individuals holding radical opinions. This work can help us better understand the formation of information cocoons and opinion polarization in real life.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130322"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robustness of multipartite entanglement in W and Greenberger–Horne–Zeilinger mixed states","authors":"Guo-Lin Lv ,&nbsp;Zhen Zhu ,&nbsp;Maoke Miao ,&nbsp;Bo Liu ,&nbsp;Xiao-Yu Chen","doi":"10.1016/j.physa.2024.130309","DOIUrl":"10.1016/j.physa.2024.130309","url":null,"abstract":"<div><div>Quantifying entanglement is an essential endeavor for both quantum foundations and quantum technologies. The robustness is one of the tractable measures for quantifying quantum resources. As many experiments aim at the generation of multipartite entanglement states, we propose a method of calculating the robustness of multipartite entanglement for Greenberger–Horne–Zeilinger (GHZ) and W mixed states. We analytically determine the upper and lower bounds of robustness for three-qubit GHZ and W mixed states, and derive a tractable solution of the robustness bounds for four-qubit GHZ and W mixed states. Our results show that the upper bound matches the lower bound well, which verifies the validity of our methods.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"659 ","pages":"Article 130309"},"PeriodicalIF":2.8,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143161295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The end of hyperbolic growth in human population and CO2 emissions","authors":"Victor M. Yakovenko","doi":"10.1016/j.physa.2025.130412","DOIUrl":"10.1016/j.physa.2025.130412","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Using current empirical data from 10,000 BCE to 2023 CE, we re-examine a hyperbolic pattern of human population growth, which was identified by von Foerster &lt;em&gt;et al.&lt;/em&gt; in 1960 with a predicted singularity in 2026. We find that human population initially grew exponentially in time as &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;∝&lt;/mo&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mi&gt;e&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; with &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;T&lt;/mi&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mn&gt;2080&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; years. This growth then gradually evolved to be super-exponential with a form similar to the Bose function in statistical physics. Around 1700, population growth further accelerated, entering the hyperbolic regime as &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;∝&lt;/mo&gt;&lt;msup&gt;&lt;mrow&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;/mrow&gt;&lt;/msup&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; with the extrapolated singularity year &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mn&gt;2030&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt;, which is close to the prediction by von Foerster &lt;em&gt;et al.&lt;/em&gt; We attribute the switch from the super-exponential to the hyperbolic regime to the onset of the Industrial Revolution and the transition to massive use of fossil fuels. This claim is supported by a linear relation that we find between the increase in the atmospheric CO&lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; level and population from 1700 to 2000. In the 21st century, we observe that the inverse population curve &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mn&gt;1&lt;/mn&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;mi&gt;N&lt;/mi&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; deviates from a straight line and follows a pattern of “avoided crossing” described by the square root of the Lorentzian function. Thus, instead of a singularity, we predict a peak in human population at &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mn&gt;2030&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; of the time width &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;τ&lt;/mi&gt;&lt;mo&gt;=&lt;/mo&gt;&lt;mn&gt;32&lt;/mn&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; years. We also find that the increase in CO&lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; level since 1700 is well fitted by &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;mi&gt;arccot&lt;/mi&gt;&lt;mrow&gt;&lt;mo&gt;[&lt;/mo&gt;&lt;mrow&gt;&lt;mo&gt;(&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;−&lt;/mo&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;mo&gt;)&lt;/mo&gt;&lt;/mrow&gt;&lt;mo&gt;/&lt;/mo&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;τ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;mo&gt;]&lt;/mo&gt;&lt;/mrow&gt;&lt;/mrow&gt;&lt;/math&gt;&lt;/span&gt; with &lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;τ&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;F&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; = 40 years, which implies a peak in the annual CO&lt;span&gt;&lt;math&gt;&lt;msub&gt;&lt;mrow&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mn&gt;2&lt;/mn&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;/math&gt;&lt;/span&gt; emissions at the same year &lt;span&gt;&lt;math&gt;&lt;mrow&gt;&lt;msub&gt;&lt;mrow&gt;&lt;mi&gt;t&lt;/mi&gt;&lt;/mrow&gt;&lt;mrow&gt;&lt;mi&gt;s&lt;/mi&gt;&lt;/mrow&gt;&lt;/msub&gt;&lt;","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130412"},"PeriodicalIF":2.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143271417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"κ-deformed quantum mechanics: Information entropies for the Mathews–Lakshmanan oscillator","authors":"Bruno G. da Costa ,&nbsp;Ignacio S. Gomez ,&nbsp;Mariela Portesi","doi":"10.1016/j.physa.2025.130407","DOIUrl":"10.1016/j.physa.2025.130407","url":null,"abstract":"<div><div>We study the problem of a position-dependent effective mass quantum system by means of the <span><math><mi>κ</mi></math></span>-formalism, focusing on the information entropies for the Mathews–Lakshmanan oscillator. We obtain the Shannon entropy in both position and wave-vector representations, for the ground and first excited states. Furthermore, the classical and semi-classical information entropies are obtained analytically; a logarithmic relationship with energy, that is linked to the anharmonicity of the oscillator, is reported.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130407"},"PeriodicalIF":2.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barrier-crossing driven by fractional Gaussian noise in the context of reactive flux formalism: An exact result","authors":"Evangelos Bakalis,&nbsp;Francesco Zerbetto","doi":"10.1016/j.physa.2025.130413","DOIUrl":"10.1016/j.physa.2025.130413","url":null,"abstract":"<div><div>The problem of barrier-crossing is considered in the case when the surroundings of the barrier maintain some memory, while, at the same time, the heat bath is at equilibrium. The system is modelled by the generalised fractional Langevin equation with the noise term described by fractional Gaussian noise (fGn). The analytical solutions, in the time domain, are given in terms of the multinomial Mittag-Leffler function and the transmission coefficient is expressed in closed form as a function of the friction coefficient, of the barrier height, and of the Hurst exponent. Kramers’ theory rate constant is a special case of the present treatment.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130413"},"PeriodicalIF":2.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the core–periphery and community structure in the financial networks through random matrix theory","authors":"Pawanesh Pawanesh ,&nbsp;Imran Ansari ,&nbsp;Niteesh Sahni","doi":"10.1016/j.physa.2025.130403","DOIUrl":"10.1016/j.physa.2025.130403","url":null,"abstract":"<div><div>In finance, Random Matrix Theory (RMT) is an important tool for filtering out noise from large datasets, revealing true correlations among stocks, and enhancing risk management and portfolio optimization. Therefore, we employ RMT to filter out noise from the full cross-correlation matrix of stock price returns for the NIFTY 200 and NIFTY 500 indices on the National Stock Exchange of India. Next, we apply the network theory tools to analyze market and sector modes as filtered correlation structures to study local interactions within financial networks. This allows us to study the very fundamental properties of networks, such as the core–periphery and the community structure of constructed networks over these filtered modes, and compare the results with the network constructed over the full cross-correlation matrix. The results suggest that the core–periphery structure is contained in the market mode, while the community structure is in the sector mode. Thus, both modes outperform the full cross-correlation in terms of capturing the essential respective structure of the network. Furthermore, we used these insights to build portfolios based on communities of the networks corresponding to the sector mode and the network corresponding to the full cross-correlation matrix. The results suggest that the portfolio constructed on the full cross-correlation-based matrix performs better than the sector mode. These insights provide a greater understanding of RMT application in the financial market.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130403"},"PeriodicalIF":2.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143271419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamics of network structure in cryptocurrency markets during abrupt changes in Bitcoin price","authors":"Nawee Jaroonchokanan ,&nbsp;Amit Sinha ,&nbsp;Sujin Suwanna","doi":"10.1016/j.physa.2025.130404","DOIUrl":"10.1016/j.physa.2025.130404","url":null,"abstract":"<div><div>Network modeling is a powerful approach to study agent interactions that can provide insights into dynamics and behaviors of complex systems. Cryptocurrency market stability can be assessed by analyzing changes in network structures, where cryptocurrencies serve as nodes in the network, and the network’s weights of connectivity represent the strength of their relationships. This study examines the roles of weighting methods — correlation, mutual information, and Fisher information distance (FID) — in constructing cryptocurrency networks, and how they perform when abrupt changes occur in the Bitcoin price. Each weighting method offers unique insights into cryptocurrency relationships. Results show that sudden Bitcoin price shifts impact the cryptocurrency network’s structures, including characteristic path length, hubs, and minimum spanning trees, providing insights into market stability and clustering behaviors. Additionally, the Granger causality test reveals that the Bitcoin’s returns drive the cryptocurrency network’s connectivity and structure changes. However, the converse is not true, suggesting that the collective behaviors of cryptocurrencies are strongly influenced by the BTC price movement, but not vice versa. The study highlights weighting methods as valuable tools for network analysis and portfolio management using minimum spanning trees.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130404"},"PeriodicalIF":2.8,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143348350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Line graph neural networks for link weight prediction","authors":"Jinbi Liang ,&nbsp;Cunlai Pu ,&nbsp;Xiangbo Shu ,&nbsp;Yongxiang Xia ,&nbsp;Chengyi Xia","doi":"10.1016/j.physa.2025.130406","DOIUrl":"10.1016/j.physa.2025.130406","url":null,"abstract":"<div><div>In real-world networks, predicting the weight (strength) of links is as crucial as predicting the existence of the links themselves. Previous studies have primarily used shallow graph features for link weight prediction, limiting the prediction performance. In this paper, we propose a new link weight prediction method, namely Line Graph Neural Networks for Link Weight Prediction (LGLWP), which learns intrinsic graph features through deep learning. In our method, we first extract the enclosing subgraph around a target link and then employ a weighted graph labeling algorithm to label the subgraph nodes. Next, we transform the subgraph into the line graph and apply graph convolutional neural networks to learn the node embeddings in the line graph, which can represent the links in the original subgraph. Finally, the node embeddings are fed into a fully-connected neural network to predict the weight of the target link, treated as a regression problem. Our method directly learns link features, surpassing previous methods that splice node features for link weight prediction. Experimental results on six network datasets of various sizes and types demonstrate that our method outperforms state-of-the-art methods.</div></div>","PeriodicalId":20152,"journal":{"name":"Physica A: Statistical Mechanics and its Applications","volume":"661 ","pages":"Article 130406"},"PeriodicalIF":2.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-range correlations in cryptocurrency markets: A multi-scale DFA approach","authors":"Huy Quoc Bui ,&nbsp;Christophe Schinckus ,&nbsp;Hamdan Al-Jaifi","doi":"10.1016/j.physa.2025.130417","DOIUrl":"10.1016/j.physa.2025.130417","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":2.8,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143271421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}