加密货币联合投资网络:代币回报反映投资模式

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS EPJ Data Science Pub Date : 2024-02-20 DOI:10.1140/epjds/s13688-023-00446-x
Luca Mungo, Silvia Bartolucci, Laura Alessandretti
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引用次数: 0

摘要

自 2009 年比特币问世以来,传统对冲基金和以加密货币为重点的对冲基金的大量投资也推动了加密货币市场剧烈而不稳定的演变。尽管对冲基金发挥了关键作用,但我们对机构投资与加密货币市场演变之间关系的了解仍然有限,这也是由于缺乏描述长期投资的全面数据。在本研究中,我们基于从最大的商业信息收集平台之一 Crunchbase 收集到的 2014 年至 2022 年期间 1324 种货币的数据集,对加密货币机构投资进行了定量研究。我们发现,加密货币市值的变化与机构投资规模高度相关,从而证实了机构投资的重要作用。此外,我们还发现,该市场由一群知名投资者主导,这些投资者往往专注于特定技术。最后,通过研究共享投资者的货币的共同投资网络,我们发现共享投资者的资产往往具有相似的市场行为特征。我们的研究揭示了机构投资者所扮演的角色,为进一步研究他们在加密货币生态系统中的影响力提供了基础。
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Cryptocurrency co-investment network: token returns reflect investment patterns

Since the introduction of Bitcoin in 2009, the dramatic and unsteady evolution of the cryptocurrency market has also been driven by large investments by traditional and cryptocurrency-focused hedge funds. Notwithstanding their critical role, our understanding of the relationship between institutional investments and the evolution of the cryptocurrency market has remained limited, also due to the lack of comprehensive data describing investments over time. In this study, we present a quantitative study of cryptocurrency institutional investments based on a dataset collected for 1324 currencies in the period between 2014 and 2022 from Crunchbase, one of the largest platforms gathering business information. We show that the evolution of the cryptocurrency market capitalization is highly correlated with the size of institutional investments, thus confirming their important role. Further, we find that the market is dominated by the presence of a group of prominent investors who tend to specialise by focusing on particular technologies. Finally, studying the co-investment network of currencies that share common investors, we show that assets with shared investors tend to be characterized by similar market behaviour. Our work sheds light on the role played by institutional investors and provides a basis for further research on their influence in the cryptocurrency ecosystem.

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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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