• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

热门因素还是创新潜力:什么能解释加密货币的回报?

Buzz Factor or Innovation Potential: What Explains Cryptocurrencies' Returns?

作者信息

Wang Sha, Vergne Jean-Philippe

机构信息

Economics Department, Western University, London, Ontario, Canada.

Ivey Business School, Western University, London, Ontario, Canada.

出版信息

PLoS One. 2017 Jan 13;12(1):e0169556. doi: 10.1371/journal.pone.0169556. eCollection 2017.

DOI:10.1371/journal.pone.0169556
PMID:28085906
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5234770/
Abstract

Cryptocurrencies have become increasingly popular since the introduction of bitcoin in 2009. In this paper, we identify factors associated with variations in cryptocurrencies' market values. In the past, researchers argued that the "buzz" surrounding cryptocurrencies in online media explained their price variations. But this observation obfuscates the notion that cryptocurrencies, unlike fiat currencies, are technologies entailing a true innovation potential. By using, for the first time, a unique measure of innovation potential, we find that the latter is in fact the most important factor associated with increases in cryptocurrency returns. By contrast, we find that the buzz surrounding cryptocurrencies is negatively associated with returns after controlling for a variety of factors, such as supply growth and liquidity. Also interesting is our finding that a cryptocurrency's association with fraudulent activity is not negatively associated with weekly returns-a result that further qualifies the media's influence on cryptocurrencies. Finally, we find that an increase in supply is positively associated with weekly returns. Taken together, our findings show that cryptocurrencies do not behave like traditional currencies or commodities-unlike what most prior research has assumed-and depict an industry that is much more mature, and much less speculative, than has been implied by previous accounts.

摘要

自2009年比特币问世以来,加密货币越来越受欢迎。在本文中,我们确定了与加密货币市值变化相关的因素。过去,研究人员认为在线媒体中围绕加密货币的“热议”解释了它们的价格变化。但这一观察结果模糊了这样一种观念,即与法定货币不同,加密货币是具有真正创新潜力的技术。通过首次使用一种独特的创新潜力衡量方法,我们发现后者实际上是与加密货币回报增加相关的最重要因素。相比之下,我们发现,在控制了各种因素(如供应增长和流动性)之后,围绕加密货币的热议与回报呈负相关。我们的另一个有趣发现是,一种加密货币与欺诈活动的关联与每周回报并无负相关——这一结果进一步限定了媒体对加密货币的影响。最后,我们发现供应增加与每周回报呈正相关。综合来看,我们的研究结果表明,加密货币的表现不同于传统货币或商品——这与大多数先前研究的假设不同——并且描绘了一个比以往描述所暗示的更加成熟、投机性更低的行业。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bef6/5234770/00cf1c8a779d/pone.0169556.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bef6/5234770/00cf1c8a779d/pone.0169556.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bef6/5234770/00cf1c8a779d/pone.0169556.g001.jpg

相似文献

1
Buzz Factor or Innovation Potential: What Explains Cryptocurrencies' Returns?热门因素还是创新潜力:什么能解释加密货币的回报?
PLoS One. 2017 Jan 13;12(1):e0169556. doi: 10.1371/journal.pone.0169556. eCollection 2017.
2
The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy.比特币经济中社会经济信号之间的反馈循环:泡沫的数字痕迹
J R Soc Interface. 2014 Oct 6;11(99). doi: 10.1098/rsif.2014.0623.
3
Age and market capitalization drive large price variations of cryptocurrencies.年龄和市值推动了加密货币的巨大价格波动。
Sci Rep. 2023 Mar 30;13(1):3351. doi: 10.1038/s41598-023-30431-3.
4
Social media engagement and cryptocurrency performance.社交媒体参与度与加密货币表现。
PLoS One. 2023 May 11;18(5):e0284501. doi: 10.1371/journal.pone.0284501. eCollection 2023.
5
Correction: Buzz Factor or Innovation Potential: What Explains Cryptocurrencies' Returns?更正:轰动效应还是创新潜力:什么能解释加密货币的回报?
PLoS One. 2017 May 10;12(5):e0177659. doi: 10.1371/journal.pone.0177659. eCollection 2017.
6
Is Bitcoin Still a King? Relationships between Prices, Volatility and Liquidity of Cryptocurrencies during the Pandemic.比特币仍是王者吗?疫情期间加密货币的价格、波动性与流动性之间的关系。
Entropy (Basel). 2021 Oct 22;23(11):1386. doi: 10.3390/e23111386.
7
Asymmetric nexus between COVID-19 outbreak in the world and cryptocurrency market.全球新冠疫情与加密货币市场之间的不对称关系。
Int Rev Financ Anal. 2021 Jan;73:101613. doi: 10.1016/j.irfa.2020.101613. Epub 2020 Oct 20.
8
The predictive capacity of GARCH-type models in measuring the volatility of crypto and world currencies.GARCH类模型在衡量加密货币和世界货币波动性方面的预测能力。
PLoS One. 2021 Jan 29;16(1):e0245904. doi: 10.1371/journal.pone.0245904. eCollection 2021.
9
The resilience of cryptocurrency market efficiency to COVID-19 shock.加密货币市场效率对新冠疫情冲击的弹性。
Physica A. 2022 Dec 1;607:128218. doi: 10.1016/j.physa.2022.128218. Epub 2022 Oct 3.
10
Estimating the volatility of cryptocurrencies during bearish markets by employing GARCH models.运用广义自回归条件异方差(GARCH)模型估计加密货币在熊市期间的波动性。
Heliyon. 2019 Aug 13;5(8):e02239. doi: 10.1016/j.heliyon.2019.e02239. eCollection 2019 Aug.

引用本文的文献

1
A Crime by Any Other Name: Gender Differences in Moral Reasoning When Judging the Tax Evasion of Cryptocurrency Traders.换个名字的罪行:判断加密货币交易者逃税行为时道德推理中的性别差异
Behav Sci (Basel). 2024 Mar 1;14(3):198. doi: 10.3390/bs14030198.
2
Predicting Bitcoin (BTC) Price in the Context of Economic Theories: A Machine Learning Approach.在经济理论背景下预测比特币(BTC)价格:一种机器学习方法。
Entropy (Basel). 2022 Oct 18;24(10):1487. doi: 10.3390/e24101487.
3
An analysis of investors' behavior in Bitcoin market.比特币市场中投资者行为分析。

本文引用的文献

1
Statistical Analysis of the Exchange Rate of Bitcoin.比特币汇率的统计分析
PLoS One. 2015 Jul 29;10(7):e0133678. doi: 10.1371/journal.pone.0133678. eCollection 2015.
2
The predecessors of bitcoin and their implications for the prospect of virtual currencies.比特币的前身及其对虚拟货币前景的影响。
PLoS One. 2015 Apr 28;10(4):e0123071. doi: 10.1371/journal.pone.0123071. eCollection 2014.
3
What are the main drivers of the Bitcoin price? Evidence from wavelet coherence analysis.比特币价格的主要驱动因素有哪些?来自小波相干分析的证据。
PLoS One. 2022 Mar 10;17(3):e0264522. doi: 10.1371/journal.pone.0264522. eCollection 2022.
4
On the (in)efficiency of cryptocurrencies: have they taken daily or weekly random walks?关于加密货币的(无)效率:它们呈现出每日还是每周的随机游走?
Heliyon. 2021 Apr 6;7(4):e06685. doi: 10.1016/j.heliyon.2021.e06685. eCollection 2021 Apr.
5
Using algorithmic trading to analyze short term profitability of Bitcoin.使用算法交易分析比特币的短期盈利能力。
PeerJ Comput Sci. 2021 Feb 3;7:e337. doi: 10.7717/peerj-cs.337. eCollection 2021.
6
From code to market: Network of developers and correlated returns of cryptocurrencies.从代码到市场:加密货币开发者网络与相关回报
Sci Adv. 2020 Dec 16;6(51). doi: 10.1126/sciadv.abd2204. Print 2020 Dec.
7
Evolutionary dynamics of the cryptocurrency market.加密货币市场的演化动态。
R Soc Open Sci. 2017 Nov 15;4(11):170623. doi: 10.1098/rsos.170623. eCollection 2017 Nov.
8
Correction: Buzz Factor or Innovation Potential: What Explains Cryptocurrencies' Returns?更正:轰动效应还是创新潜力:什么能解释加密货币的回报?
PLoS One. 2017 May 10;12(5):e0177659. doi: 10.1371/journal.pone.0177659. eCollection 2017.
PLoS One. 2015 Apr 15;10(4):e0123923. doi: 10.1371/journal.pone.0123923. eCollection 2015.
4
The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy.比特币经济中社会经济信号之间的反馈循环:泡沫的数字痕迹
J R Soc Interface. 2014 Oct 6;11(99). doi: 10.1098/rsif.2014.0623.
5
Do the rich get richer? An empirical analysis of the Bitcoin transaction network.富人更富?比特币交易网络的实证分析。
PLoS One. 2014 Feb 5;9(2):e86197. doi: 10.1371/journal.pone.0086197. eCollection 2014.
6
BitCoin meets Google Trends and Wikipedia: quantifying the relationship between phenomena of the Internet era.比特币与谷歌趋势和维基百科:量化互联网时代现象之间的关系。
Sci Rep. 2013 Dec 4;3:3415. doi: 10.1038/srep03415.
7
Cross-correlations between volume change and price change.成交量变化与价格变化之间的交叉相关关系。
Proc Natl Acad Sci U S A. 2009 Dec 29;106(52):22079-84. doi: 10.1073/pnas.0911983106. Epub 2009 Dec 15.