检索结果-南通市图书馆

On-chain analytics for sentiment-driven statistical causality in cryptocurrencies

Blockchain(Research and Applications) 2022年第2期3卷 39-63页

作者： Ioannis Chalkiadakis Anna Zaremba Gareth W.Peters michael j.chantler School of Mathematical and Computer Sciences Heriot-Watt UniversityScotlandEH144ASUK Department of Computer Science University CollegeLondonWC1E 7HUUK janet and Ian Duncan Endowed Chair of Actuarial Science Department of Statistics and Applied ProbabilityUniversity of CaliforniaSanta BarbaraCA93106USA

This paper establishes a new framework for assessing multimodal statistical causality between cryptocurrency market(cryptomarket)sentiment and cryptocurrency price *** order to achieve this,we present an efficient algorithm for multimodal statistical causality analysis based on Multiple-Output Gaussian *** from different information sources(modalities)are jointly modelled as a Multiple-Output Gaussian Process,and then using a novel approach to statistical causality based on Gaussian Processes(GPs),we study linear and non-linear causal effects between the different *** demonstrate the effectiveness of our approach in a machine learning application by studying the relationship between cryptocurrency spot price dynamics and sentiment time-series data specific to the crypto sector,which we conjecture influences retail investor *** investor sentiment is extracted from cryptomarket news data via methods developed in the area of statistical machine learning known as Natural Language Processing(NLP).To capture sentiment,we present a novel framework for text to time-series embedding,which we then use to construct a sentiment index from publicly available news *** conduct a statistical analysis of our sentiment statistical index model and compare it to alternative state-of-the-art sentiment models popular in the NLP *** regard to the multimodal causality,the investor sentiment is our primary modality of exploration,in addition to price and a blockchain technologyrelated indicator(hash rate).Analysis shows that our approach is effective in modelling causal structures of variable degree of complexity between heterogeneous data sources and illustrates the impact that certain modelling choices for the different modalities can have on detecting causality.A solid understanding of these factors is necessary to gauge cryptocurrency adoption by retail investors and provide sentiment-and technologybased insights about the cry

关键词： Cryptocurrencies Statistical causality Blockchain regression Multiple-output Gaussian process Natural language processing Cryptonews sentiment

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：