Assessing causal relationships between cryptocurrencies and investor attention: New results from transfer entropy methodology

【Author】 Tong, Zezheng; Goodell, John W.; Shen, Dehua

【Source】FINANCE RESEARCH LETTERS

【影响因子】9.848

【Abstract】Studies apply non-parametric wavelet Granger causality testing to investigate bi-directional causalities of cryptocurrencies with Twitter and Google. However, this method only provides the existence of information flows without quantization and assumes time series are linear. Considering this, we highlight transfer entropy as an alternative, model-free methodology. We quantify the impact of search-engine attention (Google Trends) and social-media attention (Twitter) on cryptocurrency returns, employing in turn Shannon and Re ' nyi transfer entropy methodologies. We document levels of bi-directional causalities, showing that tail events are more informative than center observations in the cryptocurrency market.

【Keywords】Cryptocurrencies; Investor attention; Transfer entropy; Google trends; Twitter

【发表时间】2022 DEC

【收录时间】2022-10-08

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-数字货币