Predicting the cryptocurrency market using social media metrics and search trends during COVID-19

被引：6

作者：

Mou, Jian ^{[1
]}

Liu, Wenting ^{[2
]}

Guan, Chong ^{[2
]}

Westland, J. Christopher ^{[3
]}

Kim, Jongki ^{[1
]}

机构：

[1] Pusan Natl Univ, Sch Business, 2 Busandaehak Ro 63Beon-Gil, Busan 46241, South Korea

[2] Singapore Univ Social Sci, Sch Business, Singapore, Singapore

[3] Univ Illinois, Informat & Decis Sci, Chicago, IL USA

来源：

ELECTRONIC COMMERCE RESEARCH | 2024年 / 24卷 / 02期

基金：

新加坡国家研究基金会;

关键词：

Cryptocurrency; COVID-19; Social media; Search trends; GOOGLE TRENDS; STOCK MARKETS; INFERENCE; SENTIMENT; FORECAST;

D O I：

10.1007/s10660-023-09801-6

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Bitcoin is one of the most well-known cryptocurrencies worldwide. Recently, as the COVID-19 pandemic raged globally, a new wave of price volatility and interest in Bitcoin was witnessed. Identifying the roles played by different information sources in the emergence and diffusion of content through Internet resources can reveal the influential factors affecting cryptocurrencies' value. This study aims to reveal the forces behind cryptocurrencies' monetary value-the market price movements on major exchanges before, during, and post the March 2020, COVID-19 market crash. The daily prices of the two largest cryptocurrencies, Bitcoin and Ether, were obtained from CoinDesk. By integrating Google Trends data, we found that Google searches increase when the number of tweets on COVID-19 soars, with a one-period lag (one day). Furthermore, search trends have a significant impact on cryptocurrencies' future returns such that increased (decreased) searches for a negative event indicate lower (higher) future cryptocurrency prices.

引用

页码：1307 / 1333

页数：27

共 90 条

[31] Does investor sentiment on social media provide robust information for Bitcoin returns predictability? [J].

Guegan, Dominique ;

Renault, Thomas .

FINANCE RESEARCH LETTERS, 2021, 38

[32] What Makes Gun Violence a (Less) Prominent Issue? A Computational Analysis of Compelling Arguments and Selective Agenda Setting [J].

Guo, Lei ;

Mays, Kate ;

Zhang, Yiyan ;

Wijaya, Derry ;

Betke, Margrit .

MASS COMMUNICATION AND SOCIETY, 2021, 24 (05) :651-675

[33] Capture the contagion network of bitcoin - Evidence from pre and mid COVID-19 [J].

Guo, Xiaochun ;

Lu, Fengbin ;

Wei, Yunjie .

RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2021, 58

[34]

Hall D. M., 2020, THESIS WALDEN U

[35] COVID-19: Media coverage and financial markets behavior-A sectoral inquiry [J].

Haroon, Omair ;

Rizvi, Syed Aun R. .

JOURNAL OF BEHAVIORAL AND EXPERIMENTAL FINANCE, 2020, 27

[36] On spurious Granger causality [J].

He, ZL ;

Maekawa, K .

ECONOMICS LETTERS, 2001, 73 (03) :307-313

[37] Subset selection for vector autoregressive processes using Lasso [J].

Hsu, Nan-Jung ;

Hung, Hung-Lin ;

Chang, Ya-Mei .

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2008, 52 (07) :3645-3657

[38] Predicting the direction of stock markets using optimized neural networks with Google Trends [J].

Hu, Hongping ;

Tang, Li ;

Zhang, Shuhua ;

Wang, Haiyan .

NEUROCOMPUTING, 2018, 285 :188-195

[39] Forecasting stock market movements using Google Trend searches [J].

Huang, Melody Y. ;

Rojas, Randall R. ;

Convery, Patrick D. .

EMPIRICAL ECONOMICS, 2020, 59 (06) :2821-2839

[40] Is Bitcoin really more than a diversifier? A pre- and post-COVID-19 analysis [J].

Huang, Yingying ;

Duan, Kun ;

Mishra, Tapas .

FINANCE RESEARCH LETTERS, 2021, 43

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