Google Trends and cryptocurrencies: a nonparametric causality-in-quantiles analysis

被引:9
|
作者
Raza, Syed Ali [1 ]
Yarovaya, Larisa [2 ]
Guesmi, Khaled [3 ]
Shah, Nida [1 ]
机构
[1] IQRA Univ, Dept Management Sci, Karachi, Pakistan
[2] Univ Southampton, Southampton, Hants, England
[3] Paris Sch Business, CRECC, Paris, France
关键词
Google Trends; Cryptocurrencies; Bitcoin; NEM; Ripple; Dash; Ethereum; Litecoin; Nonparametric causality-in-quantiles test; BITCOIN; CONSUMPTION; PARAMETER; ATTENTION; SEARCHES; RETURNS; TESTS;
D O I
10.1108/IJOEM-10-2021-1522
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose This article aims to uncover the impact of Google Trends on cryptocurrency markets beyond Bitcoin during the time of increased attention to altcoins, especially during the COVID-19 pandemic. Design/methodology/approach This paper analyses the nexus among the Google Trends and six cryptocurrencies, namely Bitcoin, New Economy Movement (NEM), Dash, Ethereum, Ripple and Litecoin by utilizing the causality-in-quantiles technique on data comprised of the years January 2016-March 2021. Findings The findings show that Google Trends cause the Litecoin, Bitcoin, Ripple, Ethereum and NEM prices at majority of the quantiles except for Dash. Originality/value The findings will help investors to develop more in-depth understanding of impact of Google Trends on cryptocurrency prices and build successful trading strategies in a more matured digital assets ecosystem.
引用
收藏
页码:5972 / 5989
页数:18
相关论文
共 50 条
  • [31] Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods
    Yang, Dong-Xiao
    Wu, Bi-Bo
    Tong, Jing-Yang
    RESOURCES POLICY, 2021, 74
  • [32] The Asymmetric Effects of Extreme Climate Risk Perception on Coal Futures Return Dynamics: Evidence from Nonparametric Causality-In-Quantiles Tests
    Gao, Wang
    Wei, Jiajia
    Yang, Shixiong
    SUSTAINABILITY, 2023, 15 (10)
  • [33] Does Chinese investor sentiment predict Asia-pacific stock markets? Evidence from a nonparametric causality-in-quantiles test
    Li, Xiao
    FINANCE RESEARCH LETTERS, 2021, 38
  • [34] Terror attacks and stock-market fluctuations: evidence based on a nonparametric causality-in-quantiles test for the G7 countries
    Balcilar, Mehmet
    Gupta, Rangan
    Pierdzioch, Christian
    Wohar, Mark E.
    EUROPEAN JOURNAL OF FINANCE, 2018, 24 (04): : 333 - 346
  • [35] On the relationship of gold, crude oil, stocks with financial stress: A causality-in-quantiles approach
    Das, Debojyoti
    Kumar, Surya Bhushan
    Tiwari, Aviral Kumar
    Shahbaz, Muhammad
    Hasim, Haslifah M.
    FINANCE RESEARCH LETTERS, 2018, 27 : 169 - 174
  • [36] Uncertainty and daily predictability of housing returns and volatility of the United States: Evidence from a higher-order nonparametric causality-in-quantiles test
    Bouri, Elie
    Gupta, Rangan
    Kyei, Clement Kweku
    Shivambu, Rinsuna
    QUARTERLY REVIEW OF ECONOMICS AND FINANCE, 2021, 82 : 200 - 206
  • [37] How does COVID-19 influence dynamic spillover connectedness between cryptocurrencies? Evidence from non-parametric causality-in-quantiles techniques
    Raza, Syed Ali
    Shah, Nida
    Guesmi, Khaled
    Msolli, Badreddine
    FINANCE RESEARCH LETTERS, 2022, 47
  • [38] Did Baltic stock markets offer diversification benefits during the recent financial turmoil? Novel evidence from a nonparametric causality-in-quantiles test
    Vassilios Babalos
    Mehmet Balcilar
    Tumisang B. Loate
    Shingie Chisoro
    Empirica, 2018, 45 : 29 - 47
  • [39] Do Exchange Rates Fluctuations Influence Gold Price in G7 Countries? New Insights from a Nonparametric Causality-in-Quantiles Test
    Raza, Syed Ali
    Shah, Nida
    Ali, Muhammad
    Shahbaz, Muhammad
    ZAGREB INTERNATIONAL REVIEW OF ECONOMICS & BUSINESS, 2021, 24 (02): : 37 - 57
  • [40] On exchange-rate movements and gold-price fluctuations: evidence for gold-producing countries from a nonparametric causality-in-quantiles test
    Balcilar M.
    Gupta R.
    Pierdzioch C.
    International Economics and Economic Policy, 2017, 14 (4) : 691 - 700