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Examining interconnectedness between media attention and cryptocurrency markets: A transfer entropy story

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  • Neto, David

Abstract

This note aims at using transfer entropy as a broader concept of causality than Granger’s approach to measure the direction and the intensity of spillovers between five major cryptocurrencies. For this purpose, we use two channels of transmission: price movements and Google-based investor attention. Our results shed light on the dominance of only a few cryptocurrencies, in their influences on price movements as well as on media attention in the other cryptocurrencies.

Suggested Citation

  • Neto, David, 2022. "Examining interconnectedness between media attention and cryptocurrency markets: A transfer entropy story," Economics Letters, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:ecolet:v:214:y:2022:i:c:s0165176522001033
    DOI: 10.1016/j.econlet.2022.110460
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    Cited by:

    1. Wen, Bohui & Yan, Yulin & Hao, Jing & He, Feng, 2023. "Investors’ online searching and green knowledge dissemination," Finance Research Letters, Elsevier, vol. 54(C).
    2. Chen, Yunxiao & Bai, Mingliang & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2023. "Proactively selection of input variables based on information gain factors for deep learning models in short-term solar irradiance forecasting," Energy, Elsevier, vol. 284(C).
    3. Qingjie Zhou & Panpan Zhu & Yinpeng Zhang, 2023. "Contagion Spillover from Bitcoin to Carbon Futures Pricing: Perspective from Investor Attention," Energies, MDPI, vol. 16(2), pages 1-22, January.

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    More about this item

    Keywords

    Cryptocurrency; Media attention; Financial contagion; Transfer entropy;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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