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Feedback trading in the cryptocurrency market

Author

Listed:
  • Mohamed Shaker Ahmed
  • Adel Alsamman
  • Kaouther Chebbi

Abstract

Purpose - This paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market. Design/methodology/approach - It uses the GJR-GARCH model to investigate feedback trading in the cryptocurrency market. Findings - The findings show a negative relationship between trading volume and autocorrelation in the cryptocurrency market. The GJR-GARCH model shows that only the USD Coin and Binance USD show an asymmetric effect or leverage effect. Interestingly, other cryptocurrencies such as Ethereum, Binance Coin, Ripple, Solana, Cardano and Bitcoin Cash show the opposite behavior of the leverage effect. The findings of the GJR-GARCH model also show positive feedback trading for USD Coin, Binance USD, Ripple, Solana and Bitcoin Cash and negative feedback trading for Ethereum and Cardano only. Originality/value - This paper contributes to the literature by extendingSentana and Wadhwani (1992) to explore the presence of feedback trading in the cryptocurrency market using a sample of the most active cryptocurrencies other than Bitcoin, namely, Ethereum, USD coin, Binance Coin, Binance USD, Ripple, Cardano, Solana and Bitcoin Cash.

Suggested Citation

  • Mohamed Shaker Ahmed & Adel Alsamman & Kaouther Chebbi, 2023. "Feedback trading in the cryptocurrency market," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 41(1), pages 46-63, May.
    • Handle: RePEc:eme:sefpps:sef-02-2023-0096
    DOI: 10.1108/SEF-02-2023-0096
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    More about this item

    Keywords

    Feedback trading; Herding behavior; Cryptocurrencies; Bitcoin; Trading volume; Autocorrelation; GJR-GARCH model; C43; C54; C58; D80; G01; G41;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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