Feedback trading in the cryptocurrency market

IF 2.3 Q2 BUSINESS, FINANCE
Mohamed Shaker Ahmed, Adel Alsamman, Kaouther Chebbi
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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 extending Sentana 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.
加密货币市场的反馈交易
本文旨在研究加密货币市场中的反馈交易和自相关行为。设计/方法/方法它使用GJR-GARCH模型来调查加密货币市场的反馈交易。研究结果显示,加密货币市场的交易量与自相关性之间存在负相关关系。GJR-GARCH模型显示,只有USD Coin和Binance USD表现出不对称效应或杠杆效应。有趣的是,以太坊、币安、瑞波、索拉纳、卡尔达诺和比特币现金等其他加密货币表现出与杠杆效应相反的行为。GJR-GARCH模型的研究结果还显示,美元币、币安美元、瑞波币、索拉纳和比特币现金的正反馈交易,以及以太坊和卡尔达诺的负反馈交易。原创性/价值本文通过扩展Sentana和Wadhwani(1992)来探索加密货币市场中反馈交易的存在,使用比特币以外最活跃的加密货币样本,即以太坊,美元硬币,币安硬币,币安美元,Ripple, Cardano, Solana和比特币现金。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.30
自引率
10.50%
发文量
43
期刊介绍: Topics addressed in the journal include: ■corporate finance, ■financial markets, ■money and banking, ■international finance and economics, ■investments, ■risk management, ■theory of the firm, ■competition policy, ■corporate governance.
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