{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T08:12:43Z","timestamp":1778659963607,"version":"3.51.4"},"reference-count":38,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advs. Complex Syst."],"published-print":{"date-parts":[[2020,8]]},"abstract":"<jats:p> This study examines the information flow between prices and transaction volumes in the cryptocurrency market, where transfer entropy is used for measurement. We selected four cryptocurrencies (Bitcoin, Ethereum, Litecoin and XRP) with large market values, and Bitcoin and BCH (Bitcoin Cash) for hard fork analysis; a hard fork is when a single cryptocurrency splits in two. By examining the real price data, we show that the long-term time series includes too much noise obscuring the local information flow; thus, a dynamic calculation is needed. The long-term and short-term sliding transfer entropy (TE) values and the corresponding [Formula: see text]-values, based on daily data, indicate that there is a dynamic information flow. The dominant direction of which is [Formula: see text]. In addition, the example based on minute Bitcoin data also shows a dynamic flow of information between price and transaction volume. The price\u2013volume dynamics of multiple time scales helps to analyze the price mechanism in the cryptocurrency market. <\/jats:p>","DOI":"10.1142\/s0219525920500149","type":"journal-article","created":{"date-parts":[[2021,2,7]],"date-time":"2021-02-07T15:55:16Z","timestamp":1612713316000},"page":"2050014","source":"Crossref","is-referenced-by-count":3,"title":["THE DYNAMICS OF PRICE\u2013VOLUME INFORMATION TRANSFER IN THE CRYPTOCURRENCY MARKETS"],"prefix":"10.1142","volume":"23","author":[{"given":"JINGLAN","family":"ZHENG","sequence":"first","affiliation":[{"name":"National Astronomy Observatories, Chinese Academy of Science, Beijing 100101, P.\u00a0R.\u00a0China"},{"name":"University of Chinese Academy of Science, Beijing 100049, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7790-0803","authenticated-orcid":false,"given":"CHUN-XIAO","family":"NIE","sequence":"additional","affiliation":[{"name":"Institute of Quantitative Economics, School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,2,6]]},"reference":[{"key":"S0219525920500149BIB001","doi-asserted-by":"publisher","DOI":"10.2307\/2330874"},{"key":"S0219525920500149BIB002","doi-asserted-by":"publisher","DOI":"10.1093\/rfs\/5.2.199"},{"key":"S0219525920500149BIB003","doi-asserted-by":"publisher","DOI":"10.1016\/0378-4266(88)90048-9"},{"issue":"5","key":"S0219525920500149BIB004","first-page":"1639","volume":"49","author":"Craig H.","year":"1994","journal-title":"The J. 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