{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T03:56:44Z","timestamp":1774583804690,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T00:00:00Z","timestamp":1703462400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This study bridges finance and physics by applying thermodynamic concepts to model the limit order book (LOB) with high-frequency trading data on the Bitcoin spot. We derive the measures of Market Temperature and Market Entropy from the kinetic and potential energies in the LOB to provide a deeper understanding of order activities and market participant behavior. Market Temperature emerges as a robust indicator of market liquidity, correlating with liquidity measures such as Active Quote Volume, bid\u2013ask spread and match volume. Market Entropy, on the other hand, quantifies the degree of disorder or randomness in the LOB, providing insights into the instantaneous volatility of price in the high-frequency trading market. Our empirical findings not only broaden the theoretical framework of econophysics but also enhance comprehensive understanding of the market microstructure and order book dynamics.<\/jats:p>","DOI":"10.3390\/e26010024","type":"journal-article","created":{"date-parts":[[2023,12,25]],"date-time":"2023-12-25T03:42:12Z","timestamp":1703475732000},"page":"24","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Thermodynamic Analysis of Financial Markets: Measuring Order Book Dynamics with Temperature and Entropy"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5785-9404","authenticated-orcid":false,"given":"Haochen","family":"Li","sequence":"first","affiliation":[{"name":"Department of Informatics, King\u2019s College London, Bush House, Strand, London WC2R 2LS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7330-7052","authenticated-orcid":false,"given":"Yue","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Informatics, King\u2019s College London, Bush House, Strand, London WC2R 2LS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7421-3012","authenticated-orcid":false,"given":"Maria","family":"Polukarov","sequence":"additional","affiliation":[{"name":"Department of Informatics, King\u2019s College London, Bush House, Strand, London WC2R 2LS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1464-1215","authenticated-orcid":false,"given":"Carmine","family":"Ventre","sequence":"additional","affiliation":[{"name":"Department of Informatics, King\u2019s College London, Bush House, Strand, London WC2R 2LS, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,25]]},"reference":[{"key":"ref_1","unstructured":"Borland, L. 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