{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/180902772","title":"Order book model with herd behavior exhibiting long-range memory","arxiv_id":"1809.02772","date":"2018-09-08","proceeding":null,"authors":["Aleksejus Kononovicius","Julius Ruseckas"],"abstract":"In this work, we propose an order book model with herd behavior. The proposed\nmodel is built upon two distinct approaches: a recent empirical study of the\ndetailed order book records by Kanazawa et al. [Phys. Rev. Lett. 120, 138301]\nand financial herd behavior model. Combining these approaches allows us to\npropose a model that replicates the long-range memory of absolute returns and\ntrading activity. We compare the statistical properties of the model against\nthe empirical statistical properties of the Bitcoin exchange rates and New York\nstock exchange tickers. We also show that the fracture in the spectral density\nof the high-frequency absolute return time series might be related to the\nmechanism of convergence towards the equilibrium price.","url_abs":"http://arxiv.org/abs/1809.02772v3","url_pdf":"http://arxiv.org/pdf/1809.02772v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"180902772","repo_url":"https://github.com/akononovicius/herding-OB-model","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}