{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:46:37Z","timestamp":1742913997082,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031083327"},{"type":"electronic","value":"9783031083334"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-08333-4_25","type":"book-chapter","created":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T15:52:13Z","timestamp":1655394733000},"page":"304-315","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["TraderNet-CR: Cryptocurrency Trading with\u00a0Deep Reinforcement Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9431-6679","authenticated-orcid":false,"given":"Vasilis","family":"Kochliaridis","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1214-3845","authenticated-orcid":false,"given":"Eleftherios","family":"Kouloumpris","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3477-8825","authenticated-orcid":false,"given":"Ioannis","family":"Vlahavas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,6,10]]},"reference":[{"unstructured":"Low, R.K.Y., Tan, E.: The Role of Analyst Forecasts in the Momentum Effect. Wiley Trading (2006)","key":"25_CR1"},{"unstructured":"Baiynd, A.M.: The Trading Book: A Complete Solution to Mastering Technical Systems and Trading Psychology. McGraw-Hill (2011)","key":"25_CR2"},{"unstructured":"Brown, R.G.: Smoothing, Forecasting and Prediciton of Time Series. Dover Publications (1963)","key":"25_CR3"},{"unstructured":"Brown, R.G.: New Concepts in Technical Trading Systems. Trend Research (1978)","key":"25_CR4"},{"unstructured":"Brown, R.G.: Technical Analysis Power Tools for Active Investors. Financial Times Prentice Hall (2005)","key":"25_CR5"},{"unstructured":"Gerstein, M.: Evaluation of the chaikin power gauge stock rating system. Chaikin Analytics (2013)","key":"25_CR6"},{"unstructured":"Granville, J.E.: Granville\u2019s New Key to Stock Market Profits. Papamoa Press (2018)","key":"25_CR7"},{"unstructured":"Jiang, Z., Xu, D., Liang, J.: A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem, pp. 1\u201331 (2017). http:\/\/arxiv.org\/abs\/1706.10059","key":"25_CR8"},{"issue":"20","key":"25_CR9","doi-asserted-by":"publisher","first-page":"14021","DOI":"10.1007\/s00521-021-06043-1","volume":"33","author":"IE Livieris","year":"2021","unstructured":"Livieris, I.E., Stavroyiannis, S., Iliadis, L., Pintelas, P.: Smoothing and stationarity enforcement framework for deep learning time-series forecasting. Neural Comput. Appl. 33(20), 14021\u201314035 (2021). https:\/\/doi.org\/10.1007\/s00521-021-06043-1","journal-title":"Neural Comput. Appl."},{"doi-asserted-by":"crossref","unstructured":"Low, R.K.Y., Tan, E.: The role of analyst forecasts in the momentum effect. Int. Rev. Finan. Anal. 9 (2016)","key":"25_CR10","DOI":"10.2139\/ssrn.2739825"},{"issue":"23","key":"25_CR11","doi-asserted-by":"publisher","first-page":"17229","DOI":"10.1007\/s00521-020-05359-8","volume":"32","author":"G Lucarelli","year":"2020","unstructured":"Lucarelli, G., Borrotti, M.: A deep q-learning portfolio management framework for the cryptocurrency market. Neural Comput. Appl. 32(23), 17229\u201317244 (2020)","journal-title":"Neural Comput. Appl."},{"doi-asserted-by":"crossref","unstructured":"Mudassir, M., Bennbaia, S. Unal, D.H.M.: Time-series forecasting of bitcoin prices using high-dimensional features: a machine learning approach. Neural Computing and Applications (2020)","key":"25_CR12","DOI":"10.1007\/s00521-020-05129-6"},{"unstructured":"Mulloy, P.: Technical Analysis of Stocks and Commodities 40(1) (1982)","key":"25_CR13"},{"unstructured":"Murphy, J.J.: Technical analysis of the financial markets: a comprehensive guide to trading methods and applications. Penguin (1999)","key":"25_CR14"},{"unstructured":"Noel, A.D., van Hoof, C., Millidge, B.: Online reinforcement learning with sparse rewards through an active inference capsule (2021)","key":"25_CR15"},{"issue":"4","key":"25_CR16","doi-asserted-by":"publisher","first-page":"1506","DOI":"10.3390\/app10041506","volume":"10","author":"O Sattarov","year":"2020","unstructured":"Sattarov, O., Muminov, A., Lee, C.W., Kang, H.K., Oh, R., Ahn, J., Oh, H.J., Jeon, H.S.: Recommending cryptocurrency trading points with deep reinforcement learning approach. Appl. Sci. 10(4), 1506 (2020)","journal-title":"Appl. Sci."},{"unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., Klimov, O.: Proximal policy optimization algorithms (2017)","key":"25_CR17"}],"container-title":["IFIP Advances in Information and Communication Technology","Artificial Intelligence Applications and Innovations"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-08333-4_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,16]],"date-time":"2022-06-16T16:05:48Z","timestamp":1655395548000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-08333-4_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031083327","9783031083334"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-08333-4_25","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"10 June 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"IFIP International Conference on Artificial Intelligence Applications and Innovations","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hersonissos","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiai2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ifipaiai.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}