{"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/discovering-bayesian-market-views-for","title":"Discovering Bayesian Market Views for Intelligent Asset Allocation","arxiv_id":"1802.09911","date":"2018-02-27","proceeding":null,"authors":["Frank Z. Xing","Erik Cambria","Lorenzo Malandri","Carlo Vercellis"],"abstract":"Along with the advance of opinion mining techniques, public mood has been\nfound to be a key element for stock market prediction. However, how market\nparticipants' behavior is affected by public mood has been rarely discussed.\nConsequently, there has been little progress in leveraging public mood for the\nasset allocation problem, which is preferred in a trusted and interpretable\nway. In order to address the issue of incorporating public mood analyzed from\nsocial media, we propose to formalize public mood into market views, because\nmarket views can be integrated into the modern portfolio theory. In our\nframework, the optimal market views will maximize returns in each period with a\nBayesian asset allocation model. We train two neural models to generate the\nmarket views, and benchmark the model performance on other popular asset\nallocation strategies. Our experimental results suggest that the formalization\nof market views significantly increases the profitability (5% to 10% annually)\nof the simulated portfolio at a given risk level.","url_abs":"http://arxiv.org/abs/1802.09911v2","url_pdf":"http://arxiv.org/pdf/1802.09911v2.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":"discovering-bayesian-market-views-for","repo_url":"https://github.com/fxing79/ibaa","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"opinion-mining","task_name":"Opinion Mining"},{"task_slug":"stock-market-prediction","task_name":"Stock Market Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}