{"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/automated-formulaic-alpha-generation-for","title":"Automated Formulaic Alpha Generation for Quantitative Investing using Evolutionary Algorithms","arxiv_id":null,"date":"2022-03-13","proceeding":"2022 2022 3","authors":["Zhao Meng","Prof. Dr. Roger Wattenhofer"],"abstract":"A cosmic ray consists of mostly highly energetic protons that emanate from the\r\nsun, the Milky Way and distant galaxies. By colliding with particles in our at\u0002mosphere they trigger a chain reaction that leads to so called cosmic-ray showers\r\nof lower energetic particles like pions [1]. In modern biology these are held re\u0002sponsible for inducing the random genetic mutations that led to the development\r\nof life on our planet as we know it [2].\r\nIn the frame of this thesis we will explore how we can make use of these\r\nrandom mutations of the genetic representation of competing candidates to find\r\nfunctions that correlate well with the stock market. This will yield a set of\r\nformulaic alphas that are used in quantitative investing to recognise patterns in\r\na stock’s price development and trade on them accordingly. We will evaluate the\r\nperformance of a set of eight formulaic alphas that are generated by a genetic\r\nprogram on the Nasdaq 100 and realize that they are highly correlated with\r\nthe development of the federal reserve’s balance sheet. The assessment of a\r\nsimple trading algorithm’s performance increase allows the assumption that the\r\ngenerated formulaic alphas help to recognise patterns in the stock market.","url_abs":"https://pub.tik.ee.ethz.ch/students/2021-HS/BA-2021-32.pdf","url_pdf":"https://pub.tik.ee.ethz.ch/students/2021-HS/BA-2021-32.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":"automated-formulaic-alpha-generation-for","repo_url":"https://github.com/RL-MLDM/alphagen","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"evolutionary-algorithms","task_name":"Evolutionary Algorithms"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}