{"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/multi-period-trading-via-convex-optimization","title":"Multi-Period Trading via Convex Optimization","arxiv_id":"1705.00109","date":"2017-04-29","proceeding":null,"authors":["Stephen Boyd","Enzo Busseti","Steven Diamond","Ronald N. Kahn","Kwangmoo Koh","Peter Nystrup","Jan Speth"],"abstract":"We consider a basic model of multi-period trading, which can be used to\nevaluate the performance of a trading strategy. We describe a framework for\nsingle-period optimization, where the trades in each period are found by\nsolving a convex optimization problem that trades off expected return, risk,\ntransaction cost and holding cost such as the borrowing cost for shorting\nassets. We then describe a multi-period version of the trading method, where\noptimization is used to plan a sequence of trades, with only the first one\nexecuted, using estimates of future quantities that are unknown when the trades\nare chosen. The single-period method traces back to Markowitz; the multi-period\nmethods trace back to model predictive control. Our contribution is to describe\nthe single-period and multi-period methods in one simple framework, giving a\nclear description of the development and the approximations made. In this paper\nwe do not address a critical component in a trading algorithm, the predictions\nor forecasts of future quantities. The methods we describe in this paper can be\nthought of as good ways to exploit predictions, no matter how they are made. We\nhave also developed a companion open-source software library that implements\nmany of the ideas and methods described in the paper.","url_abs":"http://arxiv.org/abs/1705.00109v1","url_pdf":"http://arxiv.org/pdf/1705.00109v1.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":"multi-period-trading-via-convex-optimization","repo_url":"https://github.com/jollyraven100/Quant_algorithmic-trading_and_More","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"multi-period-trading-via-convex-optimization","repo_url":"https://github.com/jollyraven100/Trade-Ideas-and-Research-Reference","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"multi-period-trading-via-convex-optimization","repo_url":"https://github.com/michaelsyao/Trade-Ideas-and-Research-Reference","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"model-predictive-control","task_name":"Model Predictive Control"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1705.00109","atlas_url":"https://app.syntology.ai/?focus=1705.00109","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}