{"title":"A Posteriori Multistage Optimal Trading under Transaction Costs and a Diversification Constraint","authors":"Mogens Graf Plessen, A. Bemporad","doi":"10.3905/jot.2018.1.064","DOIUrl":null,"url":null,"abstract":"This article presents a simple method for a posteriori (historical) multivariate, multistage optimal trading under transaction costs and a diversification constraint. Starting from a given amount of money in some currency, the authors analyze the stage-wise optimal allocation over a time horizon with potential investments in multiple currencies and various assets. Three variants are discussed: unconstrained trading frequency, a fixed number of total admissible trades, and waiting a specific time period after every executed trade until the next trade. The developed methods are based on efficient graph generation and consequent graph search and are evaluated quantitatively on real-world data. The fundamental motivation of this work is preparatory labeling of financial time-series data for supervised machine learning.","PeriodicalId":254660,"journal":{"name":"The Journal of Trading","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Trading","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/jot.2018.1.064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This article presents a simple method for a posteriori (historical) multivariate, multistage optimal trading under transaction costs and a diversification constraint. Starting from a given amount of money in some currency, the authors analyze the stage-wise optimal allocation over a time horizon with potential investments in multiple currencies and various assets. Three variants are discussed: unconstrained trading frequency, a fixed number of total admissible trades, and waiting a specific time period after every executed trade until the next trade. The developed methods are based on efficient graph generation and consequent graph search and are evaluated quantitatively on real-world data. The fundamental motivation of this work is preparatory labeling of financial time-series data for supervised machine learning.