{"title":"具有多周期随机预测和规模约束的投资组合执行","authors":"Dmitriy Nuriyev","doi":"10.2139/ssrn.2814597","DOIUrl":null,"url":null,"abstract":"This paper investigates the problem of finding a dynamically updating trading schedule for a portfolio with stochastically evolving forecasts, absolute value based execution costs and a decaying market impact as well as size constraints. This is achieved by deriving a continuous time stochastic state evolution model as well as a Hamiltonian with a corresponding HJB equation which is then approximately solved to third order accuracy which provides a Value function and the optimal controls.","PeriodicalId":57292,"journal":{"name":"公司治理评论","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Portfolio Execution with Multi-Period Stochastic Forecasts and Size Constraints\",\"authors\":\"Dmitriy Nuriyev\",\"doi\":\"10.2139/ssrn.2814597\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the problem of finding a dynamically updating trading schedule for a portfolio with stochastically evolving forecasts, absolute value based execution costs and a decaying market impact as well as size constraints. This is achieved by deriving a continuous time stochastic state evolution model as well as a Hamiltonian with a corresponding HJB equation which is then approximately solved to third order accuracy which provides a Value function and the optimal controls.\",\"PeriodicalId\":57292,\"journal\":{\"name\":\"公司治理评论\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"公司治理评论\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2814597\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"公司治理评论","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.2139/ssrn.2814597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Portfolio Execution with Multi-Period Stochastic Forecasts and Size Constraints
This paper investigates the problem of finding a dynamically updating trading schedule for a portfolio with stochastically evolving forecasts, absolute value based execution costs and a decaying market impact as well as size constraints. This is achieved by deriving a continuous time stochastic state evolution model as well as a Hamiltonian with a corresponding HJB equation which is then approximately solved to third order accuracy which provides a Value function and the optimal controls.