{"title":"具有重新分配成本的动态资本分配","authors":"Ermo Chen, Lan Wu, Jingyi He","doi":"10.1016/j.orl.2024.107114","DOIUrl":null,"url":null,"abstract":"<div><p>Traditional static capital allocation incurs significant reallocation costs over periods due to drastic fluctuations. We propose a new framework for dynamic capital allocation with time-varying capital constraints that incorporates reallocation costs. We obtain an analytical solution in a recursive form and demonstrate its admirable performance through simulations. The solution compromises between static allocation and expected future risk structure and strikes a balance between addressing current risk profiles and adjustment costs. It successfully provides an effective allocation tool while preserving stability.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"54 ","pages":"Article 107114"},"PeriodicalIF":0.8000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic capital allocation with reallocation cost\",\"authors\":\"Ermo Chen, Lan Wu, Jingyi He\",\"doi\":\"10.1016/j.orl.2024.107114\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Traditional static capital allocation incurs significant reallocation costs over periods due to drastic fluctuations. We propose a new framework for dynamic capital allocation with time-varying capital constraints that incorporates reallocation costs. We obtain an analytical solution in a recursive form and demonstrate its admirable performance through simulations. The solution compromises between static allocation and expected future risk structure and strikes a balance between addressing current risk profiles and adjustment costs. It successfully provides an effective allocation tool while preserving stability.</p></div>\",\"PeriodicalId\":54682,\"journal\":{\"name\":\"Operations Research Letters\",\"volume\":\"54 \",\"pages\":\"Article 107114\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-04-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research Letters\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167637724000506\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167637724000506","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Traditional static capital allocation incurs significant reallocation costs over periods due to drastic fluctuations. We propose a new framework for dynamic capital allocation with time-varying capital constraints that incorporates reallocation costs. We obtain an analytical solution in a recursive form and demonstrate its admirable performance through simulations. The solution compromises between static allocation and expected future risk structure and strikes a balance between addressing current risk profiles and adjustment costs. It successfully provides an effective allocation tool while preserving stability.
期刊介绍:
Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.