{"title":"要素风险预算及其他","authors":"Adil Rengim Cetingoz, Olivier Guéant","doi":"arxiv-2312.11132","DOIUrl":null,"url":null,"abstract":"Portfolio optimization methods have evolved significantly since Markowitz\nintroduced the mean-variance framework in 1952. While the theoretical appeal of\nthis approach is undeniable, its practical implementation poses important\nchallenges, primarily revolving around the intricate task of estimating\nexpected returns. As a result, practitioners and scholars have explored\nalternative methods that prioritize risk management and diversification. One\nsuch approach is Risk Budgeting, where portfolio risk is allocated among assets\naccording to predefined risk budgets. The effectiveness of Risk Budgeting in\nachieving true diversification can, however, be questioned, given that asset\nreturns are often influenced by a small number of risk factors. From this\nperspective, one question arises: is it possible to allocate risk at the factor\nlevel using the Risk Budgeting approach? This paper introduces a comprehensive\nframework to address this question by introducing risk measures directly\nassociated with risk factor exposures and demonstrating the desirable\nmathematical properties of these risk measures, making them suitable for\noptimization. We also propose a framework to find the portfolio that\neffectively balances the risk contributions from both assets and factors.\nLeveraging standard stochastic algorithms, our framework enables the use of a\nwide range of risk measures.","PeriodicalId":501045,"journal":{"name":"arXiv - QuantFin - Portfolio Management","volume":"55 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Factor Risk Budgeting and Beyond\",\"authors\":\"Adil Rengim Cetingoz, Olivier Guéant\",\"doi\":\"arxiv-2312.11132\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Portfolio optimization methods have evolved significantly since Markowitz\\nintroduced the mean-variance framework in 1952. While the theoretical appeal of\\nthis approach is undeniable, its practical implementation poses important\\nchallenges, primarily revolving around the intricate task of estimating\\nexpected returns. As a result, practitioners and scholars have explored\\nalternative methods that prioritize risk management and diversification. One\\nsuch approach is Risk Budgeting, where portfolio risk is allocated among assets\\naccording to predefined risk budgets. The effectiveness of Risk Budgeting in\\nachieving true diversification can, however, be questioned, given that asset\\nreturns are often influenced by a small number of risk factors. From this\\nperspective, one question arises: is it possible to allocate risk at the factor\\nlevel using the Risk Budgeting approach? This paper introduces a comprehensive\\nframework to address this question by introducing risk measures directly\\nassociated with risk factor exposures and demonstrating the desirable\\nmathematical properties of these risk measures, making them suitable for\\noptimization. We also propose a framework to find the portfolio that\\neffectively balances the risk contributions from both assets and factors.\\nLeveraging standard stochastic algorithms, our framework enables the use of a\\nwide range of risk measures.\",\"PeriodicalId\":501045,\"journal\":{\"name\":\"arXiv - QuantFin - Portfolio Management\",\"volume\":\"55 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Portfolio Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2312.11132\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Portfolio Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2312.11132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Portfolio optimization methods have evolved significantly since Markowitz
introduced the mean-variance framework in 1952. While the theoretical appeal of
this approach is undeniable, its practical implementation poses important
challenges, primarily revolving around the intricate task of estimating
expected returns. As a result, practitioners and scholars have explored
alternative methods that prioritize risk management and diversification. One
such approach is Risk Budgeting, where portfolio risk is allocated among assets
according to predefined risk budgets. The effectiveness of Risk Budgeting in
achieving true diversification can, however, be questioned, given that asset
returns are often influenced by a small number of risk factors. From this
perspective, one question arises: is it possible to allocate risk at the factor
level using the Risk Budgeting approach? This paper introduces a comprehensive
framework to address this question by introducing risk measures directly
associated with risk factor exposures and demonstrating the desirable
mathematical properties of these risk measures, making them suitable for
optimization. We also propose a framework to find the portfolio that
effectively balances the risk contributions from both assets and factors.
Leveraging standard stochastic algorithms, our framework enables the use of a
wide range of risk measures.