{"title":"基于风险最小化的最优投资组合建模","authors":"G. Mazhara","doi":"10.31521/modecon.v38(2023)-11","DOIUrl":null,"url":null,"abstract":"Abstract. Introduction. Portfolio optimization modelling is a study aimed at determining the best way to allocate an investor's funds between securities of different companies. The study uses a number of methods and approaches, such as: multicriteria optimization methods - optimization of criteria for minimum and maximum, modeling of the optimal stock portfolio with minimal risk, to determine the best way to allocate funds that will help investors achieve maximum return while minimizing risk. Purpose. There are a lot of publicly traded companies in the modern American stock market. Having chosen the companies that may grow in the future, the problem of allocating your funds among them remains relevant. Building an optimal portfolio of securities using various economic and mathematical methods solves the problem of allocating financial resources, focusing on the desired future profit and the level of risk exposure. Results. The model for this study was built using one of the methods of multi-criteria optimization - criteria convolution, taking into account portfolio diversification and the specified constraints. The optimization is based on the \"Modern Portfolio Theory\" of the prominent scientist Harry Markowitz. Conclusions. As a result, we built an optimal and diversified portfolio of shares, in which each company on the list represents at least 1%. All constraints have been met and the main conditions have been fulfilled - the portfolio minimizes risk and maximizes profit. With a minimum risk of 5.39%, we expect a return of 1.75%. Such results can be obtained if we use a convolution of the criteria where the preference is given to minimizing risk - 0.7. The largest contributors to the portfolio were the following companies: T-Mobile Us Inc., McKesson Corporation, The Kroger Co., Microsoft Corporation, and Apple Inc. These companies account for a significant portion of the portfolio - 65%. Given the focus on portfolio diversification and the ratio of risk to potential return, we can say that the portfolio is efficient and can be used in practice.","PeriodicalId":201493,"journal":{"name":"Modern Economics","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling of the Optimal Investment Portfolio Focused on Risk Minimization\",\"authors\":\"G. Mazhara\",\"doi\":\"10.31521/modecon.v38(2023)-11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Introduction. Portfolio optimization modelling is a study aimed at determining the best way to allocate an investor's funds between securities of different companies. The study uses a number of methods and approaches, such as: multicriteria optimization methods - optimization of criteria for minimum and maximum, modeling of the optimal stock portfolio with minimal risk, to determine the best way to allocate funds that will help investors achieve maximum return while minimizing risk. Purpose. There are a lot of publicly traded companies in the modern American stock market. Having chosen the companies that may grow in the future, the problem of allocating your funds among them remains relevant. Building an optimal portfolio of securities using various economic and mathematical methods solves the problem of allocating financial resources, focusing on the desired future profit and the level of risk exposure. Results. The model for this study was built using one of the methods of multi-criteria optimization - criteria convolution, taking into account portfolio diversification and the specified constraints. The optimization is based on the \\\"Modern Portfolio Theory\\\" of the prominent scientist Harry Markowitz. Conclusions. As a result, we built an optimal and diversified portfolio of shares, in which each company on the list represents at least 1%. All constraints have been met and the main conditions have been fulfilled - the portfolio minimizes risk and maximizes profit. With a minimum risk of 5.39%, we expect a return of 1.75%. Such results can be obtained if we use a convolution of the criteria where the preference is given to minimizing risk - 0.7. The largest contributors to the portfolio were the following companies: T-Mobile Us Inc., McKesson Corporation, The Kroger Co., Microsoft Corporation, and Apple Inc. These companies account for a significant portion of the portfolio - 65%. Given the focus on portfolio diversification and the ratio of risk to potential return, we can say that the portfolio is efficient and can be used in practice.\",\"PeriodicalId\":201493,\"journal\":{\"name\":\"Modern Economics\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Modern Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31521/modecon.v38(2023)-11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Modern Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31521/modecon.v38(2023)-11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
摘要介绍。投资组合优化建模是一项旨在确定投资者在不同公司的证券之间分配资金的最佳方式的研究。本研究采用了多种方法和途径,如:多标准优化方法-优化最小和最大的标准,以最小的风险建立最优股票投资组合的模型,以确定最佳的方式来配置资金,将帮助投资者实现最大的回报,同时将风险最小化。目的。在现代美国股票市场上有许多上市公司。选择了未来可能成长的公司后,在这些公司中分配资金的问题仍然是相关的。利用各种经济和数学方法构建最优证券投资组合解决了财务资源配置问题,重点关注期望的未来利润和风险暴露水平。结果。本研究的模型采用多准则优化方法之一——准则卷积,考虑了投资组合的多样化和指定的约束条件。这种优化是基于著名科学家哈里·马科维茨的“现代投资组合理论”。结论。因此,我们建立了一个最优和多元化的股票投资组合,其中名单上的每个公司至少占1%。所有的约束条件都得到了满足,主要条件也得到了满足——投资组合的风险最小化,利润最大化。最低风险为5.39%,我们预计收益为1.75%。这样的结果可以得到,如果我们使用一个标准的卷积,其中优先考虑最小化风险- 0.7。对投资组合贡献最大的是以下公司:T-Mobile Us Inc.、McKesson Corporation、The Kroger Co.、微软公司和苹果公司。这些公司占投资组合的很大一部分——65%。考虑到投资组合的多样化和风险与潜在收益的比率,我们可以说该投资组合是有效的,可以在实践中使用。
Modeling of the Optimal Investment Portfolio Focused on Risk Minimization
Abstract. Introduction. Portfolio optimization modelling is a study aimed at determining the best way to allocate an investor's funds between securities of different companies. The study uses a number of methods and approaches, such as: multicriteria optimization methods - optimization of criteria for minimum and maximum, modeling of the optimal stock portfolio with minimal risk, to determine the best way to allocate funds that will help investors achieve maximum return while minimizing risk. Purpose. There are a lot of publicly traded companies in the modern American stock market. Having chosen the companies that may grow in the future, the problem of allocating your funds among them remains relevant. Building an optimal portfolio of securities using various economic and mathematical methods solves the problem of allocating financial resources, focusing on the desired future profit and the level of risk exposure. Results. The model for this study was built using one of the methods of multi-criteria optimization - criteria convolution, taking into account portfolio diversification and the specified constraints. The optimization is based on the "Modern Portfolio Theory" of the prominent scientist Harry Markowitz. Conclusions. As a result, we built an optimal and diversified portfolio of shares, in which each company on the list represents at least 1%. All constraints have been met and the main conditions have been fulfilled - the portfolio minimizes risk and maximizes profit. With a minimum risk of 5.39%, we expect a return of 1.75%. Such results can be obtained if we use a convolution of the criteria where the preference is given to minimizing risk - 0.7. The largest contributors to the portfolio were the following companies: T-Mobile Us Inc., McKesson Corporation, The Kroger Co., Microsoft Corporation, and Apple Inc. These companies account for a significant portion of the portfolio - 65%. Given the focus on portfolio diversification and the ratio of risk to potential return, we can say that the portfolio is efficient and can be used in practice.