{"title":"均值-标准差投资组合优化模型","authors":"Nurhadini Putri, M. Suyudi, I. Sulaiman","doi":"10.46336/ijqrm.v3i4.359","DOIUrl":null,"url":null,"abstract":"Stock investment is an investment in securities with the hope of getting profits in the future. Investors are expected to make a series of portfolios to get optimal results from investments. This discussion aims to find the weight of the funds invested along with the returns and risks. The method used is the mean + std deviation. The results of this portfolio optimization show that the risk aversion coefficient is 0.1. The optimum weight for investment in each company is KLBF (22.67%), PGAS (8.796%), BBCA (41.77%), ASII (8, 24%), and SMAR (18.52%) with a maximum ratio of 8.8% of a return of 0.0881% and a risk of 1.0009%. The results of this portfolio optimization are expected to help investors by dividing the number of funds to be invested by the return and risk.","PeriodicalId":14309,"journal":{"name":"International Journal of Quantitative Research and Modeling","volume":"133 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investment Portfolio Optimization Model with Mean-Std Deviation\",\"authors\":\"Nurhadini Putri, M. Suyudi, I. Sulaiman\",\"doi\":\"10.46336/ijqrm.v3i4.359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stock investment is an investment in securities with the hope of getting profits in the future. Investors are expected to make a series of portfolios to get optimal results from investments. This discussion aims to find the weight of the funds invested along with the returns and risks. The method used is the mean + std deviation. The results of this portfolio optimization show that the risk aversion coefficient is 0.1. The optimum weight for investment in each company is KLBF (22.67%), PGAS (8.796%), BBCA (41.77%), ASII (8, 24%), and SMAR (18.52%) with a maximum ratio of 8.8% of a return of 0.0881% and a risk of 1.0009%. The results of this portfolio optimization are expected to help investors by dividing the number of funds to be invested by the return and risk.\",\"PeriodicalId\":14309,\"journal\":{\"name\":\"International Journal of Quantitative Research and Modeling\",\"volume\":\"133 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Quantitative Research and Modeling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46336/ijqrm.v3i4.359\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Quantitative Research and Modeling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46336/ijqrm.v3i4.359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Investment Portfolio Optimization Model with Mean-Std Deviation
Stock investment is an investment in securities with the hope of getting profits in the future. Investors are expected to make a series of portfolios to get optimal results from investments. This discussion aims to find the weight of the funds invested along with the returns and risks. The method used is the mean + std deviation. The results of this portfolio optimization show that the risk aversion coefficient is 0.1. The optimum weight for investment in each company is KLBF (22.67%), PGAS (8.796%), BBCA (41.77%), ASII (8, 24%), and SMAR (18.52%) with a maximum ratio of 8.8% of a return of 0.0881% and a risk of 1.0009%. The results of this portfolio optimization are expected to help investors by dividing the number of funds to be invested by the return and risk.
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