{"title":"如果你投资多种资产,模糊性很重要","authors":"Yuki Shigeta","doi":"10.2139/ssrn.3110403","DOIUrl":null,"url":null,"abstract":"This study examines the practical performance of the multiple priors optimal portfolio based on the mean-variance preference. The multiple priors optimal portfolio is designed to be robust to model uncertainty, also known as ambiguity. A back test finds two properties: the multiple priors optimal portfolio tends to be efficient when the number of assets is large and it has fewer turnovers than the mean-variance-efficient portfolios. Furthermore, the presented simulation shows that the multiple priors optimal portfolio outperforms the others when the number of assets is large and number of observations to form a portfolio is small.","PeriodicalId":260073,"journal":{"name":"Mathematics eJournal","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ambiguity Matters If You Invest in Many Assets\",\"authors\":\"Yuki Shigeta\",\"doi\":\"10.2139/ssrn.3110403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examines the practical performance of the multiple priors optimal portfolio based on the mean-variance preference. The multiple priors optimal portfolio is designed to be robust to model uncertainty, also known as ambiguity. A back test finds two properties: the multiple priors optimal portfolio tends to be efficient when the number of assets is large and it has fewer turnovers than the mean-variance-efficient portfolios. Furthermore, the presented simulation shows that the multiple priors optimal portfolio outperforms the others when the number of assets is large and number of observations to form a portfolio is small.\",\"PeriodicalId\":260073,\"journal\":{\"name\":\"Mathematics eJournal\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematics eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3110403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3110403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This study examines the practical performance of the multiple priors optimal portfolio based on the mean-variance preference. The multiple priors optimal portfolio is designed to be robust to model uncertainty, also known as ambiguity. A back test finds two properties: the multiple priors optimal portfolio tends to be efficient when the number of assets is large and it has fewer turnovers than the mean-variance-efficient portfolios. Furthermore, the presented simulation shows that the multiple priors optimal portfolio outperforms the others when the number of assets is large and number of observations to form a portfolio is small.