{"title":"归一化期望效用-熵投资决策模型及其在选股中的应用","authors":"Jiping Yang, Lijian Zhang, Xiaoxuan Chen","doi":"10.1109/PIC.2010.5687461","DOIUrl":null,"url":null,"abstract":"We first introduce the normalized Expected Utility-Entropy (EU-E) decision model, which is a weighted linear average of normalized expected utility and information entropy. Based on the normalized EU-E decision model, we establish a normalized EU-E investment decision model. Then we apply the model to stock selection when we invest in the 40 sample stocks of Shenzhen component index. It has concluded that portfolios of 4 stocks selected by normalized EU-E model with larger tradeoff coefficient λ are more efficient than that of those selected with smaller tradeoff coefficient λ with relative general utility function. Thus, this has demonstrated that we should not only take the expected utility of a risky action itself into account but also the information entropy to measure the uncertainty of the state of nature, which further verified the usefulness of the information entropy.","PeriodicalId":142910,"journal":{"name":"2010 IEEE International Conference on Progress in Informatics and Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Normalized Expected Utility-Entropy investment decision model and its application in stock selection\",\"authors\":\"Jiping Yang, Lijian Zhang, Xiaoxuan Chen\",\"doi\":\"10.1109/PIC.2010.5687461\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We first introduce the normalized Expected Utility-Entropy (EU-E) decision model, which is a weighted linear average of normalized expected utility and information entropy. Based on the normalized EU-E decision model, we establish a normalized EU-E investment decision model. Then we apply the model to stock selection when we invest in the 40 sample stocks of Shenzhen component index. It has concluded that portfolios of 4 stocks selected by normalized EU-E model with larger tradeoff coefficient λ are more efficient than that of those selected with smaller tradeoff coefficient λ with relative general utility function. Thus, this has demonstrated that we should not only take the expected utility of a risky action itself into account but also the information entropy to measure the uncertainty of the state of nature, which further verified the usefulness of the information entropy.\",\"PeriodicalId\":142910,\"journal\":{\"name\":\"2010 IEEE International Conference on Progress in Informatics and Computing\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Progress in Informatics and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PIC.2010.5687461\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Progress in Informatics and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PIC.2010.5687461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Normalized Expected Utility-Entropy investment decision model and its application in stock selection
We first introduce the normalized Expected Utility-Entropy (EU-E) decision model, which is a weighted linear average of normalized expected utility and information entropy. Based on the normalized EU-E decision model, we establish a normalized EU-E investment decision model. Then we apply the model to stock selection when we invest in the 40 sample stocks of Shenzhen component index. It has concluded that portfolios of 4 stocks selected by normalized EU-E model with larger tradeoff coefficient λ are more efficient than that of those selected with smaller tradeoff coefficient λ with relative general utility function. Thus, this has demonstrated that we should not only take the expected utility of a risky action itself into account but also the information entropy to measure the uncertainty of the state of nature, which further verified the usefulness of the information entropy.