{"title":"探索风险管理工具","authors":"K. Ng, G. Sheblé","doi":"10.1109/CIFER.2000.844601","DOIUrl":null,"url":null,"abstract":"Operations research tools vary significantly. In this paper, several operations research tools that can handle uncertainty are investigated. They include sensitivity analysis, parametric analysis, mean-variance analysis, stochastic linear programming, fuzzy linear programming, and value at risk (VaR). In addition, these tools are compared and contrasted based on their applicability, time, and technical requirements.","PeriodicalId":308591,"journal":{"name":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Exploring risk management tools\",\"authors\":\"K. Ng, G. Sheblé\",\"doi\":\"10.1109/CIFER.2000.844601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Operations research tools vary significantly. In this paper, several operations research tools that can handle uncertainty are investigated. They include sensitivity analysis, parametric analysis, mean-variance analysis, stochastic linear programming, fuzzy linear programming, and value at risk (VaR). In addition, these tools are compared and contrasted based on their applicability, time, and technical requirements.\",\"PeriodicalId\":308591,\"journal\":{\"name\":\"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIFER.2000.844601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIFER.2000.844601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Operations research tools vary significantly. In this paper, several operations research tools that can handle uncertainty are investigated. They include sensitivity analysis, parametric analysis, mean-variance analysis, stochastic linear programming, fuzzy linear programming, and value at risk (VaR). In addition, these tools are compared and contrasted based on their applicability, time, and technical requirements.