{"title":"利用风险现金流进行流动性管理","authors":"B. Stoyanov, H.W. Wieczorrek, A. Antonov","doi":"10.1109/IS.2008.4670466","DOIUrl":null,"url":null,"abstract":"The article describes the methodology and practical implementation of Cash Flow at Risk (CFaR) calculation with the help of a multidimensional Monte Carlo simulation. CFar is one of the most important characteristics of liquidity. It assesses the likelihood that operating cash flows will drop below a prespecified level. In this paper is considered application for measuring CFaR under impact of different environment factors. The application is written in C# .NET.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Liquidity management using Cash Flow at Risk\",\"authors\":\"B. Stoyanov, H.W. Wieczorrek, A. Antonov\",\"doi\":\"10.1109/IS.2008.4670466\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article describes the methodology and practical implementation of Cash Flow at Risk (CFaR) calculation with the help of a multidimensional Monte Carlo simulation. CFar is one of the most important characteristics of liquidity. It assesses the likelihood that operating cash flows will drop below a prespecified level. In this paper is considered application for measuring CFaR under impact of different environment factors. The application is written in C# .NET.\",\"PeriodicalId\":305750,\"journal\":{\"name\":\"2008 4th International IEEE Conference Intelligent Systems\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 4th International IEEE Conference Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IS.2008.4670466\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 4th International IEEE Conference Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IS.2008.4670466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The article describes the methodology and practical implementation of Cash Flow at Risk (CFaR) calculation with the help of a multidimensional Monte Carlo simulation. CFar is one of the most important characteristics of liquidity. It assesses the likelihood that operating cash flows will drop below a prespecified level. In this paper is considered application for measuring CFaR under impact of different environment factors. The application is written in C# .NET.
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