{"title":"跟踪概念漂移的配对评估方法:在对冲基金操作中的应用","authors":"Masabumi Furuhata, T. Mizuta, J. So","doi":"10.1109/ICDMW.2010.131","DOIUrl":null,"url":null,"abstract":"In order to deal with sudden unexpected changes of circumstances, we propose a new forecast method based on paired evaluators, the stable evaluator and the reactive evaluator. These two evaluators are good at detecting consecutive concept drifts. We conduct a back-testing using financial data in order to demonstrate the performance of our proposing forecast method. The results of the back-testing show that our method is effective and robust even against the late-2000s recessions.","PeriodicalId":170201,"journal":{"name":"2010 IEEE International Conference on Data Mining Workshops","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Paired Evaluators Method to Track Concept Drift: An Application for Hedge Funds Operations\",\"authors\":\"Masabumi Furuhata, T. Mizuta, J. So\",\"doi\":\"10.1109/ICDMW.2010.131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to deal with sudden unexpected changes of circumstances, we propose a new forecast method based on paired evaluators, the stable evaluator and the reactive evaluator. These two evaluators are good at detecting consecutive concept drifts. We conduct a back-testing using financial data in order to demonstrate the performance of our proposing forecast method. The results of the back-testing show that our method is effective and robust even against the late-2000s recessions.\",\"PeriodicalId\":170201,\"journal\":{\"name\":\"2010 IEEE International Conference on Data Mining Workshops\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Data Mining Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMW.2010.131\",\"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 Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2010.131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Paired Evaluators Method to Track Concept Drift: An Application for Hedge Funds Operations
In order to deal with sudden unexpected changes of circumstances, we propose a new forecast method based on paired evaluators, the stable evaluator and the reactive evaluator. These two evaluators are good at detecting consecutive concept drifts. We conduct a back-testing using financial data in order to demonstrate the performance of our proposing forecast method. The results of the back-testing show that our method is effective and robust even against the late-2000s recessions.