{"title":"将金融发展指标纳入预警系统","authors":"Alexey Ponomarenko, Stas Tatarintsev","doi":"10.1016/j.jeca.2022.e00284","DOIUrl":null,"url":null,"abstract":"<div><p>We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators in addition to conventional imbalances measures. The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that combining financial imbalances and financial development indicators helps to improve the out-of-sample accuracy of the early warning system.</p></div>","PeriodicalId":38259,"journal":{"name":"Journal of Economic Asymmetries","volume":"27 ","pages":"Article e00284"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Incorporating financial development indicators into early warning systems\",\"authors\":\"Alexey Ponomarenko, Stas Tatarintsev\",\"doi\":\"10.1016/j.jeca.2022.e00284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators in addition to conventional imbalances measures. The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that combining financial imbalances and financial development indicators helps to improve the out-of-sample accuracy of the early warning system.</p></div>\",\"PeriodicalId\":38259,\"journal\":{\"name\":\"Journal of Economic Asymmetries\",\"volume\":\"27 \",\"pages\":\"Article e00284\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economic Asymmetries\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1703494922000445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Asymmetries","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1703494922000445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
Incorporating financial development indicators into early warning systems
We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators in addition to conventional imbalances measures. The evaluation of the model is conducted using a three-step procedure (i.e. training, validation and testing sub-samples). The results indicate that combining financial imbalances and financial development indicators helps to improve the out-of-sample accuracy of the early warning system.