{"title":"基于模糊信息粒度支持向量机的金融传染动态预测模型","authors":"Lin Liu, Y. Shao, X. Hui","doi":"10.1109/CINTI.2013.6705257","DOIUrl":null,"url":null,"abstract":"Contagion time prediction is an important research topic in financial crises. This article put forward a prediction model of contagion time based on fuzzy information granularity SVM. It uses granularity fuzzy and SVM to estimate the bounds of stock index, and further forecast the similarity index. The predicted contagion time from the United States to the United Kingdom, Germany, Frence and China are tested, and compared with the real ones. The empirical analyses comfirm that the model is a feasible method to predict the financial contagion arrival time.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic financial contagion prediction model based on fuzzy information granularity SVM\",\"authors\":\"Lin Liu, Y. Shao, X. Hui\",\"doi\":\"10.1109/CINTI.2013.6705257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Contagion time prediction is an important research topic in financial crises. This article put forward a prediction model of contagion time based on fuzzy information granularity SVM. It uses granularity fuzzy and SVM to estimate the bounds of stock index, and further forecast the similarity index. The predicted contagion time from the United States to the United Kingdom, Germany, Frence and China are tested, and compared with the real ones. The empirical analyses comfirm that the model is a feasible method to predict the financial contagion arrival time.\",\"PeriodicalId\":439949,\"journal\":{\"name\":\"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINTI.2013.6705257\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINTI.2013.6705257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic financial contagion prediction model based on fuzzy information granularity SVM
Contagion time prediction is an important research topic in financial crises. This article put forward a prediction model of contagion time based on fuzzy information granularity SVM. It uses granularity fuzzy and SVM to estimate the bounds of stock index, and further forecast the similarity index. The predicted contagion time from the United States to the United Kingdom, Germany, Frence and China are tested, and compared with the real ones. The empirical analyses comfirm that the model is a feasible method to predict the financial contagion arrival time.