IMECH-IR  > 流固耦合系统力学重点实验室
Dynamic financial contagion prediction model based on fuzzy information granularity SVM
Liu L1; Shao YF(邵颖峰)2; Hui XF1
Source PublicationCINTI 2013 - 14th IEEE International Symposium on Computational Intelligence and Informatics, Proceedings
2013
Pages545-550
Conference Name14th IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2013
Conference DateNovember 19, 2013 - November 21, 2013
Conference PlaceBudapest, Hungary
AbstractContagion 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. © 2013 IEEE.
KeywordArtificial intelligence Finance Information granules Support vector machines Arrival time Empirical analysis Financial contagions Financial crisis Fuzzy information nonlinear similarity Prediction model Similarity indices
ISBN9781479901975
Indexed ByEI
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://dspace.imech.ac.cn/handle/311007/77992
Collection流固耦合系统力学重点实验室
Affiliation1.School of Management, Harbin Institute of Technology, Harbin, China;
2.State Key Laboratory of Nonlinear Mechanics (LNM), Institute of Mechanics, Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Liu L,Shao YF,Hui XF. Dynamic financial contagion prediction model based on fuzzy information granularity SVM[C],2013:545-550.
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