Research on Extreme Financial Risk Early Warning Based on ODR-ADASYN-SVM

DOI

10.2991/hsmet-17.2017.209How to use a DOI?

Keywords

ORD; ADASYN; support vector machine; extreme risk; early warning model

Abstract

this paper uses index of Shanghai and Shenzhen 300 as research object, it will combines with ODR, ADASYN and traditional SVM, it puts forward one kind of improved SVM model--ODR-ADASYN-SVM model to predict financial market extreme risk in China, and it also makes evaluation on precision, stability of risk early warning for this model, which has greatly enhanced unbalance sample learning ability of SVM and effectively overcome over-fitting of SMOTE, represents the superior extreme financial risk prediction ability, so it has certain practice and application value.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shuanglian Chen
PY  - 2017/02
DA  - 2017/02
TI  - Research on Extreme Financial Risk Early Warning Based on ODR-ADASYN-SVM
BT  - Proceedings of the 2017 International Conference on Humanities Science, Management and Education Technology (HSMET 2017)
PB  - Atlantis Press
SP  - 1132
EP  - 1137
SN  - 2352-5398
UR  - https://doi.org/10.2991/hsmet-17.2017.209
DO  - 10.2991/hsmet-17.2017.209
ID  - Chen2017/02
ER  -