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http://dx.doi.org/10.7465/jkdi.2015.26.6.1189

Using fuzzy-neural network to predict hedge fund survival  

Lee, Kwang Jae (Department of Information and Industrial Engineering, Yonsei University)
Lee, Hyun Jun (Department of Information and Industrial Engineering, Yonsei University)
Oh, Kyong Joo (Department of Information and Industrial Engineering, Yonsei University)
Publication Information
Journal of the Korean Data and Information Science Society / v.26, no.6, 2015 , pp. 1189-1198 More about this Journal
Abstract
For the effects of the global financial crisis cause hedge funds to have a strong influence on financial markets, it is needed to study new approach method to predict hedge fund survival. This paper proposes to organize fuzzy neural network using hedge fund data as input to predict hedge fund survival. The variables of hedge fund data are ambiguous to analyze and have internal uncertainty and these characteristics make it challenging to predict their survival from the past records. The object of this study is to evaluate the predictability of fuzzy neural network which uses grades of membership to predict survival. The results of this study show that proposed system is effective to predict the hedge funds survival and can be a desirable solution which helps investors to support decision-making.
Keywords
Fuzzy neural network; hedge fund; survival prediction;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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