DocumentCode
3322560
Title
Measuring of Value at Risk (VAR) on emerging stock markets by neural networks method
Author
Chen, Cheng-Te ; Hsieh, Chin-Shan
Author_Institution
Dept. of Manage. Inf. Syst., Far East Univ., Tainan, Taiwan
Volume
2
fYear
2010
fDate
5-7 May 2010
Firstpage
137
Lastpage
140
Abstract
This study using neural network method for estimating VAR in emerging stock markets include Chinese and Hong Kong stock markets. Empirical results showed that the neural network method has outperformed conventional methods (historical simulation (HS), variance/covariance and the Monte Carlo simulation) in estimating VAR.
Keywords
Monte Carlo methods; neural nets; stock markets; Chinese stock markets; Hong Kong stock markets; Monte Carlo simulation; historical simulation; neural networks method; value at risk; variance-covariance; Artificial intelligence; Artificial neural networks; Distributed computing; Economic forecasting; Loss measurement; Neural networks; Portfolios; Predictive models; Reactive power; Stock markets; Neural Networks; Value at Risk;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Communication Control and Automation (3CA), 2010 International Symposium on
Conference_Location
Tainan
Print_ISBN
978-1-4244-5565-2
Type
conf
DOI
10.1109/3CA.2010.5533637
Filename
5533637
Link To Document