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
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;
Conference_Titel :
Computer Communication Control and Automation (3CA), 2010 International Symposium on
Conference_Location :
Tainan
Print_ISBN :
978-1-4244-5565-2
DOI :
10.1109/3CA.2010.5533637
