Title :
A Business Intelligent Model for Market Risk Measurement
Author :
Chen, Xiaoliang ; Lai, Kin Keung
Author_Institution :
Dept. of Manage. Sci., City Univ. of Hong Kong, Hong Kong
Abstract :
In this study, we propose a business intelligent model integrating econometric models, i.e. ARMA, GARCH, and ANN models for VaR estimation. The business intelligent model achieves better efficiency in input variables selecting because they are selected and newly created by time series models. Repetitive trial error process could be effectively eliminated to one time series process. On the other hand, the performance of traditional time series models could be further enhanced by the forecasting power of ANN models. Empirical study shows that the business intelligent model can improve the predictive power in the framework of both accuracy and reliability.
Keywords :
business data processing; competitive intelligence; time series; business intelligent model; market risk measurement; repetitive trial error process; time series models; Artificial intelligence; Artificial neural networks; Econometrics; Economic forecasting; Input variables; Neural networks; Predictive models; Reactive power; Risk management; Smoothing methods; ARMA; GARCH; VaR; business intelligence; neural networks;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.457