TY  - JOUR
AV  - public
Y1  - 2011///
EP  - 202
SN  - 0976-5697
N2  -  	In this paper we propose an alternative and modified Generalized Regression Neural Networks Autoregressive model (GRNN-AR) in S&P 500 and FTSE 100 index returns, as also in Gross domestic product growth rate of Italy, USA and UK. We compare the forecasts with Generalized Autoregressive conditional Heteroskedasticity (GARCH) and Autoregressive Integrated Moving Average (ARIMA) models. The results indicate that GRNN outperform significant the conventional econometric models and can be an efficient alternative tool for forecasting. The MATLAB algorithm we propose is provided in appendix for further applications, suggestions, modifications and improvements.
ID  - eprints1638
KW  - Autoregressive Moving Average
KW  -  Forecasting
KW  -  GARCH
KW  -  Generalized Regression Neural Networks
KW  -  MATLAB
KW  -  Stock Returns
TI  - Application of a Modified Generalized Regression Neural Networks Algorithm in Economics and Finance
JF  -  	International Journal of Advanced Research in Computer Science
SP  - 197
A1  - Giovanis, Eleftherios
VL  - 2
IS  - 2
UR  - http://www.ijarcs.info/?wicket:bookmarkablePage=:com.genxcellence.journal.pharmacy.web.issue.IssueDetail&target=1041&author=Eleftherios+Giovanis&country=United+Kingdom&title=Application+of+a+Modified+Generalized+Regression+Neural+Networks++Algorithm+in+Ec
ER  -