In this paper we present the Radial Basis Neural Network Function. We examine some simple numerical examples of time-series in economics and finance. The forecasting performance is significant superior, especially in financial time-series, to traditional econometric modeling indicating that artificial intelligence procedure are more appropriate. Some MATLAB routines are presented for further application research
This research work investigates the possibility to apply several neural network architectures for si...
In this paper, authors apply feed-forward artificial neural network (ANN) of RBF type into the proce...
There has been increasing interest in the application of neural networks to the field of finance. Se...
In this paper, we implement an effective way for forecasting financial time series with nonlinear re...
The literature indicates that exchange rates are largely unforecastable from the fact that the overw...
The purpose of this research is to investigate the forecasting performance of Artificial Neural Netw...
Financial and economic time series forecasting has never been an easy task due to its sensibility to...
This paper is concerned with approximating nonlinear time series by an artificial neural network bas...
I propose a flexible nonlinear method for studying the time series properties of macroeconomic varia...
Neural network forecasting models have been widely used in the analyses of finan-cial time series du...
AbstractIn this paper, authors present a new approach in forecasting economic time series - applicat...
The main objective of this research paper is to highlight the global implications arising in financi...
Time series analysis and prediction are major scientific challenges that find their applications in ...
Summarization: Financial management maximise investors’ return, seeking for stocks with increasing e...
AbstractIn this paper, we investigate the volatility dynamics of EUR/GBP currency using statistical ...
This research work investigates the possibility to apply several neural network architectures for si...
In this paper, authors apply feed-forward artificial neural network (ANN) of RBF type into the proce...
There has been increasing interest in the application of neural networks to the field of finance. Se...
In this paper, we implement an effective way for forecasting financial time series with nonlinear re...
The literature indicates that exchange rates are largely unforecastable from the fact that the overw...
The purpose of this research is to investigate the forecasting performance of Artificial Neural Netw...
Financial and economic time series forecasting has never been an easy task due to its sensibility to...
This paper is concerned with approximating nonlinear time series by an artificial neural network bas...
I propose a flexible nonlinear method for studying the time series properties of macroeconomic varia...
Neural network forecasting models have been widely used in the analyses of finan-cial time series du...
AbstractIn this paper, authors present a new approach in forecasting economic time series - applicat...
The main objective of this research paper is to highlight the global implications arising in financi...
Time series analysis and prediction are major scientific challenges that find their applications in ...
Summarization: Financial management maximise investors’ return, seeking for stocks with increasing e...
AbstractIn this paper, we investigate the volatility dynamics of EUR/GBP currency using statistical ...
This research work investigates the possibility to apply several neural network architectures for si...
In this paper, authors apply feed-forward artificial neural network (ANN) of RBF type into the proce...
There has been increasing interest in the application of neural networks to the field of finance. Se...