Article ID: | iaor1997596 |
Country: | United Kingdom |
Volume: | 24 |
Issue: | 2 |
Start Page Number: | 205 |
End Page Number: | 215 |
Publication Date: | Apr 1996 |
Journal: | OMEGA |
Authors: | Urban T.L., Chiang W.-C., Baldridge G.W. |
Keywords: | time series & forecasting methods, neural networks |
In this paper, an artificial neural network method is applied to forecast the end-of-year net asset value (NAV) of mutual funds. The back-propagation neural network is identified and explained. Historical economic information is used for the prediction of NAV data. The results of the forecasting are compared to those of traditional econometric techniques (i.e. linear and nonlinear regression analysis), and it is shown that neural networks significantly outperform regression models in situations with limited data availability.