Article ID: | iaor2001283 |
Country: | United Kingdom |
Volume: | 27 |
Issue: | 3 |
Start Page Number: | 373 |
End Page Number: | 380 |
Publication Date: | Jun 1999 |
Journal: | OMEGA |
Authors: | Patuwo B.E., Indro D.C., Jiang C.X., Zhang G.P. |
Keywords: | neural networks, time series & forecasting methods |
This study utilizes an artificial neural network (ANN) approach to predict the performance of equity mutual funds that follow value, blend and growth investment styles. Using a multi-layer perceptron model and GRG2 nonlinear optimizer, fund-specific historical operating characteristics were used to forecast mutual funds' risk-adjusted return. Results show that ANN generates better forecasting results than linear models for funds of all styles. In addition, our model outperforms that of Chiang