USING A DYNAMIC ARTIFICIAL NEURAL NETWORK FOR FORECASTING THE VOLATILITY OF A FINANCIAL TIME SERIES
The ability to obtain accurate volatility forecasts is an important issue for the financial analyst. In this paper, we use the DAN2 model, a multilayer perceptron and an ARCH model to predict the monthly conditional variance of stock prices. The results show that DAN2 model is more accurate for pred...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad de Medellín
2013-06-01
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| Series: | Revista Ingenierías Universidad de Medellín |
| Subjects: | |
| Online Access: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1692-33242013000100012&lng=en&tlng=en |