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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...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Universidad de Medellín
2013-06-01
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| Colecção: | Revista Ingenierías Universidad de Medellín |
| Assuntos: | |
| Acesso em linha: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1692-33242013000100012&lng=en&tlng=en |
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