USING A DYNAMIC ARTIFICIAL NEURAL NETWORK FOR FORECASTING THE VOLATILITY OF A FINANCIAL TIME SERIES

Revista Ingenierías Universidad de Medellín

Juan D. Velásquez¹  Carlos J. Franco¹  Sarah Gutiérrez¹ 

[1] Universidad Nacional de Colombia;

关键词: Pronóstico de la volatilidad;    modelos no lineales;    heterocedasticidad;   

DOI  :  

来源: DOAJ

【 摘 要 】

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 predicting in-sample and out-of-sample variance that the other considered models for the used dataset. Thus, the value of this neural network as a predictive tool is demonstrated.

【 授权许可】

Unknown