In recent years the interest of the investors in e±cient methods for the forecasting price trend of a share in financial markets has grown steadily. The aim is to accurately forecast the future behavior of the market in order to identificate the so-called "correct timing". In this paper we analyze three di®erent approaches for forecasting financial data: Autoregression, artificial neural networks and support vector machines and we will determine potentials and limits of these methods. Application to the Italian financial market is also presented.

Autoregression and artificial neural networks for financial market forecast

DE LEONE, Renato;
2006

Abstract

In recent years the interest of the investors in e±cient methods for the forecasting price trend of a share in financial markets has grown steadily. The aim is to accurately forecast the future behavior of the market in order to identificate the so-called "correct timing". In this paper we analyze three di®erent approaches for forecasting financial data: Autoregression, artificial neural networks and support vector machines and we will determine potentials and limits of these methods. Application to the Italian financial market is also presented.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11581/115686
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