Revistes Catalanes amb Accés Obert (RACO)

A heuristic forecasting model for stock decision

D. Zhang, Q. Jiang, X. Li

Resum


This paper describes a heuristic forecasting model based on neural networks
for stock decision-making. Some heuristic strategies are presented for
enhancing the learning capability of neural networks and obtaining better
trading performance. The China Shanghai Composite Index is used as case
study. The forecasting model can forecast the buying and selling signs according
to the result of neural network prediction. Results are compared
with a benchmark buy-and-hold strategy. The forecasting model was found
capable of consistently outperforming this benchmark strategy.

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