USING NEURAL NETWORKS AND GENETIC ALGORITHMS TO PREDICT STOCK MARKET RETURNS

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Abstract
In this study we attempt to predict the daily excess returns of FTSE 500 and S&P 500
indices over the respective Treasury Bill rate returns. Initially, we prove that the excess
returns time series do not fluctuate randomly. Furthermore we apply two different types
of prediction models: Autoregressive (AR) and feed forward Neural Networks (NN) to
predict the excess returns time series using lagged values. For the NN models a Genetic
Algorithm is constructed in order to choose the optimum topology. Finally we evaluate
the prediction models on four different metrics and conclude that they do not manage to
outperform significantly the prediction abilities of naï ve predictors.

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关键词：Algorithms Algorithm Networks predict Genetic Networks Neural