Using artificial neural network models in stock market index prediction

Expert Systems with Applications

Volumn 38, Issue 8, 2011, Pages 10389-10397

  Guresen, Erkam ^a   Kayakutlu, Gulgun ^a   Daim, Tugrul U ^b  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

^b PORTLAND STATE UNIVERSITY   (United States)

Author keywords

Dynamic artificial neural networks (DAN2); Financial time series (FTS) prediction; Hybrid forecasting models; Recurrent neural networks (RNN)

Indexed keywords

ACCURATE PREDICTION; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; FINANCIAL PROBLEMS; FINANCIAL TIME SERIES (FTS) PREDICTION; GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY; HYBRID FORECASTING MODELS; HYBRID MODEL; HYBRID NEURAL NETWORKS; INPUT VARIABLES; MARKET PREDICTION; MULTI LAYER PERCEPTRON; NEURAL NETWORK MODEL; NONLINEAR APPROACH; STOCK EXCHANGE; STOCK MARKET INDEX;

FINANCIAL DATA PROCESSING; FORECASTING; MEAN SQUARE ERROR; TIME SERIES;

RECURRENT NEURAL NETWORKS;

EID: 79953724824     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.02.068     Document Type: Article

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