Forecasting the Direction of BIST 100 Returns with Artificial Neural Network Models

Süleyman Bilgin Kılıç, Semin Paksoy and Tolga Genç

International Journal of Finance, Insurance and Risk Management, 2014, vol. 4, issue 3, 759

Abstract: In this paper, Artificial Neural Networks (ANN) models are used to forecast the direction of Borsa Istanbul 100 (BIST100) index returns. Weekly time-lagged values of exchange rate returns, gold price returns and interest rate returns are used as inputs to ANN models in the training process. Results of the study showed that BIST100 index returns follow a specific pattern in time. Estimated ANN models provide valuable information to the investors and that BIST100 stock market is not fully informational efficient.

Keywords: Stock Return; Forecasting; BIST100 index; Artificial Neural Networks; Back Propagation (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:ers:ijfirm:v:4:y:2014:i:3:p:759

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