Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/70872
Title: Forecasting the direction of BIST 100 returns with artificial neural network models
Authors: Bilgin Kılıç, Süleyman
Paksoy, Semin
Genç, Tolga
Keywords: Stocks
Forecasting -- Economic aspects
Neural networks (Computer science)
Back propagation (Artificial intelligence)
Issue Date: 2014
Publisher: ISMASYSTEMS Scientific Research
Citation: Bilgin Kılıç, S., Paksoy, S., & Genç, T. (2014). Forecasting the direction of BIST 100 returns with artificial neural network models. International Journal of Finance, Insurance and Risk Management, 4(3), 759-765.
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.
URI: https://www.um.edu.mt/library/oar/handle/123456789/70872
Appears in Collections:Volume 4, Issue 3, 2014

Files in This Item:
File Description SizeFormat 
Forecasting_the_direction_of_BIST_100_returns_with_artificial_neural_network_models.pdf331.17 kBAdobe PDFView/Open


Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.