1. OAR@UM
  2. External Research Collection
  3. Social Sciences
  4. Finance
  5. International Journal of Finance, Insurance and Risk Management (JFIRM)
  6. 2014
  7. Volume 4, Issue 3, 2014
Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/70872
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dc.contributor.authorBilgin Kılıç, Süleyman-
dc.contributor.authorPaksoy, Semin-
dc.contributor.authorGenç, Tolga-
dc.date.accessioned2021-03-10T08:54:34Z-
dc.date.available2021-03-10T08:54:34Z-
dc.date.issued2014-
dc.identifier.citationBilgin 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.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/70872-
dc.description.abstractIn 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.en_GB
dc.language.isoenen_GB
dc.publisherISMASYSTEMS Scientific Researchen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectStocksen_GB
dc.subjectForecasting -- Economic aspectsen_GB
dc.subjectNeural networks (Computer science)en_GB
dc.subjectBack propagation (Artificial intelligence)en_GB
dc.titleForecasting the direction of BIST 100 returns with artificial neural network modelsen_GB
dc.typearticleen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holderen_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.35808/ijfirm/105-
dc.publication.titleInternational Journal of Finance, Insurance and Risk Managementen_GB
Appears in Collections:Volume 4, Issue 3, 2014

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