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Financial Risk and Management Reviews

June 2015, Volume 1, 2, pp 53-67

Stock Market Index Prediction with Neural Network during Financial Crises: A Review on Bist-100



Mehmet YAVUZ


Aslan Deniz KARAOÄžLAN



Åžakir SAKARYA 1
Mehmet YAVUZ 2

Aslan Deniz KARAOÄžLAN 3
Necati ÖZDEMİR 4

  1. Balikesir University, Department of Business Administration, Cağiş Campus, Balıkesir, Turkey 1

  2. Necmettin Erbakan University, Fakulty of Science, Department of Mathematics-Computer Sciences, Meram, Konya, Turkey 2

  3. Balikesir University, Department of Industrial Engineering, Cağiş Campus, Balıkesir, Turkey 3

  4. Balikesir University, Department of Mathematics, Cağiş Campus, Balıkesir, Turkey 4

Pages: 53-67

DOI: 10.18488/journal.89/2015.1.2/

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Predetermining the future value of a variable is both quite important and rather difficult process in financial markets. In this context, especially in the last 15 years, Artificial Neural Networks (ANNs) are widely used in order to resolve various kinds of financial problems such as performing portfolio construction, stock index, and bankruptcy prediction. This study examines the predictability of daily and weekly returns of Borsa İstanbul (BIST)-100 Index during global crisis period (July 2007-December 2009) by using ANN. It differs from other similar studies in the literature as it: i) covers global crisis period, ii) predicts index value of the next day and next week and finally iii) uses seven different economic parameters (variables) as input. The results obtained suggest that ANN can be used quite successfully in this area and foresee correctly the value for next day and next week with an accuracy margin error of less than 5% even for unknown samples. The ANN model in this study is developed using MATLAB R2008b.

Contribution/ Originality




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