 Stock Market Index Prediction with Neural Network during Financial Crises: A Review on Bist-100Şakir Sakarya, Mehmet Yavuz, Aslan Deniz Karaoğlan and Necati Özdemi̇r Financial Risk and Management Reviews, 2015, vol. 1, issue 2, 53-67 Abstract: 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. Keywords: Financial crises; Artificial neural networks; Index forecasting; BIST-100 index (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:pkp:frmrev:v:1:y:2015:i:2:p:53-67:id:1718 Access Statistics for this article More articles in Financial Risk and Management Reviews from Conscientia Beam |
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