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Yapay sinir ağlarıyla hisse senedi fiyatları ve yönlerinin tahmini

Forecasting the directions and prices of stocks by using artificial neural networks

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Abstract (2. Language): 
It is important to predict the value of variables like prices of financial assets and values of indexes. Various model are developed continuously for this aim. In addition to conventional forecasting methods (like linear/ nonlinear regression analysis, Random Walk, ARIMA, GARCH) Artificial Neural Networks is used for this aim recently. It was seen that Artificial Neural Networks produce more accurate results compared to conventional methods In this study, Artificial Neural Networks was formed to predict price directions and vaules of 30 stocks in BIST30. As a result, stock price directions are predicted with 58% accuracy on a daily basis. Mean absolute percentage error and mean absolute error were 1.80 % and 0.21 TL respectively according to predictions.
Abstract (Original Language): 
Finansal varlıkların fiyatları, çeşitli endekslerin değerleri gibi değişkenlerin önceden tahmini finans alanında oldukça önem arz etmekte ve bu konuda uzun zamandır çeşitli modeller geliştirilmektedir. Geleneksel tahmin teknikleri olan doğrusal ve doğrusal olmayan regresyon analizi, Random Walk, GARCH, ARIMA gibi modellerin yanı sıra son yıllarda Yapay Sinir Ağları bu alanda kullanım alanı bulmaya başlamış ve geleneksel tekniklere göre daha başarılı sonuçlar ürettiği görülmüştür. Bu çalışmada BİST30 endeksine ait 30 hisse senedinin günlük bazda fiyatları ve fiyat yönleri Yapay Sinir Ağları ile tahmin edilmiştir. Sonuçta BİST 30'daki hisse senetleri için günlük bazda fiyat yönü ortalama %58 oranında doğru tahmin edilmiştir. Yapılan tahminlerin ortalama mutlak yüzde hatası %1,80, ortalama mutlak hatası ise 21 Kuruş olmuştur.
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