Yapay Sinir Ağlarıyla Hisse Senedi Fiyatları ve Yönlerinin Tahmini

Year 2015, Volume: 10 Issue: 3, 177 - 194, 01.12.2015

Muhammed Mustafa Tuncer Çalışkan Devran Deniz

Abstract

Finansal varlıkların fiyatları, çeşitli endekslerin değerleri gibi değişkenlerin önceden tahmini finans alanında oldukça önem arz etmekte ve bu konuda 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

Keywords

Yapay Sinir Ağı, İleri Beslemeli Ağ, Geri Yayılım Algoritması

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

Abstract

It is important to predict the value of variables like prices of financial assets and values of indexes. 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

Keywords

Artificial Neural Network, Feedforward Network, Backpropagation

References

• Aghababaeyan, R. vd. (2011), “Forecasting the Tehran Stock Market by Artificial Neural Network”, International Journal of Advanced Computer Science and Applications, Special Issue on Artificial Intelligence.
• Akcan, A., C. Kartal (2011) “İMKB Sigorta Endeksini Oluşturan Şirketlerin Hisse Senedi Fiyatlarının Yapay Sinir Ağları ile Tahmini”, Muhasebe ve Finansman Dergisi, 07- 2011,27-40. Beale, M. H. vd. (2014), “Neural Network Toolbox User’s Guide”, https://www.mathworks.com/help/pdf_doc/nnet/nnet_ug.pdf, (Erişim: 15.11.2014).
• Carvalhal, A., T. Riberio (2008), “Do Artificial Neural Networks Provide Better Forecasts? Evidence from Latin American Stock Indexes, Latin American Business Review, 8(3), 92-110.
• Chauhan, B. vd(2014), “Stock Market Prediction Using Artificial Neural Networks”, International Journal of Computer Science and Information Technologies (IJCSIT), 5 (1), 904-907.
• Diler, A.İ. (2003), “İMKB Ulusal-100 Endeksinin Yönünün Yapay Sinir Ağlarıyla Hata Geriye Yayma Yöntemi İle Tahmin Edilmesi”, İMKB Dergisi, 7(25-26), 65-81.
• Elmas, Ç. (2011), Yapay Zeka Uygulamaları, Ankara: Seçkin Yayıncılık, 2. Baskı Erdogan, E., H. Özyürek (2012), “Yapay Sinir Ağlarıyla Fiyat Tahminlenmesi”, Sosyal ve Beşeri Bilimler Dergisi, 4(1), 1309-8012.
• Fauset, Laurene (2011), Fundemantals of Neural Networks.
• Grudnitski, G. ve L. Osburn (1993), “Forecasting S&P and Gold Future Prices: An Application of Neural Network”, The Journal of Future Markets, 13(6), 631-643.
• “IBM SPSS Neural Networks 21”, http://www.sussex.ac.uk/its/pdfs/SPSS_Neural_Network_21, (Erişim: 19.12.2014).
• Jabin, S. (2014), “Stock Market PredictionUusing Feed-forward Artificial Neural Network”, International Journal of Computer Applications, 99 (9).
• Kara, Y. ve diğ. (2011), “Predicting Direction of Stock Price Index Movement Using Artificial Neural Networks and Support Vector Machines: The sample of The Istanbul Stock Exchange”, Expert Systems with Applications 38, 5311–5319.
• Karaatlı, M. vd. (2009), “Hisse senedi fiyat hareketlerinin yapay sinir ağıyla tahmin edilmesi”, Akademik Fener Dergisi, 2(1), 22-48.
• Kılıç, B. (2005), “Test of The Weak Form Efficient Market Hypothesis for The Istanbul Stock Exchange By Markov Chains Methodology”, Çukurova Üniversitesi Sosyal Bilimler Enstitüsü, 14(1), 333-342.
• Kıyılar, M. (1998), “Etkin Pazar Kuramının Test Edilmesi”, Yönetim, 9(29),34-51. Kutlu, B. ve B. Bodur (2009), “Yapay Sinir Ağları ile Borsa Endeksi Tahmini”, Yönetim Dergisi, 20(63).
• Lin, C.T. ve H. Y. Yeh (2009), “Emprical of Taiwan Stock Index Option Price Forecasting Model- Applied Artificial Neural Network”, Applied Economics,41, 1965-1972.
• McNelis, P.D. (1996), “A Neural Network Analysis of Brazillian Stock Price: Tequila Effects vs. Pisco Sour Effects”, Journal of Emerging Markets, 1(2).
• Naeini, M. P. vd. (2010), “Stock Market Value Prediction Using Neural Networks”, International Conference on Computer Information Systems and Industrial Management Applications (CSIM).
• Özalp, A., A.S. Anagün (2001), “Hisse Senedi Fiyat Tahmininde Yapay Sinir Ağı Yaklaşımı ve Klasik Tahminleme Yöntemleri ile Karşılaştırılması”, Endüstri Mühendisliği Dergisi, 12(3-4), 2-17.
• Patel, M. B., S.R. (2014), Yalamalle, “Stock Price Prediction Using Artificial Neural Network” International Journal of Innovative Research in Science, Engineering and Technology ,3(6).
• Shah, M. et al. (2014), “Performance Analysis of Neural Network Algorithms on Stock Market Forecasting”, International Journal Of Engineering And Computer Science, 3(9), 8347-8351.
• Şenol, D. (2008), “Prediction of Stock Price Direction By Artificial Neural Network Approach”, Master Thesis, Bogazici University.
• Toraman, C. (2008), “Demir Çelik Sektöründe Yapay Sinir Ağları ile Hisse Senedi Fiyat Tahmini: Erdemir A.Ş ve Kardemir A.Ş. Üzerine Bir Tahmin Uygulaması”, Muhasebe ve Finansman Dergisi; 39, 20-32.
• Ticknor, J.L. (2013), “A Bayesian Regularized Artificial Neural Network for Stock Market Forecasting”, Expert Systems with Applications, 40, 5501-5506.
• Vaisla, K.S. ve A.K. Bhatt (2010), “An Analysis of the Performance of Artificial Neural Network Technique for Stock Market Forecasting”, International Journal on Computer Science and Engineering,2(6), 2104-2109.
• White, H. (1988), “Economic Prediction Using Neural Network: The Case of IBM Daily Stock Return”, IEEE International Conference on Neural Networks, 2(1), 451-458.
• Yıldız, B. (2009), Finansal Analizde Yapay Zeka, Detay Yayıncılık, Ankara.
• Zekic, M. (1998), “Neural Network Application in Stock Market Predictions- A Methodology Analysis”, Proc. of 9. Intl’ Conf. Information and Intelligent Systems