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Morgan Stanley Capital International Turkiye Endeksinin Yapay Sinir Aglari ile Ongorusu

Author

Listed:
  • Nuray GUNERI TOSUNOGLU

    (Gazi Universitesi, Ticaret ve Turizm Egitim Fakultesi, Bilgisayar Uygulamalari Egitimi Bolumu)

  • Yasemin KESKIN BENLI

    (Gazi Universitesi, Endustriyel Sanatlar Egitim Fakultesi, Isletme Egitimi Bolumu)

Abstract

Zaman serisi analizi ile borsa endeksinin gelecek degerlerini ongorme, finans alaninda oldukca ilgi goren bir konudur. Borsa endeks ongorusu icin kullanilan farkli zaman serisi yontemleri bulunmaktadir. Bu yontemlerden biri, son yillarda bircok arastirmada kullanildigi gorulen Yapay Sinir Aglari (YSA)’dir. Yapay sinir aglarinin, diger zaman serisi yontemleri ile karsilastirildiginda, bazi on kosullar gerektirmemesi ve esnek bir modelleme yapisi olmasi nedeniyle daha ustun oldugu yapilan calismalarla ortaya konulmustur. Bu calismada Morgan Stanley Capital International (MSCI) Turkiye endeksinin aylik degerlerine iliskin ongorulerin yapay sinir aglari ile elde edilmesi amaclanmistir. Calismanin verileri Aralik 1987-Agustos 2008 donemini kapsamaktadir. Uygulamada, 12 girdi, 11 gizli ve 1 cikti noronundan olusan ileri beslemeli bir ag modeli kullanilmistir. Performans olcutu, hata kareler ortalamasinin karekoku olarak secilmis ve degeri 0,1131 olarak hesaplanmistir. Calisma sonucunda YSA ile endeks degerlerine iliskin, basarili ongoruler elde edilmistir.True Value Added (TVA), Market Value Added (MVA), Cash Flow Return on Investment (CFROI) and Cash Value Added (CVA), respectively. In this study, the weights of the performance measures are obtained by using FAHP. The companies are ranked with respect to their strategic financial performance measures’ values for each year for the period 1998-2011, and also ranked with respect to the average values of these measures for the related period by using the VIKOR method.

Suggested Citation

  • Nuray GUNERI TOSUNOGLU & Yasemin KESKIN BENLI, 2012. "Morgan Stanley Capital International Turkiye Endeksinin Yapay Sinir Aglari ile Ongorusu," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 12(4), pages 541-547.
    • Handle: RePEc:ege:journl:v:12:y:2012:i:4:p:541-547
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    Cited by:

    1. Nuray Tosunoğlu & Hilal Abacı & Gizem Ateş & Neslihan Saygılı Akkaya, 2023. "Artificial neural network analysis of the day of the week anomaly in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.

    More about this item

    Keywords

    Borsa; MSCI Turkiye endeksi; zaman serisi analizi; yapay sinir aglari; ongoru;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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