AN EXCHANGE RATE MODEL FOR TURKEY USING THE ARTIFICIAL NEURAL NETWORKS

Verilen kararlar.n ba/ar.l. olmas. yaln.zca karar vericilerin (hükümetler, üreticiler, tüketiciler, v.b.) davran./lar.na ba2l. olmay.p, ayn. zamanda gelece2i do2ru biçimde tahmin edebilme yetene2ine de ba2l.d.r. Tahmin modellemesi birçok ara/t.rma alan. ve ekonomi için büyük bir öneme sahiptir. Son y.llarda yapay sinir a2lar. (YSA) ekonomide tahmin amac.yla artan bir biçimde kullan.lmaya ba/lanm./t.r. Bu çal./mada hem YSA hem de vektör otoregresif metot (VAR) Türkiye için geli/tirilen döviz kuru modelinin çözümünde kullan.lmakta ve iki metodun sonuçlar. birbirleri ile kar/.la/t.r.lmaktad.r

AN EXCHANGE RATE MODEL FOR TURKEY USING THE ARTIFICIAL NEURAL NETWORKS

The success of decisions depends not only on the behaviors of decision makers (governments, producers, consumers, and so on) but also the ability of forecasting future correctly. Forecasting modeling has a great importance for many research areas as well as economics. In recent years artificial neural networks (ANNs) have increasingly been used for forecasting in economics. In this study both ANNs and vector auto regression method (VAR) are used to solve the exchange rate model developed for Turkey and the results obtained from the two methods are compared.

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Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi-Cover
  • ISSN: 1302-1966
  • Yayın Aralığı: Yılda 2 Sayı
  • Başlangıç: 1999
  • Yayıncı: Afyon Kocatepe Üniversitesi, İktisadi ve İdari Bilimler Fakültesi