مقایسه عملکرد پیش بینی شبکه عصبی و برابری قدرت خرید: مورد ترکیه

Investors consider foreign exchange as being among the most significant financial markets. Many discussions regarding economic development, growth strategies and stabilization policies place real exchange rate to play the most important role in the macroeconomic adjustment mechanism. This study compares a structural model and a statistical model, namely, purchasing power parity and artificial neural network models respectively, for the long term forecasting of exchange rates. Monthly data sets for the US dollar during the period of 1986–2010 and euro during the period of 1999–2010 are used. ANN has been confirmed as an effective tool in forecasting exchange rates through the evaluation of the empirical results. A possibility of extracting hidden information from the exchange rates and using this information to predict the future has been investigated by this technique. The average behavior of the above stated loss functions are estimated to form the basis for evaluating the proposed model.