through the history and since 1933, the iranian rial has declined from 11.2 rials per dollar to almost 8600 rials per dollar today in the parallel or black market. at the same time the official rate has been kept at artificial level most of the time, not consistent with other macro conditions of the country. historically, however, the central bank has adjusted the official rate and brought it i...

The foreign currency exchange market is the highest and most liquid of the financial markets, with an estimated $1 trillion traded every day. Foreign exchange rates are the most important economic indices in the international financial markets. The prediction of them poses many theoretical and experimental challenges. This paper reports empirical proof that a neural network model is applicable ...

this paper analyzes the effects ofexchange policies on iran,s foreign trade, by applying new econometric techniques. in assessing the impacts of depreciation of the national currency on macroeconomic variable, the real rather than nominal exchange rate has been determined to be more appropriate criterion to demonstrate the success or failure ofthe adopted policies. during the period under the s...

This paper presents the application of six nonlinear ensemble architectures to forecasting the foreign exchange rates in the computational intelligence paradigm. Intelligent techniques such as Backpropagation neural network (BPNN), Wavelet neural network (WNN), Multivariate adaptive regression splines (MARS), Support vector regression (SVR), Dynamic evolving neuro-fuzzy inference system (DENFIS...

This paper presents a new option that can be used by agents for managing foreign exchange risk. Unlike the Garman Kolhagen model [1], (GK), this paper presents a new model with a preset exchange rate (PE), that allows the agent to take advantage of the his/her view on both the direction and magnitude of rate movement and as such provides this agent with more choices. The model has a provision f...