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...

The geometric Lévy model (GLM) is a natural generalization of the geometric Brownian motion (GBM) model used in the derivation of the Black–Scholes formula. The theory of such models simplifies considerably if one takes a pricing kernel approach. In one dimension, once the underlying Lévy process has been specified, the GLM has four parameters: the initial price, the interest rate, the volatili...

Forward and spot exchange rates are modelled as an unrestricted bivariate autoregression from weekly data on the New York foreign exchange market for June, 1973 to April, 1980. The null hypothesis that the forward exchange rate is an unbiased estimate of the corresponding future spot exchange rate is tested by means of a nonlinear Wald test and is rejected for all six currencies considered. The...

This project presents the implementation prediction that can accuracy predict the foreign exchange rate. how the prediction accuracy can be improved by developing an ensemble model of the deep learning algorithm, Distributed Random forest and generalised linear model using sparkling water (Spark +H20). According to the researchers of literature review from 2000-2016, there are several models th...