The exchange rate plays an essential role for firms which export goods and import raw materials. In this paper, the effects of real specific exchange rate fluctuations in imports, exports and aggregate trade on industry sector, chemical and transportation industries outputs in 49 OIC countries were investigated by using a panel data model over 1990-2014. Particularly, this paper presents eviden...

I n this paper, the evaluation of the real exchange rate transfer and the asymmetric transmission of real exchange rate fluctuations to the export prices of food products for the country during the period (2001-2015) was studied using two approaches of PMG and GMM systems. The TGARCH method was used to calculate the real exchange rate fluctuation index and the Markov Switching method was u...

Artificial neural network; Exchange rate forecasting; Functional link artificial neural network (FLANN); Knowledge guided ANN model Abstract This paper presents a new adaptive forecasting model using a knowledge guided artificial neural network (KGANN) structure for efficient prediction of exchange rate. The new structure has two parallel systems. The first system is a least mean square (LMS) t...

exchange rate has the fundamental role as one of the economy key variables in determining the domestic price. so it is important to know how is the empirical relationship between the exchange rate and domestic prices and the factors influencing this relationship. the main objective of this study is to determine the effect of vehichel imports share on the exchange rate pass – through on domestic...

The present paper aims in investigating the performance of state-of-the-art machine learning techniques in trading with the EUR/USD exchange rate at the ECB fixing. For this purpose, five supervised learning classification techniques (K-Nearest Neighbors algorithm, Naïve Bayesian Classifier, Artificial Neural Networks, Support Vector Machines and Random Forests) were applied in the problem of t...

background: hepatitis b (hb) is a major global mortality. accurately predicting the trend of the disease can provide an appropriate view to make health policy disease prevention. this paper aimed to apply three different to predict monthly incidence rates of hb. methods: this historical cohort study was conducted on the hb incidence data of hamadan province, the west of iran, from 2004 to 2012....

The empirical “gravity” equation is extremely successful in explaining bilateral trade. This paper shows how a multi-country model of specialization and costly trade (i.e. a microfounded gravity model) can be applied to explain empirical exchange rate puzzles. One such puzzle is the fact that nominal exchange rates are enormously volatile, but that this volatility does not appear to affect infl...

This paper investigates the effect of exchange rate uncertainty on the Iran’s import trade. The exchange rate ‎uncertainty series were generated utilizing the TARCH model. This model analyzes the asymmetric effects. The analysis of uncertainty and asymmetry ‎of the exchange rate shows significant TARCH ‎effect on Iran’s exchange rates‎. The findings of the study indicate negative shocks (bad ne...

Recent studies have shown the classification and prediction power of the Neural Networks. It has been demonstrated that a NN can approximate any continuous function. Neural networks have been successfully used for forecasting of financial data series. The classical methods used for time series prediction like Box-Jenkins or ARIMA assumes that there is a linear relationship between inputs and ou...

One of the main issues in international finance is the ratio of exchange rate pass through to consumer prices. The main objective of this study is to examine the exchange rate fluctuations and its asymmetric effect on consumer prices in Iran’s economy. In the present study, the effects of positive and negative impacts of the exchange rate on inflation rate and other macroeconomic variables of I...