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...

Artificial neural networks (ANNs) have been applied to time series forecasting. Genetic algorithm (GA) can be used as an optimization search scheme to determine the near optimal architecture and parameters of a neural network, as well. In this study a rich evolutionary connectionist model is proposed, in which GA is used to determine the optimum number of input and hidden nodes of a feedforward...

in this paper, the value of exchange rate was calculated in order to determine comparative advantage in crops of sari township during 2009-2010. hence, first, comparative advantage indices are estimated by using a policy analysis matrix. the results showed that just wheat has a drc index of one in the minimum amount of national currency exchange rate value. this indicated the fact that only whe...

In this study, financial assets such as exchange rate, KOSPI index, and interest rate (3-year government bond) were predicted using the vector error correction model used in various markets. For purpose, time series data from February 2000 to January 2021 provided by Bank of Korea used. To estimate prediction model, stability variables was confirmed ADF test, causal relationship between Granger...

Prediction of nonlinear and nonstationary time series datasets can be achieved by using support vector regression. To improve the accuracy, we propose a new model ‘averaging intrinsic mode function’ which is a derivative of empirical mode decomposition to filter datasets of an exchange rate, followed by using a new algorithm of multiclass Support Vector Regression (SVR) for prediction. Simulati...

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 ...

abstract according to the importance of date export in iran, this study investigates short run and long run relationship between date export and important economical variable, specifically exchange rate. for this purpose, an autoregressive distributed lag approach (ardl) to cointegration is applied to annually time-series data from 1981 to 2007. results showed that the exchange rate, export pri...