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Any company operating globally must deal in foreign currencies.It has to pay suppliers in other countries with a currency different from its home country’s currency.Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day.To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network.Even if a company expects to be paid in its own currency, it must assess the risk that the buyer may not be able to pay the full amount due to currency fluctuations.XE Currency Converter - Live Rates com/currencyconverter Calculate live currency and foreign exchange rates with this free currency converter.

The primary purpose is to ensure that foreign currency reports prepared by agencies are consistent with regularly published Treasury foreign currency reports regarding amounts stated in foreign currency units and U. This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process.

They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm.

Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. Profits or losses accrue as the exchange rate of that currency fluctuates on the open market.

In order to determine which is the fixed currency when neither currency is on the above list (i.e.

both are "other"), market convention is to use the fixed currency which gives an exchange rate greater than 1.000.

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