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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.There are various ways to measure RER. Thus the real exchange rate is the exchange rate times the relative prices of a market basket of goods in the two countries.
The forward exchange rate refers to an exchange rate that is quoted and traded today but for delivery and payment on a specific future date.
In some areas of Europe and in the retail market in the United Kingdom, EUR and GBP are reversed so that GBP is quoted as the fixed currency to the euro.
The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average.
The moving average is supposed to enhance the outputs of the network using the error part of the original 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.