In finance, an exchange rate (also known as a foreign-exchange rate, forex rate, ER, FX rate or Agio) between two currencies is the rate at which one currency will be exchanged for another.
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.This reduces rounding issues and the need to use excessive numbers of decimal places.There are some exceptions to this rule: for example, the Japanese often quote their currency as the base to other currencies.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.
This report provides exchange rate information under Section 613 of Public Law 87-195 dated September 4, 1961 ( (b)) which gives the Secretary of the Treasury sole authority to establish the exchange rates for all foreign currencies or credits reported by all agencies of the government. The rates provided in this report are not meant to be used by the general public for conducting foreign currency conversion transactions.
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.
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.
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