Abstract:
Nowadays, forecasting of exchange rates
plays an important role in international
economics. Additional to basic economic and
financial news, investors and traders employ in
their decision process technical tools to analyze
the transaction data.
In this paper, the system based on neural
networks implemented for forecasting Myanmar
Currency exchange ratesusing artificial neural
network. The system uses back-propagation
algorithm to train the exchange rates. Feed
forward neural network is used to improve the
efficiency of the back-propagation. Multilayer
Perceptron (MLP) network is the main
architecture. Network architecture parameters
especially number of input and number of hidden
layers are analyzed.System performance is
evaluated in terms of Mean Absolute Error
(MAE). Daily historical price data for currency
pairs for the last three years are inputted to the
system. The system is implemented using
programming language C#.
