Probability of trend prediction of exchange rate by ANFIS

Modelling the human behaviour in the market of the exchange rate was always an important challenge for the researchers. Financial markets are influenced by many economical, political and even psychological factors and so it is very difficult to forecast the movement of future values. Many traditional methods were used to help forecasting short-term foreign exchange rates. In their effort to achieve better results many researchers started to use soft computing techniques over the last years. In this paper a neuro-fuzzy model is presented. The model uses a time series data of daily quotes of the euro/dollar exchange rate in order to calculate the probability of the trend prediction as far as exchange rate. The data is divided into the training data, checking data and testing data. The model is trained using the training data and then the testing data is used for model validation.