Abstract
Article history: Received October 10, 2011 Received in Revised form November, 14, 2011 Accepted 8 December 2011 Available online 12 December 2011 In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used. © 2012 Growing Science Ltd. All rights reserved.
Highlights
Concerning the size and importance of financial markets, foreign exchange market (FOREX) is the biggest and the most important one in the world (Baillie & McMahon, 1989)
The use of external factors for improving the prediction accuracy has been used in many financial time series but there is a lack of studying external factors in foreign exchange rate time series
Our model shows better results than the simple Multilayer Perceptron (MLP) model presented by Yao and Tan in 2000
Summary
Concerning the size and importance of financial markets, foreign exchange market (FOREX) is the biggest and the most important one in the world (Baillie & McMahon, 1989). This important financial market has a 3.98$ trillion US dollars turnover per day (Bank of International Settlements, 2010). Lack of a central or physical place is a distinguishing characteristic of FOREX as an over the counter (OTC) market. This is the feature by which FOREX- a 24*7 market- is differentiated from other stock markets with artificial time regulations that cause limitations in modeling and prediction methods (Berardia, & Serva, 2005). The collapse of Bretton-Woods agreement, which was an attempt to define the exchange rate in a fixed regime, resulted in a rise in the number of researches on the prediction of exchange rate time series in 1970s
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