Thesis supervisor: Dr. Hamed Tarkesh
Data of completion: 02/2009
Thesis Abstract: The foreign exchange market (Forex) is a global decentralized market for the trading of currencies which is responsible for determining foreign exchange rates for every national currency (e.g. US dollar, Euro, Yen, etc,). Predicting future currency exchange rates between different currencies is obviously of utmost importance for any international transactions, and can determine to a large extent the import-export policies on the macro economic level, as well as shaping individual financial transactions. In this work, we devised a novel closed-loop Artificial Neural Network (ANN) for time series analysis of the exchange rate. In particular, the ANN model was designed for predicting the future exchange rate between US dollar and Euro over a 10-day period. The model takes as input one-month histories of the exchange rate as well as other economic and social indicators of Europe and US (e.g. GDP, U.S.’s NASDAQ, S&P500, Dow Jones indices, Germany’s DAX index, etc.) to predict the future exchange rate. The accuracy of the model was tested using 5-fold cross validation techniques and resulted in a decent performance: 84% correct trend prediction (descending vs. ascending) and 78% correct prediction of the infliction point.