Abstract: Foreign exchange market is one of the most complex dynamic market with high volatility, non linear and irregularity. As the globalization spread to the world, exchange rates forecasting become more important and complicated. Many external factors influence its volatility. To forecast the exchange rates, those external variables can be used and usually chosen based on the correlation to the predicted variable. A new second correlation method to improve forecasting accuracy is proposed. The second correlation is used to choose the external variable with different time interval. The proposed method is tested using six major monthly exchange rates with Nonlinear Autoregressive with eXogenous input (NARX) compared with Nonlinear Autoregressive (NAR) for model benchmarking. We evaluated the forecasting accuracy of proposed method is increasing by 16.8% compared to univariate NAR model and slight better than linear correlation on average for Dstat parameter and gives almost no improvement for MSE.

Agus Sihabuddin, Subanar, Dedi Rosadi and Edi Winarko, “A Second Correlation Method for Multivariate Exchange Rates Forecasting” International Journal of Advanced Computer Science and Applications(IJACSA), 5(7), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050705

@article{Sihabuddin2014,
title = {A Second Correlation Method for Multivariate Exchange Rates Forecasting},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050705},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050705},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {7},
author = {Agus Sihabuddin and Subanar and Dedi Rosadi and Edi Winarko}
}