A Second Correlation Method for Multivariate Exchange Rates Forecasting

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.

Authors and Affiliations

Agus Sihabuddin, Subanar , Dedi Rosadi, Edi Winarko

Keywords

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  • EP ID EP162913
  • DOI 10.14569/IJACSA.2014.050705
  • Views 68
  • Downloads 0

How To Cite

Agus Sihabuddin, Subanar, Dedi Rosadi, Edi Winarko (2014). A Second Correlation Method for Multivariate Exchange Rates Forecasting. International Journal of Advanced Computer Science & Applications, 5(7), 30-33. https://europub.co.uk./articles/-A-162913