@article{ijbrm2018114,
author={{Mederessi, Samia and Hallara, Slaheddine},
title={A Wavelet-ARMA-GARCH Refinement Method to VaR Estimate for Foreign Exchange Market},
journal={International Journal of Business and Risk Management},
volume={1},
number={1},
pages={28--36},
year={2018},
url={http://pubs.sciepub.com/ijbrm/1/1/4},
abstract={With increasing internationalization of financial transactions, the foreign exchange market has been profoundly transformed and became more competitive and volatile. This places the accurate and reliable measurement of market risks in a crucial position for both investment decision and hedging strategy designs. This paper deals with the measurement of risks from a VaR perspective. A Wavelet-ARMA-GARCH refinement method to VaR estimate is proposed and compared with classical ARMA-GARCH approach. Performances of both approaches have been tested and compared using Kupiec backtesting procedures. Experiment results suggest that the performance of Wavelet-ARMA-GARCH refinement method to VaR estimate improves the reliability of VaR estimates at all confidence levels which offers considerable flexibility and potential performance improvement for Foreign exchange dealers. Furthermore, the appropriate selection and combination of parameters can lead to comprehensive performance improvement in reliability.},
doi={10.12691/ijbrm-1-1-4}
publisher={Science and Education Publishing}
}