Accuracy and Conservatism of VaR Models: A Wavelet Decomposed VaR Approach Versus Standard ARMA-GARCH Method

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 Value at Risk (VaR) perspective. A Wavelet-ARMA-GARCH refinement method to VaR estimate is used 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.