Evaluating the hedging performance of the constant-correlation GARCH model

Abstract

This paper compares the performances of the hedge ratios estimated from the OLS (ordinary least squares) method and the constant-correlation VGARCH (vector generalized autoregressive conditional heteroscedasticity) model. These methods are evaluated based on the out-of-sample optimal hedge ratio forecasts. A systematic comparison is provided by examining ten spot and futures markets covering currency futures, commodity futures and stock index futures. Using a recently proposed test (Tse, 2000) for the constant-correlation assumption, it is found that the assumption cannot be rejected for eight of the ten series. To gain the maximum benefit of a time-varying hedging strategy the estimation data is kept up-to-date for the re-estimation of the hedge ratios. Both the constant hedge ratio (using OLS) and the timevarying hedge ratio (using constant-correlation VGARCH) are re-estimated on a day-by-day rollover, and the post-sample variances of the hedged portfolios are examined. It is found that the OLS hedge ratio performs better than the VGARCH hedge ratio. This result may be another indication that the forecasts generated by the VGARCH models are too variable.