The effectiveness of dynamic hedging: evidence from selected European stock index futures

This paper estimates time-varying optimal hedge ratios (OHRs) using a bivariate generalized autoregressive conditional heteroscedastic (GARCH) error correction model. The GARCH specification accounts for time-varying distribution in asset returns while the error correction term preserves short-run deviations between two fundamentally linked assets. Using stock index and stock index futures from four European countries, we compare the hedging effectiveness of the GARCH error correction model with alternative hedging models that hold the OHR constant. Overall, in three out of four cases, the GARCH error correction model is shown to offer superior risk reduction compared with the competing models. Finally, we also estimate the OHRs using the GARCH-X model, which allows the error correction term to be a determinant of the time-varying volatility. The GARCH-X model performs similar to the GARCH error correction model. The results presented in this paper have important insights into the risk management of financial assets when returns distribution changes over time.