This paper investigates the market-risk-hedging effectiveness of the Taiwan Futures Exchange (TAIFEX) stock index futures using daily settlement prices for the period from July 21, 1998 to December 31, 2010. The minimum variance hedge ratios (MVHRs) are estimated from the ordinary least squares regression model (OLS), the vector error correction model (VECM), the generalized autoregressive conditional heteroskedasticity model (GARCH), the threshold GARCH model (TGARCH), and the bivariate GARCH model (BGARCH), respectively. We employ a rolling sample method to generate the time-varying MVHRs for the out-of-sample period, associated with different hedge horizons, and compare across their hedging effectiveness and risk-return trade-off. In a one-day hedge horizon, the TGARCH model generates the greatest variance reduction, while the OLS model provides the highest rate of risk-adjusted return; in a longer hedge horizon, the OLS generates the largest variance reduction, while the BGARCH model provides the best risk-return trade-off. We find that the selection of appropriate models to measure the MVHRs depends on the degree of risk aversion and hedge horizon. | Hedging effectiveness of applying constant and timevarying hedge ratios Evidence from Taiwan stock index spot and futures
