Abstract
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.