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In a number of earlier studies it has been demonstrated that the traditional regression‐based static approach is inappropriate for hedging with futures, with the result that a variety of alternative dynamic hedging strategies have emerged. In this study the authors propose a class of new copula‐based GARCH models for the estimation of the optimal hedge ratio and compare their effectiveness with that of other hedging models, including the conventional static, the constant conditional correlation (CCC) GARCH, and the dynamic conditional correlation (DCC) GARCH models. With regard to the reduction of variance in the returns of hedged portfolios, the empirical results show that in both the in‐sample and out‐of‐sample tests, with full flexibility in the distribution specifications, the copula‐based GARCH models perform more effectively than other dynamic hedging models. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:1095–1116, 2008

In this paper we analyze the least-squares estimator of the change point for fractionally integrated processes with fractionally differencing parameter À0X5 , d , 0X5. When there is a one-time change, we show that the least-squares estimator is consistent and that the rate of convergence depends on d. When there is no change, we ®nd that the least-squares estimator converges in probability to the set f0, 1g for À0X5 , d < 0 but is likely to suggest a spurious change for 0 , d , 0X5. Simulations are also used to illustrate the asymptotic analysis.

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