When market returns follow a long memory volatility process, standard approaches to estimating dynamic minimum variance hedge ratios (MVHRs) are misspecified. Simulation results and an application to the S&P 500 index document the magnitude of the misspecification that results from failure to account for basis convergence and long memory in volatility. These results have important implications for the estimation of MVHRs in the S&P 500 example and other markets as well.

Markov switching vector error correction asymmetric long memory volatility models with fat tailed innovations are proposed. Bivariate two state versions of the models are applied to a futures hedge of the S&P500. Regime switches occur between high and low cost of carry states via changes in the error correction term or basis. Regime identification is therefore dominated by switches in the mean, not volatility. Relative to a number of alternatives, the proposed models provide superior out of sample forecasts of the covariance matrix particularly for horizons greater than 10days ahead. When hedging, Markov switching with long memory improves the tail risk of hedged returns beyond 10day horizons, however there is mixed support for models with volatility asymmetries. These findings have important implications for the development of multivariate models and other applications including portfolio management, spread option pricing and arbitrage.

The events triggered by the Global Financial Crisis (GFC) have led to calls for the regulation of financial markets. Given that regulation may involve opportunity costs, this paper examines whether tighter futures price limits can reduce the effectiveness of a futures hedge. We propose a new model that uncovers the underlying spot-futures dynamics when futures prices are subject to limits. We use the model to determine the maximum number of limit days that can occur before minimum variance hedging outcomes are adversely affected. Application of this model to the US soybean and corn markets reveals that existing limits do not reduce hedge effectiveness. If the frequency of limit days increases from current levels of 1% to approximately 3–4%, conventional hedging approaches will experience economically and statistically significant increases in portfolio variance. These results are important for hedgers, clearing houses and regulators in light of the recent calls for derivatives regulation.