Markov switching GARCH models for Bayesian hedging on energy futures markets

Effective hedging strategies on oil spot and future markets are relevant in reducing price volatility for investors, energy traders and companies operating in the oil markets. A new Bayesian multi-chain Markov-switching GARCH model for dynamic hedging in energy futures markets is developed. It builds on the construction of a system of simultaneous equations for the return dynamics on the hedged portfolio and the futures. The implication of our model for portfolios allocation and energy trading are manyfold. First, our formulation allows for an easy identification of the different states of the discrete processes as volatility regimes. Secondly, the use of regime-switching models with multiple chains allows for an effective way to reduce risk. Furthermore, correlated chains are more flexible than single chain models since they account for co-movement in the volatility regimes of different markets thus they should be preferred in turbulent periods (e.g. financial crisis). Finally, the combination of the expected utility framework with the regime-switching structure allows us to define a robust minimum variance hedging strategy. Changes in the optimal hedging strategies before and after the financial crisis are evidenced when the proposed robust hedging strategy is applied to crude oil spot and futures markets. It is therefore recommended that many and different models should be used in place of a single one in energy risk hedging since they could perform differently in various phases of the market