Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Markov Switching GARCH models for Bayesian Hedging on Energy Futures Markets
Monica Billio, Roberto Casarin, Anthony Osuntuyi

Last modified: 2013-06-14

Abstract


We propose Bayesian Markov Switching Generalized Autoregressive Conditional Heteroscedasticity(MS-GARCH) models for determining time-varying Minimum Variance (MV) hedge ratio in energy futures markets. We apply an efficient simulation based technique for inference and suggest a robust hedging strategy which accounts for model parameter uncertainty. The hedging model is further applied to crude oil and gasoline spot and futures markets.

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