Markov Switching GARCH Models for Bayesian Hedging on Energy Futures Markets

31 Pages Posted: 10 Jun 2014

See all articles by Monica Billio

Monica Billio

Ca Foscari University of Venice - Dipartimento di Economia

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics

Ayokunle Anthony Osuntuyi

Ca Foscari University of Venice

Date Written: June 10, 2014

Abstract

A new Bayesian multi-chain Markov Switching GARCH model for dynamic hedging in energy futures markets is developed by constructing a system of simultaneous equations for the return dynamics on the hedged portfolio and futures. More specifically, both the mean and variance of the hedged portfolio are assumed to be governed by two unobserved discrete state processes, while the futures dynamics is driven by a univariate hidden state process. The noise in both processes are characterized by a MS-GARCH model. This formulation has two main practical and conceptual advantages. First, the different states of the discrete processes can be identified as different volatility regimes. Secondly, the parameters can be easily interpreted as different hedging components. Our formulation also provides an avenue to analyze the contribution of the volatility dynamics and state probabilities to the optimal hedge ratio at each point in time. Moreover, the combination of the expected utility framework with regime-switching models allows the definition of a robust minimum variance hedging strategy to also account for parameter uncertainty. Evidence of changes in the optimal hedging strategies before and after the financial crisis is found when the proposed robust hedging strategy is applied to crude oil spot and futures markets.

Keywords: Energy futures, GARCH, Hedge ratio, Markov-switching

JEL Classification: C1, C11, C15, C32, F31, G15

Suggested Citation

Billio, Monica and Casarin, Roberto and Osuntuyi, Ayokunle Anthony, Markov Switching GARCH Models for Bayesian Hedging on Energy Futures Markets (June 10, 2014). University Ca' Foscari of Venice, Dept. of Economics Research Paper Series No. 07/WP/2014, Available at SSRN: https://ssrn.com/abstract=2448131 or http://dx.doi.org/10.2139/ssrn.2448131

Monica Billio

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

HOME PAGE: http://www.unive.it/persone/billio

Roberto Casarin (Contact Author)

University Ca' Foscari of Venice - Department of Economics ( email )

San Giobbe 873/b
Venice, 30121
Italy
+39 030.298.91.49 (Phone)
+39 030.298.88.37 (Fax)

HOME PAGE: http://sites.google.com/view/robertocasarin

Ayokunle Anthony Osuntuyi

Ca Foscari University of Venice ( email )

Dorsoduro 3246
Venice, Veneto 30123
Italy

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