Hedging with futures: Efficacy of GARCH correlation models to European electricity markets |
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| Authors: | Giovanna Zanotti Giampaolo Gabbi Manuela Geranio |
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| Affiliation: | 1. Newhuadu Business School, Minjiang University, Fuzhou 350108, China;2. Collaborative Innovation Center for Energy Economics and Energy Policy, China Institute for Studies in Energy Policy, Xiamen University, Xiamen, Fujian, 361005, PR China;3. China Center for Energy Economics Research, College of Economics, Xiamen University, Xiamen 361005, China;4. Department of Economics, University of Liberia, Capitol Hill, Monrovia, Liberia;5. Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen 361005, China;6. School of Business, University of Cape Coast, Cape Coast, Ghana;1. SignalDemand Inc., 101 California Street, Suite 1950, San Francisco, CA 94111, USA;2. Department of Industrial and Manufacturing Engineering, North Dakota State University, Dept 2485, P.O. Box 6050, Fargo, ND 58108, USA;1. London Business School, United Kingdom;2. Centrica Energy, United Kingdom;1. Indian Institute of Management Lucknow, Uttar Pradesh, India;2. Indian Institute of Management Raipur, Chhattisgarh, India |
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| Abstract: | European electricity markets have been subject to a broad deregulation process in the last few decades. We analyse hedging policies implemented through different hedge ratios estimation. More specifically we compare naïve, ordinary least squares, and GARCH conditional variance and correlations models to test if GARCH models lead to higher variance reduction in a context of high time varying volatility as the case of electricity markets. Our results show that the choice of the hedge ratio estimation model is central on determining the effectiveness of futures hedging to reduce the portfolio volatility. |
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