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Hedging against bunker price fluctuations using petroleum futures contracts: constant versus time-varying hedge ratios

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  • Amir Alizadeh
  • Manolis Kavussanos
  • David Menachof

Abstract

The effectiveness of hedging marine bunker price fluctuations in Rotterdam, Singapore and Houston is examined using different crude oil and petroleum future contracts traded at the New York Mercantile Exchange (NYMEX) and the International Petroleum Exchange (IPE) in London. Using both constant and dynamic hedge ratios, it is found that in and out-of-sample hedging effectiveness is different across regional bunker markets. The most effective futures instruments for out of sample hedging of spot bunker prices in Rotterdam and Singapore are the IPE crude oil futures, while for Houston it is the gas oil futures. Differences in hedging effectiveness across regional markets are attributed to the varying regional supply and demand factors in each market. In comparison to other markets, the cross-market hedging effectiveness investigated in the bunker market is low.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 36 (2004)
Issue (Month): 12 ()
Pages: 1337-1353

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Handle: RePEc:taf:applec:v:36:y:2004:i:12:p:1337-1353

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  1. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038 Elsevier.
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  4. Anil K. Bera & Philip Garcia & Jae-Sun Roh, 1997. "Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches," Finance 9712007, EconWPA.
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  8. Kavussanos, Manolis G. & Visvikis, Ilias D., 2004. "Market interactions in returns and volatilities between spot and forward shipping freight markets," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 2015-2049, August.
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Cited by:
  1. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
  2. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," KIER Working Papers 743, Kyoto University, Institute of Economic Research.

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