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Premiums/Discounts and Predictive Ability of the Shrimp Futures Market

Published online by Cambridge University Press:  15 September 2016

Josué Martínez-Garmendia
Affiliation:
Department of Environmental and Natural Resource Economics at the University of Rhode Island
James L. Anderson
Affiliation:
Department of Environmental and Natural Resource Economics at the University of Rhode Island
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Abstract

Seafood futures contracts are a novelty in the derivative markets, having shrimp as their only exponent. Unfortunately, shrimp futures contracts have suffered a disappointing start. The analyses focus on testing whether premiums/discounts for non-par deliverable shrimp size categories can eliminate cash price differentials, and whether the shrimp futures market can predict cash prices without bias. Results indicate ineffective premiums/discounts and predictive bias. These results and the momentous changes taking place in the seafood industry are contrasted to discuss the viability of seafood futures contracts.

Type
Articles
Copyright
Copyright © 2001 Northeastern Agricultural and Resource Economics Association 

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References

Antoniou, A. and Foster, A.J. 1994. “Short-Term And Long-Term Efficiency In Commodity Spot And Futures Markets.” Financial Markets, Institutions and Instruments 3: 1735.Google Scholar
Crowder, W.J. and Hamed, A. 1993. “A Cointegration Test For Oil Futures Market Efficiency.” The Journal of Futures Markets 13: 933941.CrossRefGoogle Scholar
Hall, S.G. 1991. “The Effect of Varying Length VAR Models on the Maximum Likelihood Estimates of Cointegrating Vectors.” Scottish Journal of Political Economy 38: 317323.CrossRefGoogle Scholar
Harris, F.H.D., McInish, T.H., Shoesmith, G.L. and Wood, R.A. 1995. “Cointegration, Error Correction, And Price Discovery On Informationally Linked Security.” Journal of Financial and Quantitative Analysis 30: 563579.CrossRefGoogle Scholar
Johansen, S. 1988. “Statistical Analysis of Cointegration Vectors.” Journal of Economic Dynamics and Control 12: 231254.CrossRefGoogle Scholar
Lai, K.S. and Lai, M. 1991. “A Cointegration Test For Market Efficiency.” The Journal of Futures Markets 11: 567575.CrossRefGoogle Scholar
Martinez-Garmendia, J. and Anderson, J.L. 1999. “Hedging Performance of Shrimp Futures Contracts with Multiple-Deliverable Grades.” The Journal of Futures Markets 19: 957990.3.0.CO;2-Z>CrossRefGoogle Scholar
MGE. 1993. The Power of Shrimp Futures and Alternatives. Minneapolis.Google Scholar
MGE. 1997a. Shrimp Futures and Alternatives Tutorial. Minneapolis.Google Scholar
MGE. 1997b. News Release. Minneapolis.Google Scholar
Pesaran, M.H., Shin, Y., and Smith, R.J. 1996. “Structural Analysis of Vector Error Correction Models with Exogenous I(1) Variables.DAE Working Paper No. 9706, Dept. of Applied Economics, University of Cambridge.Google Scholar
Pizzi, M.A., Economopoulos, A.J. and O'Neill., H.M. 1998. “An Examination of the Relationship Between Stock Index Cash and Futures Markets: A Cointegration Approach.” The Journal of Futures Markets 18: 297305.3.0.CO;2-3>CrossRefGoogle Scholar
Rao, B.B. 1994. Cointegration for the Applied Economist. St. Martin's Press, New York.Google Scholar
Urner-Barry Publications, Inc. 1993-1998. Seafood Price-Current. Toms River, New Jersey.Google Scholar