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Dynamic Decision Making in Agricultural Futures and Options Markets

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  • Mattos, Fabio
  • Garcia, Philip
  • Pennings, Joost M.E.

Abstract

This paper investigates the dynamics of sequential decision-making in agricultural futures and options markets. Analysis of trading records of 12 traders identified considerable heterogeneity in individual dynamic trading behavior. Using risk measures derived from the deltas and vegas of trader’s portfolios, we find nearly half the traders behavior is consistent with a house-money effect and the other half with loss aversion. These findings correspond closely to expected behavior inferred from elicited utility and probability weighting functions. The results call into question more aggregate findings that discount probability weighting to develop risk measures which support the notion of more uniform, less heterogeneous, behavior. Understanding behavior in a prospect theory context appears to call for investigation of both the probability weighting and utility functions. Our findings also suggest that strategies for loss-averse traders who consolidate gains and avoid using gains in risk-seeking market activities are effective.

Suggested Citation

  • Mattos, Fabio & Garcia, Philip & Pennings, Joost M.E., 2008. "Dynamic Decision Making in Agricultural Futures and Options Markets," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37605, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  • Handle: RePEc:ags:nccest:37605
    DOI: 10.22004/ag.econ.37605
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    File URL: http://ageconsearch.umn.edu/record/37605/files/confp09-08.pdf
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    References listed on IDEAS

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    1. Lucy Ackert & Narat Charupat & Bryan Church & Richard Deaves, 2006. "An experimental examination of the house money effect in a multi-period setting," Experimental Economics, Springer;Economic Science Association, vol. 9(1), pages 5-16, April.
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    5. Joshua D. Coval & Tyler Shumway, 2005. "Do Behavioral Biases Affect Prices?," Journal of Finance, American Finance Association, vol. 60(1), pages 1-34, February.
    6. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    7. Keasey, Kevin & Moon, Philip, 1996. "Gambling with the house money in capital expenditure decisions: An experimental analysis," Economics Letters, Elsevier, vol. 50(1), pages 105-110, January.
    8. Massimo Massa & Andrei Simonov, 2005. "Behavioral Biases and Investment," Review of Finance, Springer, vol. 9(4), pages 483-507, December.
    9. Mattos, Fabio & Garcia, Philip & Pennings, Joost M.E., 2007. "Insights into Trader Behavior: Risk Aversion and Probability Weighting," 2007 Conference, April 16-17, 2007, Chicago, Illinois 37569, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
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    11. Nicholas Barberis & Ming Huang & Tano Santos, 2001. "Prospect Theory and Asset Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 116(1), pages 1-53.
    12. Langer, Thomas & Weber, Martin, 2005. "Myopic prospect theory vs. myopic loss aversion: how general is the phenomenon?," Journal of Economic Behavior & Organization, Elsevier, vol. 56(1), pages 25-38, January.
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    Cited by:

    1. Xiang Li & Yongjian Li, 2016. "On lot-sizing problem in a random yield production system under loss aversion," Annals of Operations Research, Springer, vol. 240(2), pages 415-434, May.

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    Keywords

    Agricultural Finance;

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