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Insights into Trader Behavior: Risk Aversion and Probability Weighting

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Author Info

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

Abstract

The objective of this study is to investigate how professional traders in futures and options markets behave under risk and uncertainty. Our preliminary findings suggest that most traders exhibit concave utility functions for gains and convex utility functions for losses, while their weighting functions are inverse s-shaped. However, differences in magnitude of the risk aversion parameters and the degree of probability weighting can lead to distinct behavior even if the shapes of utility and weighting functions are the same. Further, the typical pattern of prospect theory is more prevalent under risk but not as much under uncertainty. More combinations of shapes for utility and weighting functions are found under uncertainty, suggesting that different types of behavior emerge when people need to make their own assessments about the likelihood of events. Finally, our results are consistent with evidence of loss aversion and disposition effect found in studies of trading behavior in futures markets.

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File URL: http://purl.umn.edu/37569
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Bibliographic Info

Paper provided by NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management in its series 2007 Conference, April 16-17, 2007, Chicago, Illinois with number 37569.

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Date of creation: Apr 2007
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Handle: RePEc:ags:nccsci:37569

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Related research

Keywords: trader behavior; risk aversion; probability weighting;

References

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  1. Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
  2. Nathalie Etchart-Vincent, 2004. "Is Probability Weighting Sensitive to the Magnitude of Consequences? An Experimental Investigation on Losses," Journal of Risk and Uncertainty, Springer, vol. 28(3), pages 217-235, 05.
  3. Abdellaoui, Mohammed & Vossman, Frank & Weber, Martin, 2003. "Choice-Based Elicitation and Decomposition of Decision Weights for Gains and Losses Under Uncertainty," CEPR Discussion Papers 3756, C.E.P.R. Discussion Papers.
  4. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
  5. Donkers, Bas & Melenberg, Bertrand & Van Soest, Arthur, 2001. " Estimating Risk Attitudes Using Lotteries: A Large Sample Approach," Journal of Risk and Uncertainty, Springer, vol. 22(2), pages 165-95, March.
  6. Joshua D. Coval & Tyler Shumway, 2005. "Do Behavioral Biases Affect Prices?," Journal of Finance, American Finance Association, vol. 60(1), pages 1-34, 02.
  7. Benartzi, Shlomo & Thaler, Richard H, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, MIT Press, vol. 110(1), pages 73-92, February.
  8. Locke, Peter R. & Mann, Steven C., 2005. "Professional trader discipline and trade disposition," Journal of Financial Economics, Elsevier, vol. 76(2), pages 401-444, May.
  9. Berkelaar, A.B. & Kouwenberg, R.R.P., 2000. "Optimal portfolio choice under loss aversion," Econometric Institute Research Papers EI 2000-08/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  10. Michael Kilka & Martin Weber, 2001. "What Determines the Shape of the Probability Weighting Function Under Uncertainty?," Management Science, INFORMS, vol. 47(12), pages 1712-1726, December.
  11. Carmela Di Mauro & Anna Maffioletti, 2004. "Attitudes to risk and attitudes to uncertainty: experimental evidence," Applied Economics, Taylor & Francis Journals, vol. 36(4), pages 357-372.
  12. Schoemaker, Paul J H, 1982. "The Expected Utility Model: Its Variants, Purposes, Evidence and Limitations," Journal of Economic Literature, American Economic Association, vol. 20(2), pages 529-63, June.
  13. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March.
  14. Haigh, Michael S. & List, John A., 2002. "Do Professional Traders Exhibit Myopic Loss Aversion? An Experimental Analysis," Working Papers 28554, University of Maryland, Department of Agricultural and Resource Economics.
  15. John List & David Reiley, 2008. "Field experiments," Artefactual Field Experiments 00091, The Field Experiments Website.
  16. John C. Hershey & Howard C. Kunreuther & Paul J. H. Schoemaker, 1982. "Sources of Bias in Assessment Procedures for Utility Functions," Management Science, INFORMS, vol. 28(8), pages 936-954, August.
  17. Fox, Craig R & Rogers, Brett A & Tversky, Amos, 1996. "Options Traders Exhibit Subadditive Decision Weights," Journal of Risk and Uncertainty, Springer, vol. 13(1), pages 5-17, July.
  18. 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.
  19. Tversky, Amos & Kahneman, Daniel, 1992. " Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
  20. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, 08.
  21. Mohammed Abdellaoui, 2000. "Parameter-Free Elicitation of Utility and Probability Weighting Functions," Management Science, INFORMS, vol. 46(11), pages 1497-1512, November.
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Cited by:
  1. Kalayci, Erkan & Basdas, Ulkem, 2010. "Does the prospect theory also hold for power traders? Empirical evidence from a Swiss energy company," Review of Financial Economics, Elsevier, vol. 19(1), pages 38-45, January.
  2. 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.

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