Quantile Maximization in Decision Theory

@inproceedings{Rostek2007QuantileMI,
  title={Quantile Maximization in Decision Theory},
  author={Marzena Rostek},
  year={2007}
}
This paper introduces a model of preferences, in which, given beliefs about uncertain outcomes, an individual evaluates an action by a quantile of the induced distribution. The choice rule of Quantile Maximization unifies maxmin and maxmax as maximizing the lowest and the highest quantiles of beliefs distributions, respectively, and offers a family of less extreme preferences. Taking preferences over acts as a primitive, we axiomatize Quantile Maximization in a Savage setting. Our… CONTINUE READING
Highly Cited
This paper has 32 citations. REVIEW CITATIONS
22 Citations
33 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 33 references

Subjective Probability Without Monotonicity : Or How Machina ’ s Mom May Also Be Probabilistically Sophisticated ”

  • S. GRANT
  • Econometrica
  • 1995
Highly Influential
5 Excerpts

A More Robust Definition of Subjective Probability ”

  • M. MACHINA, D. SCHMEIDLER
  • Econometrica
  • 1992
Highly Influential
5 Excerpts

Maxmin Expected Utility with Non-unique Prior

  • D. SCHMEIDLER
  • Journal of Mathematical Economics
  • 1989
Highly Influential
3 Excerpts

Representation of a Preference Ordering by a Numerical Function ”

  • G. DEBREU
  • 1954
Highly Influential
3 Excerpts

Contracts for Experts with Opposing Interests ” ( Working Paper )

  • T. MYLOVANOV, A. ZAPECHELNYUK
  • 2007
1 Excerpt

Robustness (Princeton, NJ: Princeton University Press). HURWICZ, L

  • L. P. HANSEN, T. J. SARGENT
  • Probabilistically Sophisticated”, Econometrica,
  • 2007
2 Excerpts

Similar Papers

Loading similar papers…