Asymptotic Theory Of Stochastic Choice Functionals For Prospects With Embedded Comotonic Probability Measures
AbstractWe introduce a monotone class theory of Prospect Theory's value functions, which shows that they can be replaced almost surely by a topological lifting comprised of a class of compact isomorphic maps that embed weakly co-monotonic probability measures, attached to state space, in outcome space. Thus, agents solve a signal extraction problem to obtain estimates of empirical probability weights for prospects under risk and uncertainty. By virtue of the topological lifting, we prove an almost sure isomorphism theorem between compact stochastic choice operators, and well defined outcomes which, under Brouwer-Schauder theory, guarantees fixed point convergence in convex choice sets. Along the way we introduce a risk operator in the Hoffman-Jorgensen class of lifting operators, and value function [averaging] operators with respect to Radon measure. In that set up, suitable binary operations on gain-loss space show that our risk operator is isometric for gains and skewed for losses. The point spectrum from this operator constitutes the range of admissible observations for loss aversion index in a well designed experiment.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 22380.
Date of creation: 27 Apr 2010
Date of revision:
monotone class theorem; stochastic choice functional; embedded probability; comonotonic probability; isomorphism;
Find related papers by JEL classification:
- D03 - Microeconomics - - General - - - Behavioral Microeconomics; Underlying Principles
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
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