Cost-efficient payoffs under model ambiguity

Carole Bernard (), Gero Junike (), Thibaut Lux () and Steven Vanduffel ()
Additional contact information
Carole Bernard: Grenoble Ecole de Management (GEM)
Gero Junike: Carl von Ossietzky Universität Oldenburg
Thibaut Lux: Baloise Insurance Group

Finance and Stochastics, 2024, vol. 28, issue 4, No 2, 965-997

Abstract: Abstract Dybvig (1988a, 1988b) solves in a complete market setting the problem of finding a payoff that is cheapest possible in reaching a given target distribution (“cost-efficient payoff”). In the presence of ambiguity, the distribution of a payoff is, however, no longer known with certainty. We study the problem of finding the cheapest possible payoff whose worst-case distribution stochastically dominates a given target distribution (“robust cost-efficient payoff”) and determine solutions under certain conditions. We study the link between “robust cost-efficiency” and the maxmin expected utility setting of Gilboa and Schmeidler (1989), as well as more generally in a possibly nonexpected robust utility setting. Specifically, we show that solutions to maxmin robust expected utility are necessarily robust cost-efficient. We illustrate our study with examples involving uncertainty both on the drift and on the volatility of the risky asset.

Keywords: Cost-efficient payoffs; Model ambiguity; Maxmin utility; Robust preferences; Drift and volatility uncertainty; 91B30; 62E17 (search for similar items in EconPapers)
JEL-codes: C02 C63 D80 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00780-024-00547-z

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