TY  - GEN
AB  - We consider long-run behavior of agents assessing risk in terms of dynamic convex risk measures or, equivalently, utility in terms of dynamic variational preferences in an uncertain setting. By virtue of a robust representation, we show that all uncertainty is revealed in the limit and agents behave as expected utility maximizer under the true underlying distribution regardless of their initial risk anticipation. In particular, risk assessments of distinct agents converge. This result is a generalization of the fundamental Blackwell-Dubins Theorem, cp. [Blackwell & Dubins, 62], to convex risk. We furthermore show the result to hold in a non-time-consistent environment.
DA  - 2010
KW  - Time consistency
KW  - Blackwell-Dubins
KW  - Multiple priors
KW  - Dynamic convex risk measures
KW  - Robust representation
KW  - Uncertainty
LA  - eng
PY  - 2010
SN  - 0931-6558
TI  - Merging of opinions under uncertainty
UR  - https://nbn-resolving.org/urn:nbn:de:0070-bipr-47902
Y2  - 2024-11-22T05:16:53
ER  -