Merging of opinions under uncertainty

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Papers ; No. 433

Classification and Topics

• Classification: Wirtschaft ; Optimization Techniques; Programming Models; Dynamic Analysis ; Miscellaneous Mathematical Tools ; Criteria for Decision-Making under Risk and Uncertainty
• Subject: Dynamic Convex Risk Measures ; Multiple Priors ; Uncertainty ; Robust Representation ; Time-Consistency ; Blackwell-Dubins ; Risikopräferenz ; Erwartungstheorie ; Entscheidung bei Unsicherheit ; Zeitkonsistenz ; Erwartungsnutzen ; Theorie

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bier, Monika ; Engelage, Daniel
• Event: Veröffentlichung
• (who): Bielefeld University, Institute of Mathematical Economics (IMW)
• (where): Bielefeld
• (when): 2010

Further information

• Handle: http://hdl.handle.net/10419/43756
• URN: urn:nbn:de:hbz:361-17044
• Last update: 10.03.2025, 11:44 AM CET