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• W3125965162 startingPage "979" @default.
• W3125965162 abstract "An unconventional approach for optimal stopping under model ambiguity is introduced. Besides ambiguity itself, we take into account how ambiguity-averse an agent is. This inclusion of ambiguity attitude, via an $alpha$-maxmin nonlinear expectation, renders the stopping problem time-inconsistent. We look for subgame perfect equilibrium stopping policies, formulated as fixed points of an operator. For a one-dimensional diffusion with drift and volatility uncertainty, we show that every equilibrium can be obtained through a fixed-point iteration. This allows us to capture much more diverse behavior, depending on an agent's ambiguity attitude, beyond the standard worst-case (or best-case) analysis. In a concrete example of real options valuation under volatility uncertainty, all equilibrium stopping policies, as well as the best one among them, are fully characterized. It demonstrates explicitly the effect of ambiguity attitude on decision making: the more ambiguity-averse, the more eager to stop -- so as to withdraw from the uncertain environment. The main result hinges on a delicate analysis of continuous sample paths in the canonical space and the capacity theory. To resolve measurability issues, a generalized measurable projection theorem, new to the literature, is also established." @default.
• W3125965162 created "2021-02-01" @default.
• W3125965162 creator A5039144550 @default.
• W3125965162 creator A5076011582 @default.
• W3125965162 date "2021-04-19" @default.
• W3125965162 modified "2023-09-25" @default.
• W3125965162 title "Optimal stopping under model ambiguity: A time‐consistent equilibrium approach" @default.
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• W3125965162 doi "https://doi.org/10.1111/mafi.12312" @default.
• W3125965162 hasPublicationYear "2021" @default.
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