Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/201604 
Year of Publication: 
2018
Series/Report no.: 
Center for Mathematical Economics Working Papers No. 580
Publisher: 
Bielefeld University, Center for Mathematical Economics (IMW), Bielefeld
Abstract: 
We consider a robust version of the full information best choice problem (Gilbert and Mosteller (1966)): there is ambiguity (represented by a set of priors) about the measure driving the observed process. We solve the problem under a very general class of multiple priors in the setting of Riedel (2009). As in the classical case, it is optimal to stop if the current observation is a running maximum that exceeds certain thresholds. We characterize the decreasing sequence of thresholds, as well as the (history dependent) minimizing measure. We introduce locally constant ambiguity neighborhood (LCAn) which has connections to coherent risk measures. Sensitivity analysis is performed using LCAn and exponential neighborhood from Riedel (2009).
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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