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Data-driven nonlinear expectations for statistical uncertainty in decisions

Abstract:
In stochastic decision problems, one often wants to estimate the underlying probability measure statistically, and then to use this estimate as a basis for decisions. We shall consider how the uncertainty in this estimation can be explicitly and consistently incorporated in the valuation of decisions, using the theory of nonlinear expectations.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1214/17-EJS1278

Authors

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Institution:
University of Oxford
Oxford college:
Wadham College
Role:
Author


Publisher:
Institute of Mathematical Statistics
Journal:
Electronic Journal of Statistics More from this journal
Volume:
11
Issue:
1
Pages:
1858-1889
Publication date:
2017-04-28
Acceptance date:
2017-04-18
DOI:
ISSN:
1935-7524


Keywords:
Pubs id:
pubs:690103
UUID:
uuid:6a01a5ba-1882-4a49-b0d1-f870c2b4a2e4
Local pid:
pubs:690103
Source identifiers:
690103
Deposit date:
2017-04-19
ARK identifier:

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