Journal article
Path-Dependent and Randomized Strategies in Barberis’ Casino Gambling Model
- Abstract:
- We consider the dynamic casino gambling model initially proposed by Barberis (2012) and study the optimal stopping strategy of a pre-committing gambler with cumulative prospect theory (CPT) preferences. We illustrate how the strategies computed in Barberis (2012) can be strictly improved by reviewing the betting history or by tossing an independent coin, and we explain that the improvement generated by using randomized strategies results from the lack of quasi-convexity of CPT preferences. Moreover, we show that any path-dependent strategy is equivalent to a randomization of path-independent strategies.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 440.4KB, Terms of use)
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- Publisher copy:
- 10.1287/opre.2016.1545
Authors
+ Oxford-Man Institute
More from this funder
- Funding agency for:
- Obloj, J
- Zhou, X
- Grant:
- FP7/2007-2013) no. 33542
+ European Research Council
More from this funder
- Funding agency for:
- Obloj, J
- Grant:
- FP7/2007-2013) no. 33542
+ St John’s College, Oxford
More from this funder
- Funding agency for:
- Obloj, J
- Grant:
- FP7/2007-2013) no. 33542
- Publisher:
- INFORMS
- Journal:
- Operations Research More from this journal
- Volume:
- 65
- Issue:
- 1
- Pages:
- 97 - 103
- Publication date:
- 2016-11-01
- Acceptance date:
- 2016-06-03
- DOI:
- EISSN:
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1526-5463
- ISSN:
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0030-364X
- Keywords:
- Pubs id:
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pubs:656543
- UUID:
-
uuid:6e50d4d5-192f-44d1-8692-95d4167790dc
- Local pid:
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pubs:656543
- Source identifiers:
-
656543
- Deposit date:
-
2016-11-02
- ARK identifier:
Terms of use
- Copyright holder:
- INFORMS
- Copyright date:
- 2016
- Notes:
- Copyright © 2016, INFORMS. This is the accepted manuscript version of the article. The final version is available online from INFORMS at: [10.1287/opre.2016.1545]
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