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Cited by 316

The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.

BEHAVIORAL PORTFOLIO SELECTION IN CONTINUOUS TIME

Open access
Jin, Hanqing, Yu Zhou, Xun·2008·Mathematical Finance

Abstract

This paper formulates and studies a general continuous‐time behavioral portfolio selection model under Kahneman and Tversky's (cumulative) prospect theory, featuring S‐shaped utility (value) functions and probability distortions. Unlike the conventional expected utility maximization model, such a behavioral model could be easily mis‐formulated (a.k.a. ill‐posed) if its different components do not coordinate well with each other. Certain classes of an ill‐posed model are identified. A systematic approach, which is fundamentally different from the ones employed for the utility model, is developed to solve a well‐posed model, assuming a complete market and general Itô processes for asset prices. The optimal terminal wealth positions, derived in fairly explicit forms, possess surprisingly simple structure reminiscent of a gambling policy betting on a good state of the world while accepting a fixed, known loss in case of a bad one. An example with a two‐piece CRRA utility is presented to illustrate the general results obtained, and is solved completely for all admissible parameters. The effect of the behavioral criterion on the risky allocations is finally discussed.

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Crossref · 10.1111/j.1467-9965.2008.00339.x

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Metadata

Authors
Jin, H., & Yu Zhou, X.
Venue
Mathematical Finance
Publisher
Wiley
Published
2008-06-28
Volume
18
Issue
3
Pages
385-426
ISSN
  • 0960-1627 (ISSN-L)
  • 1467-9965
OpenAlex
W2134306794
Cited by
316
References
23
FWCI
23.33
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: BEHAVIORAL PORTFOLIO SELECTION IN CONTINUOUS TIME. https://app.cochat.ai/papers/10.1111/j.1467-9965.2008.00339.x
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Jin, H., & Yu Zhou, X. (2008). BEHAVIORAL PORTFOLIO SELECTION IN CONTINUOUS TIME. Mathematical Finance. https://doi.org/10.1111/j.1467-9965.2008.00339.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.