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Behavioral Capital Theory via Canonical Quantization

dc.contributor.authorHawkins, R.J.
dc.contributor.authorD’Anna, J.L.
dc.date.accessioned2022-12-15T22:41:22Z
dc.date.available2022-12-15T22:41:22Z
dc.date.issued2022
dc.identifier.citationHawkins, R. J., & D’Anna, J. L. (2022). Behavioral Capital Theory via Canonical Quantization. Entropy, 24(10), 1497.
dc.identifier.issn1099-4300
dc.identifier.doi10.3390/e24101497
dc.identifier.urihttp://hdl.handle.net/10150/667215
dc.description.abstractWe show how a behavioral form of capital theory can be derived using canonical quantization. In particular, we introduce quantum cognition into capital theory by applying Dirac’s canonical quantization approach to Weitzman’s Hamiltonian formulation of capital theory, the justification for the use of quantum cognition being the incompatibility of questions encountered in the investment decision-making process. We illustrate the utility of this approach by deriving the capital-investment commutator for a canonical dynamic investment problem. © 2022 by the authors.
dc.language.isoen
dc.publisherMDPI
dc.rightsCopyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectbehavioral economics
dc.subjectcapital theory
dc.subjectquantum cognition
dc.titleBehavioral Capital Theory via Canonical Quantization
dc.typeArticle
dc.typetext
dc.contributor.departmentWyant College of Optical Sciences, University of Arizona
dc.identifier.journalEntropy
dc.description.noteOpen access journal
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
dc.eprint.versionFinal published version
dc.source.journaltitleEntropy
refterms.dateFOA2022-12-15T22:41:22Z


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Copyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as Copyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).