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A Generalized Probability Framework to Model Economic Agents’ Decisions under Uncertainty

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journal contribution
posted on 2016-03-07, 10:51 authored by Emmanuel E. Haven, S. Sozzo
The applications of techniques from statistical (and classical) mechanics to model interesting problems in economics and finance have produced valuable results. The principal movement which has steered this research direction is known under the name of ‘econophysics’. In this paper, we illustrate and advance some of the findings that have been obtained by applying the mathematical formalism of quantum mechanics to model human decision making under ‘uncertainty’ in behavioral economics and finance. Starting from Ellsberg's seminal article, decision making situations have been experimentally verified where the application of Kolmogorovian probability in the formulation of expected utility is problematic. Those probability measures which by necessity must situate themselves in Hilbert space (such as ‘quantum probability’) enable a faithful representation of experimental data. We thus provide an explanation for the effectiveness of the mathematical framework of quantum mechanics in the modeling of human decision making. We want to be explicit though that we are not claiming that decision making has microscopic quantum mechanical features.

History

Citation

International Review of Financial Analysis, 47, pp. 297–303

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Management

Version

  • AM (Accepted Manuscript)

Published in

International Review of Financial Analysis

Publisher

Elsevier

issn

1057-5219

Acceptance date

2015-12-11

Copyright date

2015

Available date

2017-06-23

Publisher version

http://www.sciencedirect.com/science/article/pii/S1057521915002124

Notes

The file associated with this record is under a 36-month embargo from publication in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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