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|Title:||A Generalized Probability Framework to Model Economic Agents' Decisions Under Uncertainty|
|Citation:||International Review of Financial Analysis, 47, pp. 297–303|
|Abstract:||The applications of techniques from statistical (and classical) mechanics to model interesting problems in economics and finance has 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.|
|Embargo on file until:||23-Jun-2017|
|Rights:||Copyright © 2015 Elsevier Inc. All rights reserved. This manuscript version is made available after the end of the embargo period under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Description:||Jel classification D81|
The file associated with this record is under embargo until 18 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
|Appears in Collections:||Published Articles, School of Management|
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|RevisedSubmittedIRFA2015SozzoHaven.pdf||Post-review (final submitted)||156.47 kB||Adobe PDF||View/Open|
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