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A QP Framework: A Contextual Representation of Agents’ Preferences in Investment Choice

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posted on 2020-12-11, 10:15 authored by P Khrennikova, E Haven
Contextual decisions and beliefs and their impact upon market outcomes are at the core of research in behavioural finance. We describe some of the notable probabilistic fallacies that underpin investor behaviour and the consequent deviation of asset prices from the rational expectations equilibrium. In real financial markets, the complexity of financial products and the surrounding ambiguity calls for a more general formalization of agents belief formation than offered by the standard probability theory and dynamic models based on classical stochastic processes. The main advantage of quantum probability (QP) is that it can capture contextuality of beliefs through the notion of non-commuting prospect observables. QP has the potential to model myopia in asset return evaluation, as well as inter-asset valuation. Moreover, the interference term of the agents’ comparison state can provide a quantitative description of their vacillating ambiguity perception characterized by non-additive beliefs of agents. Some of the implications of non-classicality in beliefs for the composite market outcomes can also be modelled with the aid of QP. As a final step we also discuss the contributions of the growing body of psychological studies that reveal a true (quantum type) contextuality in human preference statistics showing that the classical probability theory is too restrictive to capture the very strong non-classical correlations between preference outcomes and beliefs.

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Citation

Khrennikova. P and Haven, E., A QP Framework: A Contextual Representation of Agents’ Preferences in Investment Choice in (Eds) Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung, Data Science for Financial Econometrics pp 99-113

Author affiliation

School of Business

Version

  • AM (Accepted Manuscript)

Published in

Data Science for Financial Econometrics

Volume

898

Pagination

99 - 113

Publisher

Springer International Publishing

isbn

9783030488529

Copyright date

2020

Available date

2022-11-14

Editors

Nguyen Ngoc Thach, Vladik Kreinovich, Nguyen Duc Trung

Book series

Studies in Computational Intelligence

Language

en

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