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Application of quantum master equation for long-term prognosis of asset-prices

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journal contribution
posted on 2016-03-16, 14:25 authored by Polina Khrennikova
This study combines the disciplines of behavioral finance and an extension of econophysics, namely the concepts and mathematical structure of quantum physics. We apply the formalism of quantum theory to model the dynamics of some correlated financial assets, where the proposed model can be potentially applied for developing a long-term prognosis of asset price formation. At the informational level, the asset price states interact with each other by the means of a “financial bath”. The latter is composed of agents’ expectations about the future developments of asset prices on the finance market, as well as financially important information from mass-media, society, and politicians. One of the essential behavioral factors leading to the quantum-like dynamics of asset prices is the irrationality of agents’ expectations operating on the finance market. These expectations lead to a deeper type of uncertainty concerning the future price dynamics of the assets, than given by a classical probability theory, e.g., in the framework of the classical financial mathematics, which is based on the theory of stochastic processes. The quantum dimension of the uncertainty in price dynamics is expressed in the form of the price-states superposition and entanglement between the prices of the different financial assets. In our model, the resolution of this deep quantum uncertainty is mathematically captured with the aid of the quantum master equation (its quantum Markov approximation). We illustrate our model of preparation of a future asset price prognosis by a numerical simulation, involving two correlated assets. Their returns interact more intensively, than understood by a classical statistical correlation. The model predictions can be extended to more complex models to obtain price configuration for multiple assets and portfolios.

History

Citation

Physica A: Statistical Mechanics and its Applications, 450, 2016, pp. 253–263

Version

  • AM (Accepted Manuscript)

Published in

Physica A: Statistical Mechanics and its Applications

Publisher

Elsevier for North-Holland

issn

0378-4371

Acceptance date

2015-11-20

Copyright date

2016

Available date

2017-01-12

Publisher version

http://www.sciencedirect.com/science/article/pii/S0378437116000091

Language

en

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