FINANCIAL MARKET MODELING WITH QUANTUM NEURAL NETWORKS

C. Gonçalves P.
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C. Gonçalves P.: University of Lisbon

Review of Business and Economics Studies // Review of Business and Economics Studies, 2015, vol. 3, issue 4, 44-63

Abstract:

Econophysics has developed as a research field that applies the formalism of statistical mechanics and quantum mechanics to address economics and finance problems. The branch of econophysics that applies quantum theory to economics and finance is called quantum econophysics. In finance, quantum econophysics’ contributions have ranged from option pricing to market dynamics modeling, behavioral finance and applications of game theory, integrating the empirical finding, from human decision analysis, that showsthat nonlinear update rules in probabilities, leading to non-additive decision weights, can be computationally approached from quantum computation, with resulting quantum interference terms explaining the non-additiveprobabilities. The current work draws on these results to introduce new tools from quantum artificial intelligence,namely quantum artificial neural networks as a way to build and simulate financial market models with adaptiveselection of trading rules, leading to turbulence and excess kurtosis in the returns distributions for a wide range of parameters.

Эконофизика сформировалась как исследовательская область, которая применяет понятия статистической механики и квантовой механики для исследования экономических и финансовых проблем. Раздел эконофизики, который применяет квантовую теорию к экономике и финансам, именуется квантовой эконофизикой. В финансовой сфере квантовая эконофизика используется в ряде областей - от оценки опционов до моделирования рыночной динамики. В данной работе вводятся новые инструменты из области квантового искусственного интеллекта, а именно квантовые искусственные нейронные сети в качестве способа создания адаптивных моделей финансовых рынков.

Keywords: Finance; econophysics; quantum artificial neural networks; quantum stochastic processes; cognitive science (search for similar items in EconPapers)
Date: 2019-02-25
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