Financial Market Modeling with Quantum Neural Networks
August 26, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Carlos Pedro GonΓ§alves
arXiv ID
1508.06586
Category
q-fin.CP
Cross-listed
cs.NE,
physics.soc-ph,
q-fin.GN
Citations
8
Venue
arXiv.org
Last Checked
3 months ago
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 of 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 shows that 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-additive probabilities. 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 adaptive selection of trading rules, leading to turbulence and excess kurtosis in the returns distributions for a wide range of parameters.
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