Statistical mechanics of nonlinear nonequilibrium financial markets: Applications to optimized trading

A paradigm of statistical mechanics of financial markets (SMFM) using nonlinear non-equilibrium algorithms, first published in [1], is fit to multivariate financial markets using Adaptive Simulated Annealing (ASA), a global optimization algorithm, to perform maximum likelihood fits of Lagrangians de...

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Bibliographic Details
Published in:Mathematical and computer modelling 1996-04, Vol.23 (7), p.101-121
Main Author: Ingber, L.
Format: Article
Language:English
Subjects:
Applications
Biology, psychology, social sciences
Economics
Exact sciences and technology
Finance
Insurance, economics, finance
Mathematics
Medical sciences
Probability and statistics
Probability theory and stochastic processes
Reliability, life testing, quality control
Sciences and techniques of general use
Simulated annealing
Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications)
Statistical mechanics
Statistics
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Summary:A paradigm of statistical mechanics of financial markets (SMFM) using nonlinear non-equilibrium algorithms, first published in [1], is fit to multivariate financial markets using Adaptive Simulated Annealing (ASA), a global optimization algorithm, to perform maximum likelihood fits of Lagrangians defined by path integrals of multivariate conditional probabilities. Canonical momenta are thereby derived and used as technical indicators in a recursive ASA optimization process to tune trading rules. These trading rules are then used on out-of-sample data, to demonstrate that they can profit from the SMFM model, to illustrate that these markets are likely not efficient.
ISSN:0895-7177
1872-9479
DOI:10.1016/0895-7177(96)00032-5