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Abstract: A paradigm of statistical mechanics of financial markets (SMFM) 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... (Update)
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.... and the faster quasi local codes seem to work quite well for adaptive updates after a zeroth order parameters set is found by ASA [29,30]. 3. STATISTICAL MECHANICS OF FINANCIAL MARKETS (SMFM) 3.1. Statistical Mechanics of Large Systems Aggregation problems in nonlinear...
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BibTeX entry: (Update)
L. Ingber, "Canonical momenta indicators of financial markets and neocortical EEG," in Progress in Neural Information Processing, , ed. by S.-I. Amari, L. Xu, I. King, and K.-S. Leung, Springer, New York, 1996, pp. 777-784. http://citeseer.ist.psu.edu/ingber96canonical.html More
@misc{ ingber96canonical,
author = "L. Ingber",
title = "Canonical momenta indicators of financial markets and neocortical EEG",
text = "L. Ingber, Canonical momenta indicators of financial markets and neocortical
EEG, in Progress in Neural Information Processing, , ed. by S.-I. Amari,
L. Xu, I. King, and K.-S. Leung, Springer, New York, 1996, pp. 777-784.",
year = "1996",
url = "citeseer.ist.psu.edu/ingber96canonical.html" }
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