Change search
ReferencesLink to record
Permanent link

Direct link
U.S. stock market interaction network as learned by the Boltzmann machine
KTH, School of Engineering Sciences (SCI), Applied Physics, Nanostructure Physics. KTH, Centres, Nordic Institute for Theoretical Physics NORDITA.
KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. The Kavli Institute for Systems Neuroscience, NTNU, Trondheim, Norway.
KTH, Centres, Nordic Institute for Theoretical Physics NORDITA. Institute for Materials Science, Los Alamos National Laboratory, Los Alamos, NM, United States.
2015 (English)In: European Physical Journal B: Condensed Matter Physics, ISSN 1434-6028, E-ISSN 1434-6036, Vol. 88, no 12, 1-14 p.Article in journal (Refereed) PublishedText
Abstract [en]

We study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as the market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model’s parameters might be used as a precursor of financial instabilities.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2015. Vol. 88, no 12, 1-14 p.
Keyword [en]
Statistical and Nonlinear Physics
National Category
Probability Theory and Statistics
URN: urn:nbn:se:kth:diva-181853DOI: 10.1140/epjb/e2015-60282-3ISI: 000371893400002ScopusID: 2-s2.0-84949229986OAI: diva2:901556

QC 20160208

Available from: 2016-02-08 Created: 2016-02-05 Last updated: 2016-04-01Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Borysov, StanislavRoudi, YasserBalatsky, Alexander V.
By organisation
Nanostructure PhysicsNordic Institute for Theoretical Physics NORDITA
In the same journal
European Physical Journal B: Condensed Matter Physics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 22 hits
ReferencesLink to record
Permanent link

Direct link