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Cited by 2,297

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An Introduction to Econophysics: Correlations and Complexity in Finance

Open access
Mantegna, Rosario N., Stanley, H. Eugene, Chriss, Neil A.·2000·Physics Today

Abstract

This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.

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Crossref · 10.1063/1.1341926

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Metadata

Authors
Mantegna, R. N., Stanley, H. E., & Chriss, N. A.
Venue
Physics Today
Published
2000-12-01
Volume
53
Issue
12
Pages
70-70
ISSN
  • 0031-9228 (ISSN-L)
  • 1945-0699
OpenAlex
W2136913207
Cited by
2,297
References
2
FWCI
198.63
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: An Introduction to Econophysics: Correlations and Complexity in Finance. https://app.cochat.ai/papers/10.1063/1.1341926
The paper
Mantegna, R. N., Stanley, H. E., & Chriss, N. A. (2000). An Introduction to Econophysics: Correlations and Complexity in Finance. Physics Today. https://doi.org/10.1063/1.1341926

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.