Skip to main content
Introduction to Econophysics
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 371
  • Cited by
    This (lowercase (translateProductType product.productType)) has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Kanazawa, Kiyoshi Sueshige, Takumi Takayasu, Hideki and Takayasu, Misako 2018. Derivation of the Boltzmann Equation for Financial Brownian Motion: Direct Observation of the Collective Motion of High-Frequency Traders. Physical Review Letters, Vol. 120, Issue. 13,

    Gupta, Kartikay and Chatterjee, Niladri 2018. Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2. Vol. 84, Issue. , p. 146.

    Buscema, Paolo Massimo Sacco, Pier Luigi Della Torre, Francesca Massini, Giulia Breda, Marco and Ferilli, Guido 2018. Theory of impossible worlds: Toward a physics of information. Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 28, Issue. 5, p. 055914.

    Mo, Haiyan and Wang, Jun 2018. Return scaling cross-correlation forecasting by stochastic time strength neural network in financial market dynamics . Soft Computing, Vol. 22, Issue. 9, p. 3097.

    Papenbrock, Jochen 2018. Praxishandbuch Digital Banking. p. 325.

    Posch, Peter N. Ullmann, Daniel and Wied, Dominik 2018. Detecting structural changes in large portfolios. Empirical Economics,

    Allegra, Nicolas Bamieh, Bassam Mitra, Partha and Sire, Clément 2018. Phase transitions in distributed control systems with multiplicative noise. Journal of Statistical Mechanics: Theory and Experiment, Vol. 2018, Issue. 1, p. 013405.

    Koehler, Matthew Michel, Shaun Slater, David Harvey, Christine Andrei, Amanda and Comer, Kevin 2018. Agent-based Modeling of Tax Evasion. p. 225.

    Saeedian, M and Zahabi, A 2018. Phase structure of XX0 spin chain and nonintersecting Brownian motion. Journal of Statistical Mechanics: Theory and Experiment, Vol. 2018, Issue. 1, p. 013104.

    Schinckus, Christophe and Akdere, Cinla 2018. Duality of knowledge, singularity of method. Journal of Asian Business and Economic Studies, Vol. 25, Issue. 1, p. 163.

    Donmez, Cem Cagri 2018. Fractal Approaches for Modeling Financial Assets and Predicting Crises. p. 1.

    Ribeiro, Haroldo V. Hanley, Quentin S. Lewis, Dan and Gomez-Lievano, Andres 2018. Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools. PLOS ONE, Vol. 13, Issue. 2, p. e0192931.

    Nie, Sen Stanley, H. Eugene Chen, Shi-Ming Wang, Bing-Hong and Wang, Xu-Wen 2018. Control energy of complex networks towards distinct mixture states. Scientific Reports, Vol. 8, Issue. 1,

    Franzke, Christian L. E. 2017. Extremes in dynamic-stochastic systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 27, Issue. 1, p. 012101.

    Sharma, Kiran Shah, Shreyansh Chakrabarti, Anindya S. and Chakraborti, Anirban 2017. Economic Foundations for Social Complexity Science. Vol. 9, Issue. , p. 211.

    Roehner, Bertrand M. 2017. Encyclopedia of Complexity and Systems Science. p. 1.

    Poli, Roberto 2017. Introduction to Anticipation Studies. Vol. 1, Issue. , p. 23.

    Yamashita Rios de Sousa, Arthur Matsuo Takayasu, Hideki Takayasu, Misako and Zhou, Wei-Xing 2017. Detection of statistical asymmetries in non-stationary sign time series: Analysis of foreign exchange data. PLOS ONE, Vol. 12, Issue. 5, p. e0177652.

    Lanchier, Nicolas 2017. Rigorous Proof of the Boltzmann–Gibbs Distribution of Money on Connected Graphs. Journal of Statistical Physics, Vol. 167, Issue. 1, p. 160.

    Li, Zhaoyuan and Tian, Maozai 2017. A New Method For Dynamic Stock Clustering Based On Spectral Analysis. Computational Economics, Vol. 50, Issue. 3, p. 373.

  • Export citation
  • Recommend to librarian
  • Recommend this book

    Email your librarian or administrator to recommend adding this book to your organisation's collection.

    Introduction to Econophysics
    • Online ISBN: 9780511755767
    • Book DOI:
    Please enter your name
    Please enter a valid email address
    Who would you like to send this to *
  • Buy the print book

Book description

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.


‘… they have been remarkably successful in presenting a clear and concise introductory summary of a large body of work on the statistical properties of stock prices.’

Burton Malkiel Source: Journal of Economic Literature

‘Clearly and concisely written, this book provides an excellent introduction to the problem of understanding the empirical statistical properties of prices.’

Doyne Farmer - Prediction Company, Santa Fe and the Santa Fe Institute

‘I feel the book is a useful introduction to the empirical aspects of econophysics.’

Blake LeBaron Source: Nature

‘The authors are leading researchers in the field, and were well-regarded statistical physicists before that … the book seems aimed the other way, at physicists interested in economics, and for them it would make a good introduction to finance. The writing is clear and friendly, the production values high and the guides to further reading excellent. They will find it well worth their time and money.’

Cosma Shalizi - Institute of Physics

Refine List
Actions for selected content:
Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Send to Kindle
  • Send to Dropbox
  • Send to Google Drive
  • Send content to

    To send content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to .

    To send content items to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

    Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

    Find out more about the Kindle Personal Document Service.

    Please be advised that item(s) you selected are not available.
    You are about to send

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.


Full text views

Total number of HTML views: 0
Total number of PDF views: 2098 *
Loading metrics...

Book summary page views

Total views: 1231 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 17th August 2018. This data will be updated every 24 hours.