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Introduction to Econophysics
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  • Cited by 381
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    This book 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,

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

    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.

    Cordoba, Antonio Castillejo, Christian García-Machado, Juan J. and Lara, Ana M. 2018. Nonlinear Systems, Vol. 1. p. 317.

    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.

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

    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.

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

    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.

    Klishin, Andrei A Shields, Colin P F Singer, David J and van Anders, Greg 2018. Statistical physics of design. New Journal of Physics, Vol. 20, Issue. 10, p. 103038.

    Sigaki, Higor Y. D. Perc, Matjaž and Ribeiro, Haroldo V. 2018. History of art paintings through the lens of entropy and complexity. Proceedings of the National Academy of Sciences, Vol. 115, Issue. 37, p. E8585.

    Kumar, Niraj and Harbola, Upendra 2018. Memory induced anomalous dynamics in a random walker with internal states. Journal of Statistical Mechanics: Theory and Experiment, Vol. 2018, Issue. 10, p. 103207.

    Askitas, Nikos 2018. Remembering and Forgetting in the Digital Age. Vol. 38, Issue. , p. 135.

    Baaquie, Belal Ehsan 2018. Quantum Field Theory for Economics and Finance.

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

    Michas, Georgios and Vallianatos, Filippos 2018. Stochastic modeling of nonstationary earthquake time series with long-term clustering effects. Physical Review E, Vol. 98, Issue. 4,

    Jhun, Jennifer Palacios, Patricia and Weatherall, James Owen 2018. Market crashes as critical phenomena? Explanation, idealization, and universality in econophysics. Synthese, Vol. 195, Issue. 10, p. 4477.

    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.

    Mehri-Dehnavi, Hossein Agahi, Hamzeh and Mesiar, Radko 2018. Pseudo-exponential distribution and its statistical applications in econophysics. Soft Computing,


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

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