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Introduction to Econophysics
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  • Cited by 286
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Basu, K. and Mariani, Maria C. 2016. Handbook of High-Frequency Trading and Modeling in Finance.

    Beccar-Varela, M. P. Florescu, Ionut and SenGupta, I. 2016. Handbook of High-Frequency Trading and Modeling in Finance.

    Bil, Ł. Grech, D. and Podhajska, E. 2016. Methods of Non-Extensive Statistical Physics in Analysis of Price Returns on Polish Stock Market. Acta Physica Polonica A, Vol. 129, Issue. 5, p. 986.

    Bwanakare, S. Cierpiał-Wolan, M. and Mantaj, A. 2016. Predicting Gross Domestic Product Components through Tsallis Entropy Econometrics. Acta Physica Polonica A, Vol. 129, Issue. 5, p. 993.

    Gontis, V. 2016. Interplay between Endogenous and Exogenous Fluctuations in Financial Markets. Acta Physica Polonica A, Vol. 129, Issue. 5, p. 1023.

    Gould, Martin D. Porter, Mason A. and Howison, Sam D. 2016. The Long Memory of Order Flow in the Foreign Exchange Spot Market. Market Microstructure and Liquidity, Vol. 02, Issue. 01, p. 1650001.

    Granzotti, C. R. F. Martinez, A. S. and da Silva, M. A. A. 2016. Scaling analysis of random walks with persistence lengths: Application to self-avoiding walks. Physical Review E, Vol. 93, Issue. 5,

    Li, Zhaoyuan and Tian, Maozai 2016. A New Method For Dynamic Stock Clustering Based On Spectral Analysis. Computational Economics,

    Tsujimoto, Yutaka Miki, Yuki Shimatani, Satoshi and Kiyono, Ken 2016. Fast algorithm for scaling analysis with higher-order detrending moving average method. Physical Review E, Vol. 93, Issue. 5,

    Varela, M. P. Beccar Biney, F. Mariani, Maria C. SenGupta, I. Shpak, M. and Bezdek, P. 2016. Handbook of High-Frequency Trading and Modeling in Finance.

    Xu, Kaixuan and Wang, Jun 2016. Nonlinear multiscale coupling analysis of financial time series based on composite complexity synchronization. Nonlinear Dynamics,

    Alonso, Juan J. 2015. Low-temperature spin-glass behavior in a diluted dipolar Ising system. Physical Review B, Vol. 91, Issue. 9,

    Bagarello, F and Haven, E 2015. Toward a formalization of a two traders market with information exchange. Physica Scripta, Vol. 90, Issue. 1, p. 015203.

    Biondo, Alessio Emanuele Pluchino, Alessandro and Rapisarda, Andrea 2015. Modeling financial markets by self-organized criticality. Physical Review E, Vol. 92, Issue. 4,

    Burridge, James Gao, Yu and Mao, Yong 2015. Forgetfulness can help you win games. Physical Review E, Vol. 92, Issue. 3,

    Chetalova, Desislava Schäfer, Rudi and Guhr, Thomas 2015. Zooming into market states. Journal of Statistical Mechanics: Theory and Experiment, Vol. 2015, Issue. 1, p. P01029.

    Deng, Wei and Wang, Jun 2015. Statistical analysis on multifractal detrended cross-correlation coefficient for return interval by oriented percolation. International Journal of Modern Physics C, Vol. 26, Issue. 01, p. 1550002.

    Farkas, Illés J. Kun, Jeromos Jin, Yi He, Gaoqi and Xu, Mingliang 2015. Keeping speed and distance for aligned motion. Physical Review E, Vol. 91, Issue. 1,

    Fiedor, P. 2015. Partial Mutual Information Analysis of Financial Networks. Acta Physica Polonica A, Vol. 127, Issue. 3, p. 863.

    Hagerstrom, Aaron Morgan Murphy, Thomas Edward and Roy, Rajarshi 2015. Harvesting entropy and quantifying the transition from noise to chaos in a photon-counting feedback loop. Proceedings of the National Academy of Sciences, Vol. 112, Issue. 30, p. 9258.

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    Introduction to Econophysics
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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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