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Econophysics of Systemic Risk and Network Dynamics (New Economic Windows)

Abergel, Frédéric, Chakrabarti, Bikas K., Chakraborti, Anirban and Ghosh, Asim (eds.)
Springer-Verlag: Berlin, 2012
ISBN 9788847025523 (hb)

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Reviewed by Alberto Russo
Department of Economics and Social Sciences, Universit Politecnica delle Marche, Ancona

Cover of book This book is a Proceeding volume edited by Frédéric Abergel, Bikas K. Chakrabarti, Anirban Chakraborti and Asim Ghosh which contains a selection of papers presented at the Econophys-Kolkata VI Conference, held in October 21-25 2012 in Kolkata, India. The book proposes an ample set of both theoretical and empirical contributions in the field of Econophysics and is worth reading particularly for those who are interested in the application of physics to economic and financial topics. However, reading this book could be beneficial for many others, given that systemic risk and network dynamics have gained momentum in economics and finance.

One of the relevant messages of the book is that systemic risk regards the working of the financial system as a whole, thus it does not just depend on the behaviour of a single financial institution. Therefore, we need to understand the effects of the interaction among heterogeneous agents, e.g., by applying aggregation methods or simulating network dynamics. An effort in this direction is then welcome to understand modern economies as complex adaptive systems. For this endeavour, contributions by physicists can be very important to discover complex patterns of individual and collective behaviour in large-scale, highly heterogeneous, interconnected systems.

The book is organised in three parts. Part I focuses on “Systemic risk, network dynamics and other empirical facts”. In this first part, systemic risk is related to financial contagion (Chapter 1 by Gabrielle Demange), by applying a graph-theoretic approach (Chapter 2 by Delphine Lautier and Franck Raynaud), and considering the (in)stability of interbank lending (Chapter 5 by Sitabhra Sinha, Maximilian Thess and Sheri Markose). The ‘Omori Law’, which describes the power law decay of relaxation time for the number of aftershocks after a major earthquake, is used to study the relaxation process of supplier-customer networks after mass destruction (Chapter 3 by Yoshi Fujiwara) and the occurrence of aftershocks following a major financial crash (Chapter 4 by Fulvio Baldovin et al.). The Zipf law, originally developed in linguistics, is used to explain the distribution of populations for Indian cities and to make a parallel with agglomeration patterns in China (Chapter 8 by Kausik Gangopadhyay and Banasri Basu). Moreover, some studies analyse co-movements in financial markets by investigating the complex patterns emerging from very large databases with intraday tick-by-tick observations (Chapter 6 by Gayatri Tilak et al.) and examine ‘contrarian’ behaviour which characterises (with widely different intensities) individual investors, companies and asset managers (Chapter 7 by Damien Challet and David Morton de Lachapelle).

Part II includes “model-based studies”. In recent years, physicists have largely contributed to the empirical analysis of financial markets, detecting some stylised facts by applying statistical methods to analyse available high-frequency data on a large scale. However, they have also proposed some theoretical contributions, such as stochastic models and Agent-Based Models (ABMs). For instance, using a ‘minimal’ ABM, we can observe how the trend following strategy of ‘chartists’ causes the overshooting of agents’ behaviour with respect to exogenously induced price fluctuations in financial markets (Chapter 9 by Andrea Zaccaria, Matthieu Cristelli and Lucano Pietronero). Predatory trading can cause a systemic collapse of financial markets in the absence of interaction-limiting ‘firewalls’ (Chapter 10 by Anita Mehta). Statistical mechanics can be a valuable tool to model and analyse the evolution of the labour market and its transitions from a ‘good’ to a ‘poor employment phase’ (Chapter 11 by He Chen and Jun-ichi Inoue). A physics approach can be usefully applied to a game-theoretic context, such as the choice of a restaurant, when there are many choices to be compared: some contributions analyse the specific context of the Kolkata Restaurant Problem by discussing several stochastic optimisation strategies (Chapter 12 by Asim Ghosh et al.), by detecting a cyclical norm in a revisited version of the above game (Chapter 13 by Priyodorshi Banerjee, Manipushpak Mitra and Conan Mukherjce), or through employing methods from quantum game theory, that is an approach which combines quantum mechanics, information theory, and game theory (Chapter 14 by Puya Sharif and Hoshang Heydari).

Part III contains some miscellaneous studies, such as an analysis of cross-correlations and clustering of Japanese stocks (Chapter 15 by Takero Ibuki, Sei Suzuki and Jun-ichi Inoue), a study of crisis in global financial indices that applies Random Matrix Theory and complex network techniques (Chapter 16 by Sunil Kumar and Nivedita Deo), an analysis of systemic risk involved in mutual funds, in terms of macroscopic property due to the combination of microscopic components, i.e., different stocks in the portfolio (Chapter 17 by Kishore C. Dash and Monika Dash) and an application of ‘wavelets’ and Random Matrix Theory to analyse fluctuations at various frequency windows (chapter 18 by Prasanta K. Panigrahi et al.).

In conclusion, the book has some typical shortcomings of any collection of heterogeneous contributions, which span considerably different topics. This can discourage non-specialised readers who are looking for some introductory, systematic picture. However, the book does not aim at providing an introduction to Econophysics. Rather, it presents recent advances in this field and it deserves attention by more advanced readers, especially those interested in cross-disciplinary analyses.


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