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| '''Econophysics''' is an interdisciplinary research field, applying theories and methods originally developed by [[Physics|physicists]] in order to solve problems in [[economics]], usually those including uncertainty or [[stochastic process]]es and [[Chaos theory|nonlinear dynamics]]. Its application to the study of financial markets has also been termed [[statistical finance]] referring to its roots in [[statistical physics]].
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| ==History==
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| Physicists’ interest in the [[social sciences]] is not new; [[Daniel Bernoulli]], as an example, was the originator of utility-based preferences. One of the founders of [[neoclassical economic theory]], former Yale University Professor of Economics [[Irving Fisher]], was originally trained under the renowned Yale [[physicist]], [[Josiah Willard Gibbs]].<ref>[http://www.yaleeconomicreview.com/issues/2006_spring/financephysical.html Yale Economic Review, Retrieved October-25-09]</ref> Likewise, [[Jan Tinbergen]], who won the first [[Nobel Prize in economics]] in 1969 for having developed and applied dynamic models for the analysis of economic processes, studied physics with [[Paul Ehrenfest]] at [[Leiden University]].
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| Econophysics was started in the mid-1990s by several physicists working in the subfield of [[statistical mechanics]]. Unsatisfied with the traditional explanations and approaches of economists - which usually prioritized simplified approaches for the sake of soluble theoretical models over agreement with empirical data - they applied tools and methods from physics, first to try to match financial data sets, and then to explain more general economic phenomena.
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| One driving force behind econophysics arising at this time was the sudden availability of large amounts of financial data, starting in the 1980s. It became apparent that traditional methods of analysis were insufficient - standard economic methods dealt with homogeneous agents and equilibrium, while many of the more interesting phenomena in financial markets fundamentally depended on [[Heterogeneous agents#Social and human science|heterogeneous agents]] and far-from-equilibrium situations.
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| The term “econophysics” was coined by [[H. Eugene Stanley]], to describe the large number of papers written by physicists in the problems of (stock and other) markets, in a conference on statistical physics in [[Kolkata]] (erstwhile [[Calcutta]]) in 1995 and first appeared in its proceedings publication in [[Physica A]] 1996.<ref>[http://www.saha.ac.in/cmp/camcs/Stanley-interview.pdf Interview of H. E. Stanley on Econophysics (To be published in "IIM Kozhikode Society & Management Review", Sage publication (USA), Vol. 2 Issue 2 (2013))]</ref><ref>[http://arxiv.org/abs/1308.2191 Econophysics Research in India in the last two Decades (1993-2013)]</ref> The inaugural meeting on Econophysics was organised 1998 in Budapest by [[János Kertész]] and [[Imre Kondor]].
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| Currently, the almost regular meeting series on the topic include: APFA, ECONOPHYS-KOLKATA,<ref> ECONOPHYS-KOLKATA VII : Econophysics of Agent Based Models, 8-12 November 2012 (Proc. Vol.: Econophysics of Agent Based Models, Eds. F. Abergel, H. Aoyama, B.K. Chakrabarti, A. Chakraborti, A. Ghosh, New Economic Windows, Springer Int. Publ., Switzerland, 2013); ECONOPHYS-KOLKATA VI : Econophysics of Systemic Risk and Network Dynamics, 21-25 October 2011 (Proc. Vol.: Econophysics of Systemic Risk and Network Dynamics, Eds. F. Abergel, B.K. Chakrabarti, A. Chakraborti, A. Ghosh, New Economic Windows, Springer-Verlag, Milan, 2012); ECONOPHYS-KOLKATA V : Econophysics of Order-Driven Markets, 9-13 March 2010 (Proc. Vol.: Econophysics of Order-driven Markets, Eds. F. Abergel, B.K. Chakrabarti, A. Chakraborti, M. Mitra, New Economic Windows, Springer-Verlag, Milan, 2011); ECONOPHYS-KOLKATA IV : Econophysics of Games and Social Choices, 9-13 March 2009 (Proc. Vol.: Econophysics & Economics of Games, Social Choices and Quantitative Techniques, Eds. B. Basu, B. K. Chakrabarti, S. R. Chakravarty, K. Gangopadhyay, New Economic Windows, Springer-Verlag, Milan, 2010); ECONOPHYS-KOLKATA III: Econophysics & Sociophysics of Markets and Networks, 12-15 March 2007 (Proc. Vol.: Econophysics of Markets and Business Networks, Eds. A. Chatterjee, B.K. Chakrabarti, New Economic Windows, Springer-Verlag, Milan, 2007); ECONOPHYS-KOLKATA II: Econophysics of Stock Markets and Minority Games, 14-17 February 2006 (Proc. Vol.: Econophysics of Stock and other Markets, Eds. A. Chatterjee, B.K. Chakrabarti, New Economic Windows, Springer-Verlag, Milan, 2006); ECONOPHYS-KOLKATA I: Econophysics of Wealth Distributions, 15-19 March 2005 (Proc. Vol.: Econophysics of Wealth Distributions, Eds. A. Chatterjee, S. Yarlagadda, B.K. Chakrabarti, New Economic Windows, Springer-Verlag, Milan, 2005). </ref> Econophysics Colloquium, ESHIA/ WEHIA.
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| In recent years [[network science]], heavily reliant on analogies from [[statistical mechanics]], has been applied to the study of productive systems. That is the case with the works done at the [[Santa Fe Institute]] in European Funded Research Projects as [http://www.focproject.eu Forecasting Financial Crises] and the Harvard-MIT [[The Observatory of Economic Complexity|Observatory of Economic Complexity]]
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| If "econophysics" is taken to denote the principle of applying statistical mechanics to economic analysis, as opposed to a particular literature or network, priority of innovation is probably due to Emmanuel Farjoun and Moshé Machover (1983). Their book ''Laws of Chaos: A Probabilistic Approach to Political Economy'' proposes ''dis''solving (their words) the [[transformation problem]] in Marx's political economy by re-conceptualising the relevant quantities as random variables.<ref>Farjoun and Machover disclaim complete originality: their book is dedicated to the late Robert H. Langston, who they cite for direct inspiration (page 12), and they also note an independent suggestion in a discussion paper by [[Edwin Thompson Jaynes|E.T. Jaynes]] (page 239)</ref>
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| If, on the other side, "econophysics" is taken to denote the application of physics to
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| economics, one can already consider the works of [[Léon Walras]] and [[Vilfredo Pareto]] as part of it. Indeed, as shown by Ingrao and Israel, [[general equilibrium theory]] in economics is based on the physical concept of [[mechanical equilibrium]].
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| Econophysics has nothing to do with the "physical quantities approach" to economics, advocated by [[Ian Steedman]] and others associated with [[Neo-Ricardianism]]. Notable econophysicists are [[Jean-Philippe Bouchaud]], [[Bikas K Chakrabarti]], [[J. Doyne Farmer]], [[Dirk Helbing]], [[János Kertész]], Matteo Marsili, [[Joseph L. McCauley]], Enrico Scalas, [[Didier Sornette]], [[H. Eugene Stanley]], Victor Yakovenko and Yi-Cheng Zhang. Particularly noteworthy among the formal courses on Econophysics is the one offered by the Physics Department of the [[Leiden University]],<ref>{{cite web|url=https://studiegids.leidenuniv.nl/en/courses/show/34804/econofysica|title=Physics - Education |publisher=Physics.leidenuniv.nl |date=2011-2013|accessdate=2013}}</ref> from where the first Nobel-laureate in economics [[Jan Tinbergen]] came.
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| ==Basic tools==
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| Basic tools of econophysics are [[Probability|probabilistic]] and [[Statistics|statistical]] methods often taken from statistical physics.
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| Physics models that have been applied in economics include the [[kinetic theory of gas]] (called the [[Kinetic exchange models of markets]] <ref>{{cite book| author=[[Bikas K Chakrabarti]], Anirban Chakraborti, Satya R Chakravarty, Arnab Chatterjee |title=Econophysics of Income & Wealth Distributions | publisher=[[Cambridge University Press]], [[Cambridge]]|year= 2012 |work=}} </ref>), [[percolation]] models, [[Chaos theory|chaotic]] models developed to study cardiac arrest, and models with [[self-organizing criticality]] as well as other models developed for [[earthquake prediction]].<ref>{{cite book |author=[[Didier Sornette]] |title=Why Stock Markets Crash? |publisher=[[Princeton University Press]]|year= 2003 |accessdate=2008-02-19 |work=}}</ref> Moreover, there have been attempts to use the mathematical theory of [[complexity]] and [[information theory]], as developed by many scientists among whom are [[Murray Gell-Mann]] and [[Claude E. Shannon]], respectively.
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| Since economic phenomena are the result of the interaction among many heterogeneous [[Agent (economics)|agents]], there is an analogy with statistical mechanics, where many particles interact; but it must be taken into account that the properties of human beings and particles significantly differ.
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| Another good example is [[random matrix theory]], which can be used to identify the noise in financial correlation matrices. It has been shown that this technique can significantly improve the performance of portfolios, e.g., in applied in [[Modern portfolio theory|portfolio optimization]].<ref>{{cite journal |author=Vasiliki Plerou, Parameswaran Gopikrishnan, Bernd Rosenow, Luis Amaral, Thomas Guhr and H. Eugene Stanley |title=Random matrix approach to cross correlations in financial data |journal=Physical Review E|volume= 65|page= 066126 |year=2002 |doi=10.1103/PhysRevE.65.066126 | issue = 6|arxiv = cond-mat/0108023 |bibcode = 2002PhRvE..65f6126P }}</ref> Thus, this practice is commonly encountered in the praxis of quantitative finance.
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| There are, however, various other tools from physics that have so far been used with mixed success, such as [[fluid dynamics]], [[classical mechanics]] and [[quantum mechanics]] (including so-called [[classical economy]], [[quantum economy]] and [[quantum finance]]), and the [[path integral formulation]] of statistical mechanics.
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| The concept of [[economic complexity index]], introduced by the Harvard economist [[Ricardo Hausmann]] and the MIT physicist Cesar Hidalgo, has been further developed at the Harvard-MIT [[The Observatory of Economic Complexity|Observatory of Economic Complexity]], has been devised as a [[List of countries by future GDP (based on ECI) estimates|predictive tool for economic growth]]. According to the estimates of Hausmann and Hidalgo, the ECI is far more accurate in predicting GDP growth than the traditional governance measures of the [[World Bank]].<ref>{{cite web |url=http://atlas.media.mit.edu/book/ |title= The Atlas of Economic Complexity |author= Ricardo Hausmann, Cesar Hidalgo, et al. |publisher= The Observatory of Economic Complexity (Harvard HKS/CDI - MIT Media Lab) |accessdate=26 April 2012}}</ref>
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| There are also analogies between finance theory and [[diffusion]] theory. For instance, the [[Black–Scholes equation]] for [[option (finance)|option]] pricing is a [[diffusion equation|diffusion]]-[[advection]] equation (see however <ref name="autogenerated2003">{{cite book |author=Jean-Philippe Bouchaud, Marc Potters |title=Theory of Financial Risk and Derivative Pricing |publisher=Cambridge University Press|year= 2003 |accessdate=2007-08-27 |work=}}</ref><ref>"Welcome to a non Black-Scholes world"[http://www.tandfonline.com/doi/abs/10.1080/713665871?journalCode=rquf20]</ref> for a critique of the Black-Scholes methodology).
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| ==Influence==
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| Papers on econophysics have been published primarily in journals devoted to physics and statistical mechanics, rather than in leading economics journals. [[Mainstream economics|Mainstream economists]] have generally been unimpressed by this work.<ref>{{cite journal |author=Philip Ball |title=Econophysics: Culture Crash |journal=Nature |volume=441 |pages=686–688 |year=2006 |work= |doi=10.1038/441686a |pmid=16760949 |issue=7094|bibcode = 2006Natur.441..686B }}</ref> Some [[Heterodox economics|Heterodox economists]], including [[Mauro Gallegati]], [[Steve Keen]] and [[Paul Ormerod]], have shown more interest, but also criticized trends in econophysics.
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| In contrast, econophysics is having some impact on the more applied field of [[quantitative finance]], whose scope and aims significantly differ from those of economic theory. Various econophysicists have introduced models for price fluctuations in [[financial markets]] or original points of view on established models.<ref name="autogenerated2003"/><ref>{{cite journal |author=Enrico Scalas |title=The application of continuous-time random walks in finance and economics |journal=Physica A |volume=362 |pages=225–239 |year=2006 |doi=10.1016/j.physa.2005.11.024|bibcode = 2006PhyA..362..225S |issue=2 }}</ref> Also several scaling laws have been found in various economic data.<ref>{{cite journal |author=Y. Liu, P. Gopikrishnan, P. Cizeau, M. Meyer, C.-K. Peng, and H. E. Stanley |title=Statistical properties of the volatility of price fluctuations |year=1999| journal=[[Physical Review E]]| volume=60| issue=2| page=1390| doi= 10.1103/PhysRevE.60.1390|arxiv = cond-mat/9903369 |bibcode = 1999PhRvE..60.1390L }}</ref><ref>{{cite journal |author=M. H. R. Stanley, L. A. N. Amaral, S. V. Buldyrev, S. Havlin, H. Leschhorn, P. Maass, M. A. Salinger, H. E. Stanley |title=Scaling behaviour in the growth of companies |journal=Nature |volume=379 |page=804 |year=1996| url=http://havlin.biu.ac.il/Publications.php?keyword=Scaling+behaviour+in+the+growth+of+companies&year=*&match=all |doi=10.1038/379804a0 |issue=6568|bibcode = 1996Natur.379..804S }}</ref><ref>{{cite journal |author=K. Yamasaki, L. Muchnik, S. Havlin, A. Bunde, and H.E. Stanley |title=Scaling and memory in volatility return intervals in financial markets |journal=PNAS |volume=102 |pages=9424–8 |year=2005| url=http://havlin.biu.ac.il/Publications.php?keyword=Scaling+and+memory+in+volatility+return+intervals+in+financial+markets&year=*&match=all |doi=10.1073/pnas.0502613102 |pmid=15980152 |issue=26 |pmc=1166612|bibcode = 2005PNAS..102.9424Y }}</ref>
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| ==Main results==
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| Presently, the main results of econophysics comprise the explanation of the [[Fat-tailed distribution|"fat tails"]] in the distribution of many kinds of financial data as a [[Universality class|universal]] self-similar [[scaling invariance|scaling]] property (i.e. scale invariant over many orders of magnitude in the data),<ref>The physicists noted the scaling behaviour of "fat tails" through a Letter to the scientific journal ''[[Nature]]'' by Rosario N. Mantegna and H. Eugene Stanley: ''Scaling behavior in the dynamics of an economic index'', Nature Vol. 376, pages 46-49 (1995), however the "fat tails"- phenomenon itself was discovered already earlier by economists.</ref> arising from the tendency of individual market competitors, or of aggregates of them, to exploit systematically and optimally the prevailing "microtrends" (e.g., rising or falling prices). These "fat tails" are not only mathematically important, because they comprise the [[risk]]s, which may be on the one hand, very small such that one may tend to neglect them, but which - on the other hand - are not neglegible at all, i.e. they can never be made exponentially tiny, but instead follow a measurable algebraically decreasing power law, for example with a ''failure probability'' of only <math>P\propto x^{-4}\,,</math> where ''x'' is an increasingly large variable in the tail region of the distribution considered (i.e. a price statistics with much more than 10<sup>8</sup> data). I.e., the events considered are not simply "outliers" but must really be taken into account and cannot be "insured away". <ref name="Preis" /> It appears that it also plays a role that near a change of the tendency (e.g. from falling to rising prices) there are typical "panic reactions" of the selling or buying agents with algebraically increasing bargain rapidities and volumes. <ref name="Preis">See for example Preis, Mantegna, 2003. </ref> The "fat tails" are also observed in [[commodity market]]s.
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| As in quantum field theory the "fat tails" can only be obtained by complicated "[[nonperturbative]]" methods, mainly by numerical ones, since they contain the deviations from the usual [[Gaussian distribution|Gaussian approximations]], e.g. the [[Black-Scholes]] theory.
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| ==See also==
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| {{Portal|Physics}}
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| * [[Bose–Einstein condensation (network theory)]]
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| * [[Complexity economics]]
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| * [[Complex network]]
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| * [[Detrended fluctuation analysis]]
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| * [[Kinetic exchange models of markets]]
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| * [[Long-range dependency]]
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| * [[Network theory]]
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| * [[Network science]]
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| * [[Thermoeconomics]]
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| ==References==
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| {{Reflist}}
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| ==Further reading==
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| * [[Rosario N. Mantegna]], [[H. Eugene Stanley]], ''An Introduction to Econophysics: Correlations and Complexity in Finance'', [http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=0521620082 Cambridge University Press (Cambridge, UK, 1999)]
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| *Sitabhra Sinha, Arnab Chatterjee, Anirban Chakraborti, [[Bikas K Chakrabarti]]. ''Econophysics: An Introduction'', [http://www.wiley.com/WileyCDA/WileyTitle/productCd-3527408150,descCd-authorInfo.html Wiley-VCH (2010)]
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| * [[Bikas K Chakrabarti]], Anirban Chakraborti, Arnab Chatterjee, ''Econophysics and Sociophysics : Trends and Perspectives'', [http://www.wiley-vch.de/publish/en/books/bySubjectPH00/bySubSubjectPH95/3-527-40670-0/?sID=d05b Wiley-VCH, Berlin (2006)]
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| *[[Joseph McCauley]], ''Dynamics of Markets, Econophysics and Finance'', [http://www.cambridge.org/catalogue/catalogue.asp?isbn=0521824478 Cambridge University Press (Cambridge, UK, 2004)]
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| * [[Bertrand Roehner]], ''Patterns of Speculation - A Study in Observational Econophysics'', [http://www.cambridge.org/catalogue/catalogue.asp?isbn=0521675731 Cambridge University Press (Cambridge, UK, 2002)]
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| * Arnab Chatterjee, Sudhakar Yarlagadda, [[Bikas K Chakrabarti]], ''Econophysics of Wealth Distributions'', [http://www.springer.com/sgw/cda/frontpage/0,,5-165-72-52121089-0,00.html Springer-Verlag Italia (Milan, 2005)]
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| * [[Philip Mirowski]], ''More Heat than Light - Economics as Social Physics, Physics as Nature's Economics'', [http://www.cambridge.org/catalogue/catalogue.asp?isbn=0521426898 Cambridge University Press (Cambridge, UK, 1989)]
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| * Ubaldo Garibaldi and Enrico Scalas, ''Finitary Probabilistic Methods in Econophysics'', [http://www.cambridge.org/gb/knowledge/isbn/item2708018/?site_locale=en_GB Cambridge University Press (Cambridge, UK, 2010)].
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| * Emmanual Farjoun and Moshé Machover, ''Laws of Chaos: a probabilistic approach to political economy'', [http://staffnet.kingston.ac.uk/~ku32530/PPE/PPEindex.html Verso (London, 1983) ISBN 0 86091 768 1]
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| * Nature Physics Focus issue: Complex networks in finance March 2013 Volume 9 No 3 pp 119-128
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| * Mark Buchanan, ''What has econophysics ever done for us?'', [http://www.nature.com.proxy.queensu.ca/nphys/journal/v9/n6/full/nphys2648.html Nature 2013 ]
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| ==Lectures==
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| * Economic Fluctuations and Statistical Physics: Quantifying Extremely Rare and Much Less Rare Events, [[Eugene Stanley]], [http://videolectures.net/ccss09_stanley_efasp/ Videolectures.net]
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| * Applications of Statistical Physics to Understanding Complex Systems, [[Eugene Stanley]], [http://videolectures.net/eccs08_stanley_aosptucs/ Videolectures.net]
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| * Financial Bubbles, Real Estate Bubbles, Derivative Bubbles, and the Financial and Economic Crisis, [[Didier Sornette]], [http://videolectures.net/ccss09_sornette_fbreb/ Videolectures.net]
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| * Financial crises and risk management, [[Didier Sornette]], [http://videolectures.net/risc08_sornette_fcrm/ Videolectures.net]
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| * Bubble trouble: how physics can quantify stock-market crashes, [[Tobias Preis]], [http://physicsworld.com/cws/article/multimedia/45725 Physics World Online Lecture Series]
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| ==External links==
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| * [http://phys.uh.edu/research/econophysics/index.php Econophysics Ph.D. Program at University of Houston, Houston, TX.]
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| * [http://www.yaleeconomicreview.com/issues/2006_spring/financephysical.html Finance Gets Physical] - Yale Economic Review
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| * [http://www.unifr.ch/econophysics/ Econophysics Forum]
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| * [http://staffnet.kingston.ac.uk/~ku32530/PPE/PPEindex.html Conference to mark 25th anniversary of Farjoun and Machover's book]
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| * [http://www.uni-bamberg.de/en/vwl-iwf/ Chair of International Economics, University of Bamberg (Germany)]
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| {{Physics-footer}}
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