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Application of Statistical Physics in Finance and Economics

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  • Thomas Lux

Abstract

This chapter reviews recent research adopting methods from statistical physics in theoretical or empirical work in economics and nance. The bulk of what has recently become known as 'econophysics' in broader circles draws its motivation from observed scaling laws in nancial markets and the abundance of data available from the economy's nancial sphere. The rst part of this review presents the robust power laws encountered in nancial economics and discusses potential explanations for scaling in nance derived from models of stochastic interactions of traders. Sec. 3 provides an overview over other applications of statistical physics methodology in nance and attempts to evaluate the impact they have had so far on nancial economies. With the following section, the review turns to recent work on the emergence of wealth and income heterogeneity and the recent inception of new strands of research on this topic both within econophysics and the neoclassical economics tradition. The third part reviews the new stylized facts that have been identi ed in cross-sectional data of rm characteristics and agent-based approaches to industrial organization and macroeconomic dynamics that have been motivated by these ndings. We conclude with an assessment of the major methodological contributions of this new strand of research.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Thomas Lux, 2007. "Application of Statistical Physics in Finance and Economics," Working Papers wp07-09, Warwick Business School, Finance Group.
  • Handle: RePEc:wbs:wpaper:wp07-09
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    Citations

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    Cited by:

    1. Kristoufek, Ladislav, 2009. "Procesy s dlouhou pamětí a jejich vývoj ve výnosech indexu PX v letech 1999 – 2009
      [Long-term memory and its evolution in returns of PX between 1999 and 2009]
      ," MPRA Paper 16435, University Library of Munich, Germany.
    2. Kristoufek, Ladislav, 2009. "Distinguishing between short and long range dependence: Finite sample properties of rescaled range and modified rescaled range," MPRA Paper 16424, University Library of Munich, Germany.
    3. Shu-Peng Chen & Ling-Yun He, 2013. "Bubble Formation and Heterogeneity of Traders: A Multi-Agent Perspective," Computational Economics, Springer;Society for Computational Economics, vol. 42(3), pages 267-289, October.
    4. Ladislav Krištoufek, 2010. "Dlouhá paměť a její vývoj ve výnosech burzovního indexu PX v letech 1997-2009
      [Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009]
      ," Politická ekonomie, University of Economics, Prague, vol. 2010(4), pages 471-487.
    5. Demary, Markus, 2010. "Transaction taxes and traders with heterogeneous investment horizons in an agent-based financial market model," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 4, pages 1-44.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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