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Applications 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 finance. The bulk of what has recently become known as 'econophysics' in broader circles draws its motivation from observed scaling laws in financial markets and the abundance of data available from the economy's financial sphere. Sec. 2 of this review presents the robust power laws encountered in financial economics and discusses potential explanations for scaling in finance derived from models of stochastic interactions of traders. Sec. 3 provides an overview over other applications of statistical physics methodology in finance and attempts to evaluate the impact they have had so far on financial economics. 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. Sec. 5 reviews the new stylized facts that have been identified in cross-sectional data of firm characteristics and agent-based approaches to industrial organization and macroeconomic dynamics that have been motivated by these findings. We conclude with an assessment of the major methodological contributions of this new strand of research

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Paper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1425.

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Length: 69 pages
Date of creation: Jun 2008
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Handle: RePEc:kie:kieliw:1425

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Keywords: stylized facts; power laws; agent-based models; econophysics;

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Cited by:
  1. 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, vol. 4(8), pages 1-44.
  2. 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.
  3. Shu-Peng Chen & Ling-Yun He, 2013. "Bubble Formation and Heterogeneity of Traders: A Multi-Agent Perspective," Computational Economics, Society for Computational Economics, Society for Computational Economics, vol. 42(3), pages 267-289, October.
  4. Ladislav Krištoufek, 2010. "Long-Term Memory and Its Evolution in Returns of Stock Index PX Between 1997 and 2009," Politická ekonomie, University of Economics, Prague, University of Economics, Prague, vol. 2010(4), pages 471-487.
  5. 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.

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