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A Rank-Based Approach to Zipf's Law

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  • Ricardo T. Fernholz
  • Robert Fernholz

Abstract

An Atlas model is a rank-based system of continuous semimartingales for which the steady-state values of the processes follow a power law, or Pareto distribution. For a power law, the log-log plot of these steady-state values versus rank is a straight line. Zipf's law is a power law for which the slope of this line is -1. In this note, rank-based conditions are found under which an Atlas model will follow Zipf's law. An advantage of this rank-based approach is that it provides information about the dynamics of systems that result in Zipf's law.

Suggested Citation

  • Ricardo T. Fernholz & Robert Fernholz, 2016. "A Rank-Based Approach to Zipf's Law," Papers 1602.08533, arXiv.org.
    • Handle: RePEc:arx:papers:1602.08533
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    References listed on IDEAS

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    1. Xavier Gabaix & Jean‐Michel Lasry & Pierre‐Louis Lions & Benjamin Moll, 2016. "The Dynamics of Inequality," Econometrica, Econometric Society, vol. 84, pages 2071-2111, November.
    2. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    3. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    4. Erzo G. J. Luttmer, 2011. "On the Mechanics of Firm Growth," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(3), pages 1042-1068.
    5. Ijiri, Yuji & Simon, Herbert A, 1974. "Interpretations of Departures from the Pareto Curve Firm-Size Distributions," Journal of Political Economy, University of Chicago Press, vol. 82(2), pages 315-331, Part I, M.
    6. Ricardo T. Fernholz & Christoffer Koch, 2016. "Why are big banks getting bigger?," Working Papers 1604, Federal Reserve Bank of Dallas.
    7. Tomoyuki Ichiba & Vassilios Papathanakos & Adrian Banner & Ioannis Karatzas & Robert Fernholz, 2009. "Hybrid Atlas models," Papers 0909.0065, arXiv.org, revised Apr 2011.
    8. Xavier Gabaix, 1999. "Zipf's Law for Cities: An Explanation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(3), pages 739-767.
    9. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
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