IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1802.02939.html
   My bibliography  Save this paper

The sum of log-normal variates in geometric Brownian motion

Author

Listed:
  • Ole Peters
  • Alexander Adamou

Abstract

Geometric Brownian motion (GBM) is a key model for representing self-reproducing entities. Self-reproduction may be considered the definition of life [5], and the dynamics it induces are of interest to those concerned with living systems from biology to economics. Trajectories of GBM are distributed according to the well-known log-normal density, broadening with time. However, in many applications, what's of interest is not a single trajectory but the sum, or average, of several trajectories. The distribution of these objects is more complicated. Here we show two different ways of finding their typical trajectories. We make use of an intriguing connection to spin glasses: the expected free energy of the random energy model is an average of log-normal variates. We make the mapping to GBM explicit and find that the free energy result gives qualitatively correct behavior for GBM trajectories. We then also compute the typical sum of lognormal variates using Ito calculus. This alternative route is in close quantitative agreement with numerical work.

Suggested Citation

  • Ole Peters & Alexander Adamou, 2018. "The sum of log-normal variates in geometric Brownian motion," Papers 1802.02939, arXiv.org.
    • Handle: RePEc:arx:papers:1802.02939
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1802.02939
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ole Peters & Murray Gell-Mann, 2014. "Evaluating gambles using dynamics," Papers 1405.0585, arXiv.org, revised Jun 2015.
    2. Ole Peters & William Klein, 2012. "Ergodicity breaking in geometric Brownian motion," Papers 1209.4517, arXiv.org, revised Mar 2013.
    3. Jean-Philippe Bouchaud & Marc Mezard, 2000. "Wealth condensation in a simple model of economy," Science & Finance (CFM) working paper archive 500026, Science & Finance, Capital Fund Management.
    4. Jean-Philippe Bouchaud, 2015. "On growth-optimal tax rates and the issue of wealth inequalities," Papers 1508.00275, arXiv.org, revised Aug 2015.
    5. Ole Peters & Alexander Adamou, 2015. "An evolutionary advantage of cooperation," Papers 1506.03414, arXiv.org, revised May 2018.
    6. Bouchaud, Jean-Philippe & Mézard, Marc, 2000. "Wealth condensation in a simple model of economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 282(3), pages 536-545.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cyprien Grau, 2020. "Stochastic Valuation of Revenue-Collecting Tokens in Cryptoeconomic Organizations," Working Papers hal-02894497, HAL.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stojkoski, Viktor & Karbevski, Marko & Utkovski, Zoran & Basnarkov, Lasko & Kocarev, Ljupco, 2021. "Evolution of cooperation in networked heterogeneous fluctuating environments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    2. Zhiyuan Liu & R. A. Serota, 2017. "On absence of steady state in the Bouchaud-M\'ezard network model," Papers 1704.02377, arXiv.org.
    3. Seroussi, Inbar & Sochen, Nir, 2020. "Localization phase transition in stochastic dynamics on networks with hub topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    4. M. Dashti Moghaddam & Zhiyuan Liu & R. A. Serota, 2019. "Distributions of Historic Market Data -- Relaxation and Correlations," Papers 1907.05348, arXiv.org, revised Feb 2020.
    5. Liu, Z. & Serota, R.A., 2017. "Correlation and relaxation times for a stochastic process with a fat-tailed steady-state distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 301-311.
    6. Kemp, Jordan T. & Bettencourt, Luís M.A., 2022. "Statistical dynamics of wealth inequality in stochastic models of growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    7. Venkatasubramanian, Venkat & Luo, Yu & Sethuraman, Jay, 2015. "How much inequality in income is fair? A microeconomic game theoretic perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 435(C), pages 120-138.
    8. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    9. Kočišová, J. & Horváth, D. & Brutovský, B., 2009. "The efficiency of individual optimization in the conditions of competitive growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3585-3592.
    10. Bertram During & Nicos Georgiou & Enrico Scalas, 2016. "A stylized model for wealth distribution," Papers 1609.08978, arXiv.org, revised Jul 2021.
    11. Yougui Wang & Ning Ding, 2005. "Dynamic Process of Money Transfer Models," Papers physics/0507162, arXiv.org.
    12. Liebmann, Thomas & Kassberger, Stefan & Hellmich, Martin, 2017. "Sharing and growth in general random multiplicative environments," European Journal of Operational Research, Elsevier, vol. 258(1), pages 193-206.
    13. Tamotsu Onozaki, 2018. "Nonlinearity, Bounded Rationality, and Heterogeneity," Springer Books, Springer, number 978-4-431-54971-0, April.
    14. Smerlak, Matteo, 2016. "Thermodynamics of inequalities: From precariousness to economic stratification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 441(C), pages 40-50.
    15. Marco Raberto & Silvano Cincotti & Sergio Focardi & Michele Marchesi, 2003. "Traders' Long-Run Wealth in an Artificial Financial Market," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 255-272, October.
    16. Weisbuch, Gérard & Battiston, Stefano, 2007. "From production networks to geographical economics," Journal of Economic Behavior & Organization, Elsevier, vol. 64(3-4), pages 448-469.
    17. Jiong Liu & R. A. Serota, 2023. "Rethinking Generalized Beta family of distributions," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 96(2), pages 1-14, February.
    18. Geoff Willis & Juergen Mimkes, 2004. "Evidence for the Independence of Waged and Unwaged Income, Evidence for Boltzmann Distributions in Waged Income, and the Outlines of a Coherent Theory of Income Distribution," Microeconomics 0408001, University Library of Munich, Germany.
    19. Hu, Feng-Rung, 2008. "On the estimation of the power-law exponent in the mean-field Bouchaud–Mézard model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4605-4614.
    20. G. Willis, 2004. "Laser Welfare: First Steps in Econodynamic Engineering," Papers cond-mat/0408227, arXiv.org.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1802.02939. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.