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Turnover Activity in Wealth Portfolios

Author

Listed:
  • Mishael Milakovic
  • Carolina Castaldi

Abstract

We examine several named subsets of the wealthiest individuals in the US and the UK that are compiled by Forbes Magazine and Sunday Times. The data support conventional wisdom of a wealth distribution with power law-distributed right tail, and they allow us to calibrate a statistical equilibrium model of wealth distribution. Such a model is not only able to account for the observed power law tail of wealth distribution, but is also consistent with the asymmetric laplacian distribution of portfolio returns that we observe in both our samples. In addition, with information on the distribution of portfolio returns that we construct from the subsets, the model provides an indicator for how often changes in the composition of the wealthiest portfolios occur – an indicator we call turnover activity. Finally, we also calculate a simple mobility measure from the subsets and look at trends in equality, mobility and turnover activity.

Suggested Citation

  • Mishael Milakovic & Carolina Castaldi, 2004. "Turnover Activity in Wealth Portfolios," Computing in Economics and Finance 2004 120, Society for Computational Economics.
    • Handle: RePEc:sce:scecf4:120
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    Cited by:

    1. Alfarano, Simone & Milakovic, Mishael, 2008. "Does classical competition explain the statistical features of firm growth?," Economics Letters, Elsevier, vol. 101(3), pages 272-274, December.
    2. Mikhail Goykhman, 2017. "Wealth dynamics in a sentiment-driven market," Papers 1705.07092, arXiv.org.
    3. Hamermesh, Daniel S. & Leigh, Andrew K., 2022. "“Beauty too rich for use”: Billionaires’ assets and attractiveness," Labour Economics, Elsevier, vol. 76(C).
    4. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    5. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    6. Lux, Thomas, 2008. "Applications of statistical physics in finance and economics," Kiel Working Papers 1425, Kiel Institute for the World Economy.
    7. Sylvain Barde, 2015. "Back to the Future: Economic Self-Organisation and Maximum Entropy Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 337-358, February.
    8. Philip Hans Franses & Stephanie Vermeer, 2012. "Inequality amongst the wealthiest and its link with economic growth," Applied Economics, Taylor & Francis Journals, vol. 44(22), pages 2851-2858, August.
    9. Fiaschi, Davide & Marsili, Matteo, 2012. "Distribution of wealth and incomplete markets: Theory and empirical evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 243-267.
    10. Alfarano, Simone & Milaković, Mishael & Irle, Albrecht & Kauschke, Jonas, 2012. "A statistical equilibrium model of competitive firms," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 136-149.
    11. Giulio Bottazzi, 2007. "On the Pareto Type III distribution," LEM Papers Series 2007/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    12. Jan Schulz & Mishael Milaković, 2023. "How Wealthy are the Rich?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(1), pages 100-123, March.
    13. Sylvain Barde, 2012. "Back to the future: economic rationality and maximum entropy prediction," Studies in Economics 1202, School of Economics, University of Kent.
    14. Schulz, Jan & Weber, Jan David, 2025. "Power laws in socio-economics," BERG Working Paper Series 203, Bamberg University, Bamberg Economic Research Group.
    15. Rishabh Kumar, 2016. "Capital and the Hindu rate of growth: Top Indian wealth holders 1961-1986," Working Papers 1608, New School for Social Research, Department of Economics.
    16. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    17. Goykhman, Mikhail, 2017. "Wealth dynamics in a sentiment-driven market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 132-148.

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    Keywords

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    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General

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