Power laws of wealth, market order volumes and market returns

Using the Generalized Lotka Volterra model adapted to deal with mutiagent systems we can investigate economic systems from a general viewpoint and obtain generic features common to most economies. Assuming only weak generic assumptions on capital dynamics, we are able to obtain very specific predictions for the distribution of social wealth. First, we show that in a ‘fair’ market, the wealth distribution among individual investors fulfills a power law. We then argue that ‘fair play’ for capital and minimal socio-biological needs of the humans traps the economy within a power law wealth distribution with a particular Pareto exponent α∼32. In particular, we relate it to the average number of individuals L depending on the average wealth: α∼L/(L−1). Then we connect it to certain power exponents characterizing the stock markets. We find that the distribution of volumes of the individual (buy and sell) orders follows a power law with similar exponent β∼α∼32. Consequently, in a market where trades take place by matching pairs of such sell and buy orders, the corresponding exponent for the market returns is expected to be of order γ∼2α∼3. These results are consistent with recent experimental measurements of these power law exponents (S. Maslov, M. Mills, Physica A 299 (2001) 234 for β; P. Gopikrishnan et al., Phys. Rev. E 60 (1999) 5305 for γ).

[1]  S. Solomon,et al.  Spontaneous Scaling Emergence In Generic Stochastic Systems , 1996 .

[2]  Peter Richmond,et al.  Power law distributions and dynamic behaviour of stock markets , 2001 .

[3]  A. J. Lotka,et al.  Elements of Physical Biology. , 1925, Nature.

[4]  H. S,et al.  Scale-invariant correlations in the biological and social sciences , 2002 .

[5]  M. Mézard,et al.  Wealth condensation in a simple model of economy , 2000, cond-mat/0002374.

[6]  Sergei Maslov,et al.  Dynamical optimization theory of a diversified portfolio , 1998 .

[7]  Moshe Levy,et al.  The Complex Dynamics of a Simple Stock Market Model , 1996, Int. J. High Speed Comput..

[8]  Stanley,et al.  Statistical properties of share volume traded in financial markets , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[9]  George Kingsley Zipf,et al.  Human behavior and the principle of least effort , 1949 .

[10]  J. Moody,et al.  Decision Technologies for Computational Finance , 1998 .

[11]  V. Plerou,et al.  Scaling of the distribution of fluctuations of financial market indices. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[12]  J. Farmer Market Force, Ecology, and Evolution , 1998, adap-org/9812005.

[13]  S. Solomon,et al.  The importance of being discrete: life always wins on the surface. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[14]  E W Montroll,et al.  Social dynamics and the quantifying of social forces. , 1978, Proceedings of the National Academy of Sciences of the United States of America.

[15]  S. Solomon,et al.  Adaptation of autocatalytic fluctuations to diffusive noise. , 2000, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  H. A. Simon,et al.  Skew Distributions and the Size of Business Firms , 1977 .

[17]  S. Solomon,et al.  NEW EVIDENCE FOR THE POWER-LAW DISTRIBUTION OF WEALTH , 1997 .

[18]  V. Volterra Fluctuations in the Abundance of a Species considered Mathematically , 1926 .

[19]  S Solomon,et al.  Power-law distributions and Lévy-stable intermittent fluctuations in stochastic systems of many autocatalytic elements. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[20]  Market Ecology, Pareto Wealth Distribution and Leptokurtic Returns in Microscopic Simulation of the LLS Stock Market Model , 2000, cond-mat/0005416.

[21]  Sorin Solomon,et al.  POWER LAWS ARE DISGUISED BOLTZMANN LAWS , 2001 .

[22]  Scale-invariant correlations in the biological and social sciences , 1998 .

[23]  M. Levy,et al.  POWER LAWS ARE LOGARITHMIC BOLTZMANN LAWS , 1996, adap-org/9607001.

[24]  Sergei Maslov,et al.  Price Fluctuations from the Order Book Perspective - Empirical Facts and a Simple Model , 2001, cond-mat/0102518.

[25]  Power, Lévy, exponential and Gaussian-like regimes in autocatalytic financial systems , 2000, cond-mat/0008026.

[26]  Moshe Levy,et al.  Generic emergence of power law distributions and Lévy-Stable intermittent fluctuations in discrete logistic systems , 1998, adap-org/9804001.

[27]  Demand Creation and Economic Growth , 1999 .

[28]  Rosario N. Mantegna,et al.  Book Review: An Introduction to Econophysics, Correlations, and Complexity in Finance, N. Rosario, H. Mantegna, and H. E. Stanley, Cambridge University Press, Cambridge, 2000. , 2000 .

[29]  D. Sornette,et al.  Convergent Multiplicative Processes Repelled from Zero: Power Laws and Truncated Power Laws , 1996, cond-mat/9609074.

[30]  Generalized Lotka-Volterra (GLV) Models and Generic Emergence of Scaling Laws in Stock Markets , 1999, cond-mat/9901250.

[31]  Ina Ruck,et al.  USA , 1969, The Lancet.

[32]  A. J. Lotka Elements of Physical Biology. , 1925, Nature.

[33]  W. Arthur,et al.  The Economy as an Evolving Complex System II , 1988 .

[34]  Sorin Solomon,et al.  Power laws in cities population, financial markets and internet sites (scaling in systems with a variable number of components) , 2000 .

[35]  H. Kesten Random difference equations and Renewal theory for products of random matrices , 1973 .

[36]  Moshe Levy,et al.  Microscopic Simulation of Financial Markets: From Investor Behavior to Market Phenomena , 2000 .

[37]  Stability of Pareto-Zipf Law in Non-Stationary Economies , 2000, cond-mat/0012479.

[38]  Sorin Solomon,et al.  Finite market size as a source of extreme wealth inequality and market instability , 2001 .