Scaling and criticality in a stochastic multi-agent model of a financial market

Financial prices have been found to exhibit some universal characteristics that resemble the scaling laws characterizing physical systems in which large numbers of units interact. This raises the question of whether scaling in finance emerges in a similar way — from the interactions of a large ensemble of market participants. However, such an explanation is in contradiction to the prevalent ‘efficient market hypothesis’ in economics, which assumes that the movements of financial prices are an immediate and unbiased reflection of incoming news about future earning prospects. Within this hypothesis, scaling in price changes would simply reflect similar scaling in the ‘input’ signals that influence them. Here we describe a multi-agent model of financial markets which supports the idea that scaling arises from mutual interactions of participants. Although the ‘news arrival process’ in our model lacks both power-law scaling and any temporal dependence in volatility, we find that it generates such behaviour as a result of interactions between agents.

[1]  I. Schweiger Reply to "Chicago Banking: A Critical Review" , 1962 .

[2]  B. Mandelbrot The Variation of Certain Speculative Prices , 1963 .

[3]  E. Fama Mandelbrot and the Stable Paretian Hypothesis , 1963 .

[4]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[5]  L. Summers,et al.  The Noise Trader Approach to Finance , 1990 .

[6]  Spiegel,et al.  On-off intermittency: A mechanism for bursting. , 1993, Physical review letters.

[7]  R. Palmer,et al.  Artificial economic life: a simple model of a stockmarket , 1994 .

[8]  C. Peng,et al.  Mosaic organization of DNA nucleotides. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[9]  Platt,et al.  Characterization of on-off intermittency. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[10]  Stephen F. LeRoy,et al.  American Finance Association Efficient Capital Markets : A Review of Theory and Empirical Work , 1994 .

[11]  Moshe Levy,et al.  Microscopic Simulation of the Stock Market: the Effect of Microscopic Diversity , 1995 .

[12]  William A. Brock,et al.  Rational routes to randomness , 1995 .

[13]  Bernardo A. Huberman,et al.  Clustered volatility in multiagent dynamics , 1995, adap-org/9502006.

[14]  R. Mantegna,et al.  Scaling behaviour in the dynamics of an economic index , 1995, Nature.

[15]  J. Peinke,et al.  Turbulent cascades in foreign exchange markets , 1996, Nature.

[16]  Blake LeBaron,et al.  A Dynamic Structural Model for Stock Return Volatility and Trading Volume , 1995 .

[17]  Thomas Lux,et al.  Long-term stochastic dependence in financial prices: evidence from the German stock market , 1996 .

[18]  T. Lux Time variation of second moments from a noise trader/infection model , 1997 .

[19]  Guido Caldarelli,et al.  Scaling in currency exchange , 1997 .

[20]  M. Marsili,et al.  A Prototype Model of Stock Exchange , 1997, cond-mat/9709118.

[21]  M. Paczuski,et al.  Price Variations in a Stock Market with Many Agents , 1997 .

[22]  P. Cizeau,et al.  CORRELATIONS IN ECONOMIC TIME SERIES , 1997, cond-mat/9706021.

[23]  Olivier V. Pictet,et al.  From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets , 1997, Finance Stochastics.

[24]  William A. Brock,et al.  A rational route to randomness , 1997 .

[25]  P. Gopikrishnan,et al.  Inverse cubic law for the distribution of stock price variations , 1998, cond-mat/9803374.

[26]  T. Lux The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions , 1998 .