Institutional architectures and behavioral ecologies in the dynamics of financial markets

Abstract The paper examines the properties of financial market dynamics, under different trading protocols. We start with an empirical analysis of the statistical properties of daily data from the world’s major Stock Exchanges, comparing the behavior of different market phases characterized by different trading protocols. The evidence lends support to the importance of investigating the outcome of alternative market mechanisms. Motivated by this finding, we present an agent-based model allowing the consistent treatment of agents’ behavior under three different trading set-ups, namely a Walrasian auction, a batch auction and an ‘order-book’ mechanism. The results highlight the importance of the institutional setting in shaping the dynamics of the market but also suggest that the latter can become the outcome of a complicated interaction between the trading protocol and the ecology of traders behaviors. In particular, we show that market architectures bear a central influence upon the time series properties of market dynamics. Conversely, the revealed allocative efficiency of different market settings is strongly influenced by the trading behavior of agents.

[1]  L. Marengo,et al.  Speculation, Heterogeneity and Learning: A Simulation Model of Exchange Rates Dynamics , 1996 .

[2]  V. Smith,et al.  Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets , 1988 .

[3]  Ananth N. Madhavan,et al.  Trading Mechanisms in Securities Markets , 1992 .

[4]  William A. Brock,et al.  Nonlinear Time Series, Complexity Theory, and Finance , 1995 .

[5]  Moshe Levy,et al.  Microscopic Simulation of Financial Markets , 2000 .

[6]  Willaiam A. Brock,et al.  Asset Price Behavior in Complex Environments , 1996 .

[7]  H. Stoll,et al.  Stock Market Structure and Volatility , 1990 .

[8]  Bruno Biais,et al.  Price Discovery and Learning during the Preopening Period in the Paris Bourse , 1999, Journal of Political Economy.

[9]  C. Plott,et al.  Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets , 1988 .

[10]  Y. Amihud,et al.  Trading Mechanisms and Stock Returns: An Empirical Investigation , 1987 .

[11]  Dhananjay K. Gode,et al.  What Makes Markets Allocationally Efficient , 1997 .

[12]  Blake LeBaron,et al.  Agent-based computational finance : Suggested readings and early research , 2000 .

[13]  M. Marchesi,et al.  VOLATILITY CLUSTERING IN FINANCIAL MARKETS: A MICROSIMULATION OF INTERACTING AGENTS , 2000 .

[14]  A. Lo,et al.  THE ECONOMETRICS OF FINANCIAL MARKETS , 1996, Macroeconomic Dynamics.

[15]  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.

[16]  Cees Withagen,et al.  Equilibrium, markets and dynamics : essays in honour of Claus Weddepohl , 2002 .

[17]  Cars H. Hommes,et al.  Financial markets as nonlinear adaptive evolutionary systems , 2001 .

[18]  Dhananjay K. Gode,et al.  Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality , 1993, Journal of Political Economy.

[19]  Charles Goodhart,et al.  Every minute counts in financial markets , 1991 .

[20]  W. Brock,et al.  Heterogeneous beliefs and routes to chaos in a simple asset pricing model , 1998 .

[21]  Lawrence Fisher,et al.  Some New Stock-Market Indexes , 1966 .

[22]  L. Summers,et al.  The Survival of Noise Traders in Financial Markets , 1988 .

[23]  K. Arrow.  Issues in Contemporary Economics , 1991 .

[24]  M. Marchesi,et al.  VOLATILITY CLUSTERING IN FINANCIAL MARKETS: A MICROSIMULATION OF INTERACTING AGENTS , 1998 .

[25]  D. Cliff,et al.  Zero is Not Enough: On The Lower Limit of Agent Intelligence For Continuous Double Auction Markets† , 1997 .

[26]  Annick Vignes,et al.  Price Dispersion: Theoretical Considerations and Empirical Evidence from the Marseilles Fish Market , 1991 .

[27]  R. Gencay,et al.  An Introduc-tion to High-Frequency Finance , 2001 .

[28]  T. Hens,et al.  An Application of Evolutionary Finance to Firms Listed in the Swiss Market Index , 2002 .

[29]  Takatoshi Ito,et al.  One Day in June, 1994: A Study of the Working of Reuters 2000-2 Electronic Foreign Exchange Trading System , 1995 .

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

[31]  Gilles Teyssière,et al.  Bubbles and long-range dependence in asset prices volatilities , 2002 .

[32]  R. Palmer,et al.  Asset Pricing Under Endogenous Expectations in an Artificial Stock Market , 1996 .

[33]  Jeffrey A. Frankel,et al.  The Microstructure of Foreign Exchange Markets , 1996 .

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