Avalanche Dynamics And Trading Friction Effects On Stock Market Returns

We propose a model with heterogeneous interacting traders which can explain some of the stylized facts of stock market returns. A generalized version of the Random Field Ising Model (RFIM) is introduced to describe trading behavior. Imitation effects, which induce agents to trade, can generate avalanches in trading volume and large gaps in demand and supply. A trade friction is introduced which, by responding to price movements, creates a feedback mechanism on future trading and generates volatility clustering.

[1]  Tang,et al.  Self-Organized Criticality: An Explanation of 1/f Noise , 2011 .

[2]  Real Sociedad Española de Física y Química.  Anales de fisica , 1968 .

[3]  André Orléan.  Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion , 1995 .

[4]  Nuno Crato,et al.  Long-range dependence in the conditional variance of stock returns , 1994 .

[5]  Robert F. Engle,et al.  ARCH: Selected Readings , 1995 .

[6]  M. Mézard,et al.  Spin Glass Theory and Beyond , 1987 .

[7]  R. Engle.  Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[8]  October I.  Physical Review Letters , 2022 .

[9]  Dietrich Stauffer,et al.  MONTE CARLO SIMULATION OF VOLATILITY CLUSTERING IN MARKET MODEL WITH HERDING , 1999 .

[10]  Dietrich Stauffer,et al.  A generalized spin model of financial markets , 1999 .

[11]  A. Banerjee,et al.  A Simple Model of Herd Behavior , 1992 .

[13]  C. Granger,et al.  A long memory property of stock market returns and a new model , 1993 .

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

[15]  Tim Bollerslev,et al.  The long memory of the forward premium , 1994 .

[16]  R. MacDonald,et al.  International Money and Finance, Second Edition , 1994 .

[17]  M. Ausloos,et al.  Low q-moment multifractal analysis of Gold price, Dow Jones Industrial Average and BGL-USD exchange rate , 1999 .

[18]  Dietrich Stauffer,et al.  FINITE-SIZE EFFECTS IN MONTE CARLO SIMULATIONS OF TWO STOCK MARKET MODELS , 1999 .

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

[20]  J. トービン.  流動性選好と金融政策〔Review of Economics and Statistics,May 1947掲載,全訳〕-1- , 1967 .

[21]  George Tauchen,et al.  THE PRICE VARIABILITY-VOLUME RELATIONSHIP ON SPECULATIVE MARKETS , 1983 .

[22]  E. Marinari,et al.  On the stability of the mean-field spin glass broken phase under non-Hamiltonian perturbations , 1997 .

[23]  S. Galam.  Rational group decision making: A random field Ising model at T = 0 , 1997, cond-mat/9702163.

[24]  Adrian Pagan,et al.  The econometrics of financial markets , 1996 .

[25]  Marcel Ausloos,et al.  Sparseness and roughness of foreign exchange rates , 1998 .

[26]  Shore,et al.  Hysteresis and hierarchies: Dynamics of disorder-driven first-order phase transformations. , 1992, Physical review letters.

[27]  Robert Fildes,et al.  Journal of business and economic statistics : Lutkepohl, Helmut, Forecasting vector ARMA processes with systematically missing observations, 4 1986, 375-390 , 1988 .

[28]  P. Cizeau,et al.  Volatility distribution in the S&P500 stock index , 1997, cond-mat/9708143.

[29]  M. Marchesi,et al.  Scaling and criticality in a stochastic multi-agent model of a financial market , 1999, Nature.

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

[31]  J. Cremer.  A generalization of spin glass theory in marketing: the coordination of interdependent country markets , 1997 .

[32]  Modeling the stock market prior to large crashes , 1998, cond-mat/9811066.

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

[34]  Heiko Rieger,et al.  A prognosis oriented microscopic stock market model , 1999 .

[35]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .