1. IV. Conclusions Model analyzing based on kurtosis diagram and Hurst exponent diagram suggests that the percentage of momentum investors in Chinese stock market is between 33% and 44%, which is consistent with the empirical research reported by Pan et al [5]. This work shows an optional method to study the investors’ behavior in real stock market via agent-based model analyzing. References: [1] R. Cont, J.P. Bouchaud, Herd behavior and aggregate fluctuations in financial markets, Macroeconomic Dynamics 4,170(2000). [2] J.D. Farmer, Market force, ecology, and evolution, Santa Fe Inst. Working Paper 98-12-117. [3] Karin Dahmen and James P. Sethna, Phys. Rev. B 53, 14872–14905 (1996). [4] H. L. Chen, N. Jegadeesh, and R. Wermers, Journal of Financial and Quantitative Analysis 35(2000), 343-368. [5] D. Pan, D. H. Shi, and M. Cao, The Journal of World Economy 11(2003), 71-77 (in Chinese). How many momentum investors are there in stock market: Answer from agent-based model J. R. Wei and J. P. Huang Department of Physics, Fudan University, Shanghai, 200433, China The fact that many investors in stock market adopt momentum strategy has been widely accepted. To analyze the behavior of momentum investors, we build an agent-based model, in which agents are divided into random investors and investors who trade using momentum strategy with an action threshold. We tested our model by reproducing the well-known stylized facts of stock price return. Model analyzing gives the percentage of momentum investors in Chinese stock market, which is consistent with previous empirical research. This work suggests a method to study the momentum investors’ behavior in real stock market via agent-based model analyzing. I. Agent-based Model Hyp.1: Random investors ; Hyp.1: Random investors (N r ) ; Hyp.2: Price change is decided by excess demand: II. Result 1- Stylized facts The model is used to reproduce the well-known stylized facts in real market, such as fat-tail behavior(Fig.2), long-term correlation and scaling behavior of kurtosis(Fig.3). III. Result 2- momentum investors Sell Buy Decision-making Up Fig.2, PDF of return (  =15 rounds). σ ∝  ^0.58 Fit ： 1.1 -0.30 x Hyp.3: Momentum investors; Hyp.3: Momentum investors (N m ) ; Hyp.4: Action threshold λ(λ>0) for momentum investors; Situation at time t-1Action at time t D[t-1]/σ > λBuy a unit of stock D[t-1]/σ < -λSell a unit of stock  D[t-1]/σ  < λ remain inactive Market trend Table 1: How a momentum investor trade? σ=. Fig.1, Simulated price series ( N r =101, N m =30, λ =0.23, 100000 rounds). Fig.3, Left, long-term correlation,  versus  ; Right, scaling behavior of kurtosis, kurtosis versus . Fig.4 Contour of kurtosis in parameter space of N m /N r and λ (  =15 rounds). Fig.5 Contour of Hurst exponent in parameter space of N m /N r and λ (  =15 rounds). For monthly return, empirical study shows that kurtosis is larger than 5, and Hurst exponent is larger than 0.6. Therefore we can locate the available area in parameter space.