An empirical behavioral order‑driven model with price limit rules

We propose an empirical behavioral order-driven(EBOD)model with price limit rules,which consists of an order placement process and an order cancellation process.All the ingredients of the model are determined based on the empirical microscopic regularities in the order flows of stocks traded on the Shenzhen Stock Exchange.The model can reproduce the main stylized facts in real markets.Computational experiments unveil that asymmetric setting of price limits will cause the stock price to diverge exponentially when the up price limit is higher than the down price limit and to vanish vice versa.We also find that asymmetric price limits have little influence on the correlation structure of the return series and the volatility series,but cause remarkable changes in the average returns and the tail exponents of returns.Our EBOD model provides a suitable computational experiment platform for academics,market participants,and policy makers.

HETEROGENEITY, NONLINEARITY AND ENDOGENOUS MARKET VOLATILITY

This paper aims to contribute to the literature on the explanatory power of behavior models with heterogeneous agents. The authors present a new nonlinear structural stock market model which is a nonlinear deterministic process buffeted by dynamic noise. An exogenous noise is introduced to the model with the assumption of IID normal innovations of the fundamental value in order to investigate how noisy dynamics interacts with deterministic process. The market is composed of two typical trader types： the rational fundamentalists and the boundedly rational traders governed by greed and fear. The interaction between noise and deterministic element determines the evolution process of the system as key parameters are changed. The authors find the model is able to generate time series that exhibit dynamical and statistical properties closely resembling those of the S＆：P500 index, such as volatility clustering, fat tails （leptokurtosis）, autocorrelation in square and absolute return, larger amplitude, crashes and bubbles. The authors also investigate the nonlinear dependence structure in our data. The results indicate that the GARCH-type model cannot completely account for all nonlinearity in our simulated market, which is thus consistent with the results from real markets. It seems that the nonlinear structural model is more powerful to give a satisfied explanation to market behavior than the traditional stochastic approach.

Heterogeneous Round-Trip Trading and the Emergence of Volatility Clustering in Speculation Game

This study is a detailed analysis of Speculation Game,a simple agent-based model of financial markets,in which the round-trip trading and the dynamic wealth evolution with variable trading volumes are implemented.Instead of herding behavior,the authors find that the heterogeneous holding periods in round-trip trades can contribute to the emergence of volatility clustering.In particular,the spontaneous redistribution of market wealth through repetitions of round-trip trades with non-uniform horizons can widen the wealth disparity and establish the Pareto distribution of the capital size.As a result,the intermittent placements of relatively big orders from endogenously emerged rich traders can bring on large fluctuations in price return.Empirical data are used to support the scenario derived from the model.