How do traders process and learn from market information, what trading strategies should they use, and how does learning affect the market? This paper proposes a learning model of an articial limit order market with asymmetric information to address these issues. Using a genetic algorithm as a...

The aim of this paper is to find the optimal level of position limit for the Chinese Stock Index (CSI) 300 futures market. A small position limit helps to prevent price manipulations in the spot market, thus able to keep the magnitude of instantaneous price changes within policy makers'...

What can traders learn and how does learning affect the market? When information is asymmetric, short-lived, and uninformed traders learn, we present an artificial limit order market model to examine the effect of learning, information value, and order aggressiveness on information dissemination...

This paper empirically assesses heterogeneous expectations in asset pricing. We use a maximum likelihood approach on S&P500 data to estimate a structural model. Our empirical results are consistent with a market populated with fundamentalists and chartists. In addition, agents switch between...

Following the framework of a one risky - one riskless asset model developed by Brock and Hommes (1998), this paper considers a discrete-time model of a financial market where heterogeneous groups of agents allocate their wealth amongst multiple risky assets and a riskless asset. Agents follow...

This article explores nonlinearities in the response of speculators’ trading activity to price changes in live cattle, corn, and lean hog futures markets. Analyzing weekly data from March 4, 1997 to December 27, 2005, we reject linearity in all of these markets. Using smooth transition...