How Does Learning Affect Market Liquidity? A Simulation Analysis of a Double-Auction Financial Market with Portfolio Traders

We study the relationship between liquidity and prices in an artificial financial market where portfolio traders with limited resources interact through a continuous, electronic open book. We depart from the standard asset pricing framework in two ways. First, we assume that investors have imperfect information about the distribution of returns. In particular, we assume that agents hold arbitrary priors about the marginal distributions of assetsiquest; returns, while they share a common constant view of the securities association structure. Second, we use a prospect-type utility function to model the portfolio choice problem. Each investor has an initial level of wealth and a target growth rate to reach within his investment horizon. The investor must determine an asset allocation strategy so that the portfolio growth rate will be sufficient to reach the target. We model the utility function in terms of deviations from a specified target, and we assume that investors are more sensitive to downside movements. We show that the parameters defining the learning process affect the price dynamics through their impact on the variability of the market liquidity