Based On The Main Body Of Market Maker Pricing Model Under Asymmetric Information

This essey introduces and evaluate a market-making algorithm for setting bid-ask quote with assymmetric information, and apply this algorithm into an agent-based computational economic model. Former studies on market maker clearly seperated into theoretical studies and empirical studies, which have little connections with each other. The main purpose of this essay is to bridge theoretical studies and empirical researches.This algorithm are derived from Glosten and Milgrom’s model. To compute bid-ask quote, our market maker maintains an probability density estimate of the true value of a stock. It updates its estimation after receiving market orders and derives its quote since then. This model is flexible enough to cooperate other functions, such as inventory control, profit incentive, competition for market-making and so forth.The algorithm is justified by an agent-based computational economic model. It shows that as the uncertainty towards the price increases, market maker would increase its bid-ask spread; the market maker with lower spread would win the competition against other market makers. Moreover, this algorithms also presents the same time series properties as real-world financial data, such as fat-tailed return distributions, volatility cluster, and so forth.