This paper presents an adaptive learning model for market-making under the reinforcement learn-ing framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. No knowledge of the market environment, such as the order arrival or...

This paper analyzes conditions for existence of a strongly rational expectations equilibrium (SREE) in models with private information, where the amount of private information is endogenously determined. It is shown that the conditions for existence of a SREE known from models with exogenously...

The issue regarding the influence of intelligence on market efficiency has been discussed for a long time. Gode and Sunder (1993) mentioned that the aggregate behavior of zero-intelligence traders is able to generate an efficient market. They introduced two types of markets composed of...

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy....

This paper studies the behavior of price discovery within a context of an agent based stock market in which the twin assumptions namely, rational expectations and the representative agents normally made in mainstream economics, are removed. In this model, traders stochastically update their...

Recent research has shown a variety of computational techniques to describe evolution in an artificial stock market. One can distinguish the techniques based on at which level the learning of agents is modeled. The previous literature describes learning at either individual or social level. The...

This paper uses an agent based financial market calibrated to aggregate data. It shows how these markets are able to magnify the volatility of fundamentals, and to create time series with persistent volatility. The mechanism for this persistence is explored using several of the time series...