Implementing an agent based artificial stock market model in JADE - an illustration

5 Abstract— Agent-based approach to economic and financial analysis is a suitable research methodolgy for developing and understanding the complex patterns and phenomena that are observed in economic systems. In agent-based financial market models, prices can be endogenously formed by the system itself as the result of interaction of market participants. By using agents for the study, heterogeneous, boundedly rational, and adaptive behaviour of market participants can be analysed and its impact assessed. The collective behaviour of such groups is determined by the interaction of individual behaviours distributed across the group. This being the scenario prevailing in stock markets, agent based models are suitable for the study. Through this paper, we have attempted to illustrate a detailed implementation of multi agents in an artificial stock market invoking the agent-based methodology on Java Agent Development (JADE) environment, a platform to develop multi-agent systems. The Extended Glosten and Milgrom Model, an agent based artificial stock market model, has been chosen to depict the multi-agent environment model in JADE. Keyword-Agent based modelling, artificial stock market, investors, market makers, JADE, EGM Model I. INTRODUCTION Financial markets are complex entities and hence models are required to study the phenomena prevailing therein. Artificial Stock Markets (ASM) are models for studying the link between individual investor behavior and financial market dynamics. In agent based ASM, prices arise from simulating the interactions of autonomous entities with different profit-making strategies. ASM are often computational models of financial markets, and are usually comprised of a number of heterogeneous and boundedly rational agents. These models are built for the purpose of studying agents' behavior, price discovery mechanisms, the influence of market microstructure etc. A similar bottom-up approach has been utilized in agent-based computational economics (ACE) (1) to (5), which illustrates the distributed nature of trading in financial markets by computational study of economies modeled as evolving systems of autonomous interacting agents that correspond to the trading parties. A large number of agent-based stock market models have been proposed by researchers to study various aspects of the stock market behaviour (6) to (16). The Extended Glosten and Milgrom (EGM) model, a multi agent artificial stock market model proposed by Das (17), (18), the ASM proposed to be implemented in this paper, studies the information based market making strategy. The EGM model has been implemented on Java Agent Development (JADE), a framework suitable to develop multi-agent systems described in (19). Moreover, the behaviour of the traders is designed to be continuous and autonomous (22). Prior to delving into the ASM per se, a brief overview of the market microstructure is given in the next section, which would give a perspective of the intended work and also help clarify the setting of the ASM.