ABSTRACT

Artificial stock markets are models of financial markets used to study and understand market dynamics. Agent Based Artificial Stock Markets can be seen as any market model in which prices are formed endogenously as a result of participants’ interaction and in which the representation of participants varies from simple equations of forecast functions to intricate software components endowed with human-like artificialintelligence based adaptive behavior. There are various artificial stock markets in existence that are created using different strategies and customized for specific requirements. Trading sessions may be call market sessions or continuous sessions. Call market(Discrete) sessions occur at predefined intervals of time whereas trading happens continuously in continuous sessions. In this paper, we make a study of five such artificial stock market models namely Santa Fe Artificial Stock Market (SF-ASM), Genoa Artificial Stock Market(GASM), Agent Based Model for Investment (ABMI), Business School (BS) and Baron’s Model (BM), all being call market or discrete time sessions. We analyze their features, design and their pros and cons based on a few important parameters.