DC-ASM: DYNAMICALLY CONFIGURABLE ARTIFICIAL STOCK MARKET

Abstract

Computational advancements today have made modeling of some complex social systems like stock markets possible by providing conditions for controlled experiments. Such a control has proved helpful in exploring and studying dynamics of these complex markets, by isolating the cause and effect relationship of different phenomena in here. Extensive research in multi-agent simulation of financial markets has been carried out to study various market models. Much attention has not been paid to changing artificial market properties during the simulation, which is actually the real world scenario. We hypothesize that dynamically controllable simulating environment shall prove much more beneficial for more sophisticated and richer experimentation by the market specialists. This research contributes towards the artificial market paradigm by letting the financial scientists control simulated market properties at two levels. Macro level is controlled by enabling change in the composition of market participants during simulation. Micro level control describes defining a wide set of individual properties of participating agents that is made possible through Agent Construction Framework (ACF). This framework provides extensibility in defining new agent types with varying capabilities thus supporting wide range of heterogeneity in market participants. This research presents an extensible architecture for building such a dynamic controllable market that effectively imitates the real world. This extends the usability and effectiveness of agent-based simulating environments to new levels.