Asset Market Dynamics Of Heterogeneous Agent Models With Learning PDF Download

Financial market has been extensively recognized as a complex system, where large number of heterogeneous agents contribute to price formation of asset. Interactions and adaptations of these agents form the core foundation of market operations and its resultant characteristic properties. These market agents are highly diverse in their perception of the world around them and in the way they respond to it. Various studies of statistical properties of financial markets and price fluctuations have revealed a rich set of typical characteristics knows as stylized facts. Agent-based models that can reproduce these stylized facts and explain the roots of complex dynamics of financial market have been subject of intense research in recent time. The Minority Game Model proposed by Challet and Zhang is one such model that presents a simplified paradigm of financial market. Another model proposed by Lux and Marchesi offers a different perspective to agent-based modeling, where parallels are drawn between the physical system with a large number of interacting units and financial markets. The Minority Game model succeeds to a certain extent in reproducing stylized facts and explaining behavioral foundation of it. However, in attempt to present a simplified picture of market scenario both these models make certain assumptions that dilute the heterogeneity aspect of the real market. In real world markets, agents are truly diverse in their thinking, strategy, action and analyzing ability. Due to these unrealistic assumptions, the model can be validated only with a very limited spectrum of parameters. Also, it's difficult to point out precisely which aspects of the game contribute to some of the stylized facts producible with the model. To improve on these issues, we have developed a model and a simulator based on modified minority game, which we are referring to as "adapted minority game." The main focus of our research is on improving the heterogeneity aspect of agents, their interactions, and bringing fundamental value of asset into the Minority Game model. Our model introduces fundamentalist agents into the minority game model and also allows agents to have different historical memory and time horizons. Furthermore, agents are free to switch from one trading strategy group to another to improve their chances of performing better. Reproducing the stylized facts still remains the benchmark for validating our model. Our adapted minority game succeeds to an extent in expanding the spectrum of parameters that can be used for modeling the market. Agents' interactions and adaptations have been tracked down to the basis of stylized facts. An interesting property of periodic volatility is successfully demonstrated with our model.