Agent based financial markets are simulation models of real financial markets, which are built from the bottom up by specifying simple behavioral rules of a plurality of agents. They can be used to analyze specific problems ( what would be the impact of an exogenpus shock) or to provide insights for more analitical models .
Agent based models are still an experimental frontier tool of research, and are not to be considered very reliable in actual empirical measuremets or forecasts. However, they represent a promising area of modelling, especially for financial markets. They are very flexible, and agent behavior can be modeled by a continuum of programs ranging from naive rules to complex genetic algorithms. Therefoe, they are well suited to incorporate assumptions such as overconfidence, irrational exuberance and other behavioral features of trading agents. A good , although not uptodate overview of these models; is provided by the attached paper by LaBaron (2001).
Sir, I am again thankful for your valuable comments and the attached paper. I am studying this paper and I will be looking forward for your kind guidance in future.
The paper of LaBaron (2001), you suggested, was really helpful to understand the artificial financial markets. It made me to understand design issues with respect to various aspects like agents, trading and time etc. LeBaron (2001) explained beautifully various challenges being faced by researchers in the field and made my belief stronger that this field has potential to research further.
I am trying to integrate various models of behavioural finance in an artificial financial market. In this regard, I would request to kindly guide me. I have made a brief research proposal. If you let me, can i share the same with your goodself for kind comments, please.
Looking forward for kind response from your side, please.