Exploring Trading Dynamics in a Derivative Securities Market of Heterogeneous Agents

A fundamental question that arises in derivative research is why investors trade at a specified price. We developed a model that explicitly incorporates a motivation to trade into the mathematical model describing the investment problem. This motivation lies in investors' pre-existing liabilities. By showing the equivalence, via a duality argument, of portfolio optimization and derivatives pricing operator (measure) calibration, we are also able to explore (using the same model) derivative valuation by investors in light of their individual portfolio properties.

We developed a unified methodology for financial market simulation with emphasis on separation of market operations and agent decision support. This methodology served as a foundation for MAFiMSi, the Multi-Agent Financial Market Simulator, which allowed us to implement the first, to the best of our knowledge, multi-agent simulation of a derivatives market.

We conducted a simulation of a market populated with investors whose decision support was based on this microeconomic model, and observed various trading patterns depending on investors' individual properties. These experiments pave the way to making a broker strategic.

More generally, we showed that multi-agent simulation of a financial market provides a mechanism for conducting experiments that shed light on fundamental properties of the market. As all processes in financial markets (including decision making) become automated, it becomes crucial to have a mechanism by which we can observe the patterns that emerge from a variety of possible investor behaviors.



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