agent-based analysis of asset pricing under ambiguous information
In a representative agent model, the behavior of a social system is described in terms of a single aggregate decision maker. Such models are popular in economic and finance research, largely due to their analytic tractability, but fail to account for real-world agent heterogeneity. Agent-based simulation models naturally incorporate such heterogeneity, and we exploit this capability to investigate a recent model from the finance literature proposed by Epstein and Schneider (ES), and its ability to explain the classic equity premium puzzle in risky asset pricing. In addition to the ambiguity-averse trading strategy adopted by the representative agent in the ES model, we consider simple Bayesian strategies. Rather than impose a particular strategy profile, we employ an empirical game-theoretic approach to derive stable market compositions among the set of candidate strategies. For most market configurations that we examined, ambiguity-averse pricing was not present in equilibrium support. We do, however, find ambiguity-averse pricing in equilibrium support for a market configuration analogous to an illiquid asset. For none of the market configurations that we examined were we able to find significant equity premia. Both our use of strategic equilibrium as a market composition concept, and the actions of our simulated market microstructure contribute to removing any equity premium. These findings underscore the need to verify that results from abstract representative-agent models are supportable in a higher-fidelity model where heterogeneity and strategic interactions are taken into account.
equity premium empirical game theory agent-based finance