PDF《regulatory policies*》

past performance. For instance, should the agents observe that fundamental analysis was unprofitable in the last trading periods, then at least some of them will stop using this strategy. As we will see in more detail later, such an agent-based financial market model may help us to comprehend the dynamics of financial markets. For instance, it reveals that nonlinear interactions between heterogeneous market participants may account for emergent phenomena such as bubbles and crashes, excess volatility and volatility clustering. Since agent-based models are quite powerful, it seems reasonable to use them as artificial laboratories and to carry out computer experiments with them to improve our insights into the working of certain regulatory mechanisms. Some benefits of such an approach are immediately clear. One may generate as much data as needed, control for

3 exogenous shocks, simulate special events such as a financial market crisis, measure all variables precisely and vary the policy maker'

s control parameter smoothly. We seek to demonstrate that this approach may at least be regarded as an alternative to traditio........