Agent-based modeling (ABM) is a computerized simulation of agents interacting through given rules. ABM is used in tracking diseases and simulating behavioral patterns among societies, but has not been as well developed with financial and economic issues. Now many economists are working together with physicists and computer scientists to create ABMs with the financial markets in focus. NASDAQ chief Mike Brown hired BiosGroup to develop an ABM for the stock market. But the US Securities and Exchange Commission (SEC) still do not use ABMs. SFI External Professor and computational social scientist Rob Axtell states, “When the SEC changes trading rules, it typically has either flimsy or modest support from econometric evidence for the action, or else no empirical evidence and the change is driven by ideology. You have to wonder why Mike Brown is doing this, while the SEC isn’t.” SFI External Professor John Geanakoplos, Farmer and colleagues have developed an ABM to explore how leverage affects fluctuations in stock prices. An ABM for the whole economy would take time and a lot of data of multidisciplinary collaborations of economists, psychologists, computer scientists, biologists and others. Axtell also says to this point, “Left to their own devices, academic macroeconomists will take a generation to make this transition. But if policy-makers demand better models, it can be accomplished more quickly.”