This article analyzes the effectiveness of proposed and actual securities, financial, and tax laws designed to prevent, or dampen the severity of asset price bubbles, including laws designed to mitigate excessive speculation. The article employs experimental asset market research to measure the effectiveness of these anti-bubble laws in correcting mispricings. Experimental asset markets represent complex simulations of stock markets in which subjects trade securities over a computer network. These markets allow scholars to test causal links between legal policies and market effects in ways that empirical research alone cannot. With these virtual markets, researchers can identify asset price bubbles-when prices of assets diverge from fundamental values-with a certainty that is beyond the capacity of empirical studies. The article places anti-bubble laws in the following template, which maps onto microeconomic (including behavioral finance) and macroeconomic research on bubble formation: (1) laws that aim to provide information to investors on fundamental value of assets: these laws require enhanced disclosure or investor education either to focus investor attention on information on fundamental value rather than noise or to remedy information asymmetries that lead to asset mispricing; (2) laws that attempt to short circuit positive feedback loops: these anti-bubble laws attempt to dampen the positive feedback created when investors chase rising asset prices and include transaction taxes, circuit breakers and laws that attempt to restrict access of investors to certain markets or channel less sophisticated investors to less risky assets; (3) removal of legal restrictions on arbitrage; and (4) laws that restrict credit to investors to curb speculation (e.g., margin regulations). Experimental (and empirical) evidence suggests the effectiveness of many laws in eliminating bubbles is weak. This article argues for greater use of experimental asset market research in corporate and securities law scholarship and provides a model for an analysis of the validity of experimental results.
