About $4 trillion in market wealth vanished between the April 2000 bursting of the Nasdaq bubble and its recent stabilization at lower levels. Could investors have seen it coming? Better yet, could financial regulators have picked up on subtle clues and acted beforehand to prevent the crash? Perhaps. Researchers have found an increased level of predictability in certain complex systems just before large changes. Such changes, they say, can be the result of information encoded within the system's global state.
Systems composed of so-called agents that compete for limited resources and whose strategies evolve span a range of disciplines, such as economics, evolution, traffic analysis and network design (in which the agents of interest are, respectively, traders, species, drivers, and data packets). Extreme events in such systems, such as punctuations in evolution's equilibria or traffic jams during rush hour, are important because they are drastic and because they shape the system for a long time afterward. Whereas some extreme events are triggered by random, isolated incidents (such as the stock market's steep decline after September 11), others arise from forces internal to the system.
This article was originally published with the title When Markets Go Mad.