Revisiting Market Efficiency: The Stock Market As A Complex Adaptive System

Well‐functioning financial markets are key to efficient resource allocation in a capitalist economy. While many managers express reservations about the accuracy of stock prices, most academics and practitioners agree that markets are efficient by some reasonable operational criterion. But if standard capital markets theory provides reasonably good predictions under “normal” circumstances, researchers have also discovered a number of “anomalies”—cases where the empirical data appear sharply at odds with the theory. Most notable are the occasional bursts of extreme stock price volatility (including the recent boom‐and‐bust cycle in the NASDAQ) and the limited success of the Capital Asset Pricing Model in accounting for the actual risk‐return behavior of stocks. This article addresses the question of how the market's efficiency arises. The central message is that managers can better understand markets as a complex adaptive system. Such systems start with a “heterogeneous” group of investors, whose interaction leads to “self‐organization” into groups with different investment styles. In contrast to market efficiency, where “marginal” investors are all assumed to be rational and well‐informed, the interaction of investors with different “decision rules” in a complex adaptive system creates a market that has properties and characteristics distinct from the individuals it comprises. For example, simulations of the behavior of complex adaptive systems suggest that, in most cases, the collective market will prove to be smarter than the average investor. But, on occasion, herding behavior by investors leads to “imbalances”—and, hence, to events like the crash of '87 and the recent plunge in the NASDAQ. In addition to its grounding in more realistic assumptions about the behavior of individual investors, the new model of complex adaptive systems offers predictions that are in some respects more consistent with empirical findings. Most important, the new model accommodates larger‐than‐normal stock price volatility (in statistician's terms, “fat‐tailed” distributions of prices) far more readily than standard efficient market theory. And to the extent that it does a better job of explaining volatility, this new model of investor behavior is likely to have implications for two key areas of corporate financial practice: risk management and investor relations. But even so, the new model leaves one of the main premises of modern finance theory largely intact–that the most reliable basis for valuing a company's stock is its discounted cash flow.