Adaptive Markets and the New World Order (corrected May 2012)

Abstract

In the adaptive markets hypothesis (AMH) intelligent but fallible investors learn from and adapt to changing economic environments. This implies that markets are not always efficient but are usually competitive and adaptive, varying in their degree of efficiency as the environment and investor population change over time. The AMH has several implications, including the possibility of negative risk premiums, alpha converging to beta, and the importance of macro factors and risk budgeting in asset allocation policies.

The traditional investment paradigm consists of the following beliefs: (1) There is a positive trade-off between risk and reward across all financial investments—assets with higher risk offer higher expected return; (2) this trade-off is linear, risk is best measured by equity “beta,” and excess returns are measured by “alpha,” the average deviation of a portfolio’s return from the capital asset pricing model benchmark; (3) reasonably attractive investment returns may be achieved by passive, long-only, highly diversified market-cap-weighted portfolios of equities (i.e., those containing only equity betas and no alpha); (4) strategic asset allocation among asset classes is the most important decision that an investor makes in selecting a portfolio best suited to his risk tolerance and long-run investment objectives; and (5) all investors should be holding stocks for the long run. Collectively, these basic principles have become the foundation of the investment management industry, influencing virtually every product and service offered by professional portfolio managers, investment consultants, and financial advisers.

Underlying these beliefs are several key assumptions involving rational investors, stationary probability laws, and a positive linear relationship between risk and expected return with parameters that are constant over time and can be accurately estimated. These assumptions were plausible during the Great Modulation—the six decades spanning the 1940s to the early 2000s, when equity markets exhibited relatively stable risk and expected returns—but they have broken down over time owing to major changes in population, technological innovation, and global competition. As investors adapt to these changes, temporary but significant violations of rational pricing relationships may occur. This tension between rational and behavioral market conditions is captured by the adaptive markets hypothesis (AMH), an evolutionary perspective on market dynamics in which self-interested investors—who are intelligent but not infallible—learn from and adapt to changing environments. Under the AMH, markets are not always efficient, but they are usually highly competitive and adaptive, varying in their degree of efficiency as the economic environment and investor population change over time.

The AMH has several practical implications for financial analysis. First, the trade-off between risk and reward is not necessarily stable over time or circumstances but varies as a function of the population of market participants and the business environment in which they are immersed. During normal environments, the market reflects the “wisdom of crowds,” but during periods of excessive fear or greed, the market is driven more by the “madness of mobs” and the usual positive relationship between risk and reward need not hold. Second, market efficiency is not an all-or-nothing characteristic but is a continuum that spans the entire range between perfect efficiency and complete irrationality. Some markets are more efficient than others, and a market’s degree of efficiency can be measured and managed. Third, investors should be aware of changes in their economic environment and adapt their investment policies accordingly. A case in point is diversification, a worthy objective that is much harder to achieve under current market conditions than before; hence, new assets and techniques must be considered. Fourth, the traditional separation between unique investment performance, or “alpha,” and widely held commoditized risk premiums, or “beta,” is now more complex. Competition, innovation, and natural selection among investors and portfolio managers will turn alpha into either beta—in which case the risks associated with its exploitation are sufficient to limit the number of willing participants to a stable equilibrium—or zero as these unique opportunities are permanently eliminated. Finally, the traditional approach to asset allocation must be revised under the AMH to adapt to changing environments as well as investor behavior. During the Great Modulation, static portfolios, such as 60 percent equities and 40 percent bonds, may have performed reasonably well, but when the volatility of volatility becomes significant, fixed portfolio weights may not be ideal. A more productive alternative for long-term investments may be to construct portfolios according to risk allocations and to vary portfolio weights so as to keep risk levels stable. Such an approach earns positive risk premiums during normal markets just as traditional approaches do, but differs from them in two important respects during periods of market dislocation: Risk-denominated asset allocation strategies decrease market exposures during high-volatility periods, when risk premiums tend to be lower than usual, and stable risk levels reduce the likelihood of emotional overreactions when they are most likely to be triggered.