Rational Diverse Beliefs and Economic Volatility

This is a chapter in a new series of Handbooks in Financial Economics entitled “Dynamics and Evolution of Financial Markets.” It explores works which contribute to explaining market dynamics and volatility by employing models of rational but diverse beliefs. This excludes models of Behavioral Economics. We explore models that permit endogenous amplification which can, in turn, explain such basic facts as excess volatility and high risk premia. The first part gives an exposition of the Noisy Rational Expectations (i.e. REE) Asset Pricing Theory where diversity of beliefs arises from diverse private information. Examination of these models enable us to evaluate the assumptions made and the ability of the models to explain the data on market dynamics. Our conclusion is that, although Noisy REE asset pricing theories have many attractive features, they do not offer a satisfactory paradigm for market dynamics. Indeed, for most models increased amount of idiosyncratic private information leads to a reduction in volatility. We next turn to models of diverse beliefs without private information and explore work on Rational Belief Equilibria starting with modeling beliefs. Agents do not know the structure of the dynamically complex economy but have data over a long time to enable the computation of an empirical probability on sequences which is then commonly known. A belief is a model of deviations from the empirical probability. It is shown that in a wold of diverse beliefs, to be rational a belief must fluctuate, generating a mechanism of endogenous amplification of market dynamics. An important innovation of the theory is the treatment of individual beliefs as state variables and market belief is then derived as the distribution of individual beliefs. Market belief is observable via sampling data from several sources and we review both data sources as well as computations of the first two moments of market belief. We explore an illustrative model of asset pricing theory with diverse belief for which a closed form solution is available. This enables us to explain the central theoretical implications of the theory for market dynamics, the nature of uncertainty and risk premia. Next, we review the ability of the theory to explain via simulations the stylized facts known about market volatility. It is shown that the model’s predictions are compatible with the data. It is then argued that the results offer a unified explanation for key features of market dynamics such as excess asset price volatility, the Equity Premium Puzzle, the predictability of asset returns and stochastic volatility.