Consumption based asset pricing models with time-separable preferences can generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. We consider rational investors who entertain subjective prior beliefs about price behavior that are not...

The booms and busts in U.S. stock prices over the post-war period can to a large extent be explained by fluctuations in investors' subjective capital gains expectations. Survey measures of these expectations display excessive optimism at market peaks and excessive pessimism at market troughs....

Introducing bounded rationality into a standard consumption based asset pricing model with a representative agent and time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of...

We present a decision theoretic framework in which agents are learning about market behavior and that provides microfoundations for models of adaptive learning. Agents are 'internally rational', i.e., maximize discounted expected utility under uncertainty given dynamically consistent subjective...

We study a standard consumption based asset pricing model with rationally investing agents but allow agents' prior beliefs about price and dividend behavior to deviate slightly from rational expectations priors. Learning about stock price behavior then causes the model to become quantitatively...

We present a decision theoretic framework with agents that are learning about the behavior of market determined variables. Agents are 'internally rational', i.e., maximize discounted expected utility under uncertainty given consistent beliefs about the future, but may not be 'externally...

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that...

The evolution of boundedly rational rules for playing normal form games is studied within stationary environments of stochastically changing games. Rules are viewed as algorithms prescribing strategies for the different normal form games that arise. It is shown that many of the folk results of...

Recent research has highlighted the notion that people can make judgments and choices by means of two systems that are labeled here tacit (or intuitive) and deliberate (or analytic). Whereas most decisions typically involve both systems, this chapter examines the conditions under which each...

We formulate an evolutionary learning process in the spirit of Young (1993a) for games of incomplete information. The process involves trembles. For many games, if the amount of trembling is small, play will be in accordance with the games' (semi- strict) Bayesian equilibria most of the time....