Stock Market Volatility and Learning

Abstract

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 price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though we restrict consideration to learning schemes that imply only small deviations from full rationality. The findings are robust to the particular learning rule used and the value chosen for the single free parameter introduced by learning, provided agents forecast future stock prices using past information on prices.

Keywords: Asset pricing, learning, near-rational price forecasts

JEL Classification: G12, D84