Journal Article

Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning

Allan Timmermann

in The Review of Economic Studies

Published on behalf of Review of Economic Studies Ltd

Volume 63, issue 4, pages 523-557
Published in print October 1996 | ISSN: 0034-6527
e-ISSN: 1467-937X | DOI: http://dx.doi.org/10.2307/2297792
Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning

Show Summary Details

Preview

To what extent can agents' learning and incomplete information about the “true” underlying model generating stock returns explain findings of excess volatility and predictability of returns in the stock market? In this paper we analyse two models of recursive learning in the stock market when dividends follow a (trend-)stationary autoregressive process. The asymptotic convergence properties of the models are characterized and we decompose the variation in stock prices into rational expectations and recursive learning components with different rates of convergence. A present-value learning rule is found to generate substantial excess volatility in stock prices even in very large samples, and also seems capable of explaining the positive correlation between stock returns and the lagged dividend yield. Self-referential learning, where agents' learning affect the law of motion of the process they are estimating, is shown to generate some additional volatility in stock prices, though of a magnitude much smaller than present value learning

Journal Article.  0 words. 

Subjects: Economics

Full text: subscription required

How to subscribe Recommend to my Librarian

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.