Depends on investors’ incomplete learning
Farmer and al. use a nonparametric approach to test for the presence of pockets with local predictability of stock market returns. They find evidence that stock returns are predictable more often than one would expect from a large class of asset pricing models. They attribute this presence of local return predictability to investors’ incomplete learning about future cash flow growth rates.
Pockets of Predictability
Authors: Leland E. Farmer, Lawrence Schmidt, Allan Timmermann
From: University of Virginia, University of Chicago, University of California, San Diego
…and the demographics of investors
Malmendier and al. use a stylized OLG equilibrium framework to study the effect of personal experiences on market dynamics. They find their model exhibits predictive power for future price changes. This return predictability, they argue, stems solely from the experience-based learning mechanism rather than a built-in dependence on dividends or past returns, and it depends on the demographic structure of the market.
Investor Experiences and Financial Market Dynamics
Authors: Ulrike Malmendier, Demian Pouzo, Victoria Vanasco
From: UC Berkeley, Stanford University
Which psychology-based model to use?
I have argued in this article that this approach has been fruitful. However, it is also unnecessarily narrow in scope: it focuses largely on the work of Daniel Kahneman and Amos Tversky – work that, while very influential, represents only a sliver of the field of psychology. Beyond the work on judgment and decision-making, there are large tracts of research in psychology on attention, memory, and emotion, not to mention a rapidly growing field known as decision neuroscience, that economists have not connected to very much.
Psychology-based Models of Asset Prices and Trading Volume
Author: Nicholas Barberis
From: Yale University
