(Panel A) and the news sort (Panel C). When stocks are sorted on the previous day’s
return (Panel B), investors are relatively more likely to purchase stocks they already own
on days following large negative returns than on other days. However, following large
positive returns, buy–sell imbalances do not increase for stocks already owned. This is
consistent with previous research (Odean, 1998a) that finds that individual investors are
more likely to sell stocks trading above, rather than below, the original purchase price
and more likely to buy additional shares of stocks trading below, rather than above, the
original purchase price.
Short-sale constraints are relaxed in the presence of exchange-traded options. Thus, if
short-sale constraints alone drive our results, we would expect much different results for
stocks with exchange-traded options. In auxiliary analyses, we partition stocks into two
groups—those with and those without exchange-traded options.^20 For each group, we
sort stocks into deciles on the basis of abnormal trading volume and previous-day return
and calculate buy–sell imbalances for each decile (as described in Section 7.3). The
patterns of imbalances are very similar for stocks with and without exchange-traded
options—another indication that the results we document are not driven by short-sale
constraints.
Thus short-selling constraints (and heterogeneity of beliefs) do not fully explain our
findings. For individual investors who can sell a stock without selling short, a higher
percentage of their trades consists of purchases, rather than sales, on high-attention
days.
7.6 Asset pricing: Theory and evidence
In the appendix of the version of this chapter published inThe Review of Financial
Studies, we develop a model of price formation for a market in which attention-driven
noise traders tend to buy stocks that catch their attention. Our theoretical model has the
testable prediction that the underperformance of the stocks bought relative to stocks
sold by these noise traders will be greatest following periods of high attention. The
intuition underlying this result is straightforward; noise traders create uniform buying
pressure in attention-grabbing stocks, and market-makers respond to this buying press-
ure by increasing prices, leading to lower subsequent returns—the more intense the
attention-driven buying, the lower the subsequent returns. In this section, we test this
return prediction.
There are two significant challenges in testing our model. Our first challenge is that the
model does not specify the period of time over which attention-driven buying affects
returns. Our evidence that investors do buy stocks that catch their attention is based
upon 1-day sorts. It is likely, though, that investors’ attention often spans more than a
single day. How the effects on returns of attention-driven buying persist is likely to vary
with the intensity and duration of the attention-grabbing event. In the following anal-
ysis, we form portfolios on the basis of daily attention sorts and evaluate performance
over a 1-month horizon. We obtain similar results at other horizons.
Our second challenge is that many factors not incorporated into our simple model are
known to affect asset prices. Most relevant to our timeframe, stocks with high abnormal
trading volume over a day or a week tend to appreciate over the following month
The effect of attention and news on the buying behavior of individual and institutional investors 201(^20) With thanks to Charles Cao for providing us with a list of stocks with exchange-traded options.