Investor Limited Attention
and Asset Prices
Zhi Da
University of Notre Dame
西南财大-金融研究所
SWUFE - IFS
June 2012
Traditional Asset Pricing Models
assume that information is incorporated into prices with
lightning speed

2
Investors Attention and Finance
 Attention is a scarce cognitive resource (Kahneman, 1973)
 Limited-attention has important theoretical implications
for the trading and pricing of financial securities
“What information consumes is rather obvious: it consumes the
attention of its recipients. Hence, a wealth of information creates a
poverty of attention and a need to allocate that attention
efficiently among the overabundance of information sources that
might consume it.”
--- Herbert Simon
Nobel Laureate in Economics
3
Incomplete Literature Review
 Theoretical
 Empirical
 Measurement
4
Theoretical Analysis
5
Merton (1987, JF)
 Attention is costly and investors will not have
perfect information on all stocks at all time
 Investors include a stock to her portfolio only if she
knows the stock
 Thus they hold “suboptimal” portfolios
6
Merton (1987, JF)
 Expected return is higher when
 Beta is higher
 Idiosyncratic volatility is higher
 Firm is larger
 Shareholder base is smaller
7
Hirshleifer and Teoh (2003, JAE)
 There are both attentive and inattentive investors
in the economy
 They are both mean-variance optimizers
 They each set their optimal demand function
 Aggregate demand equals aggregate supply (0) 
equilibrium asset prices
8
Hirshleifer and Teoh (2003, JAE)
 Information structure and inattention
 Inattentive investors assume public information
signals to be drawn from simpler distributions
 Inattentive investors have simpler rules of thumb
for valuation parameters
9
Peng and Xiong (2006, JFE)
 A representative investor solves two optimization
problems each period:
10
1.
Optimally allocate her limited attention to (1) market
factor; (2) sector factors; (3) firm-specific factors
2.
Based on the processed information, she then solves
the standard consumption Bellman equation
Peng and Xiong (2006, JFE)
 Limited attention results in categorical learning
 Investors allocate more attention to market- and
sector-level factors than to firm-specific factors
 In severely constrained cases, the investor allocates all
attention to market- and sector-level information and
ignores all the firm-specific data
 Limited attention could acerbate the impact of
behavioral biases on asset prices
11
Empirical Evidence
12
Anecdotes
 Huberman and Regev (2001, JF)
 The publication of an article in the New York Times about a new
cancer-curing drug from EntreMed attracted great public
attention and generated a daily return of more than 300% in its
stocks, even though the same story had already been published
more than five months earlier in Nature and other newspapers.
 Rashes (2001, JF)
 Excessive co-movement in MCI–MCIC pair
13
Retail attention
 Barber and Odean (2008)
“… individual investors are more likely to buy rather than sell
those stocks that catch their attention. … this is so because
attention affects buying—where investors search across thousands
of stocks—more than selling—where investors generally choose
only from the few stocks that they own. While each investor does
not buy every single stock that grabs his attention, individual
investors are more likely to buy attention-grabbing stocks than to
sell them. (pg 786)”
Increased retail attention  positive price pressure
Preferences determine choices after attention has determined
the choice set
14
Time-varying attention constraint
 Corwin and Coughenour (2008, JF)
 NYSE specialists allocate effort toward their most active
stocks during periods of increased activity, resulting in less
frequent price improvement and increased transaction
costs for their remaining assigned stocks
 Hirshleifer, Lim, and Teoh (2009, JF)
 Investor distraction hypothesis: More post-earnings
announcement drift following days with more
announcements
 DellaVigna and Pollet (2009, JF)
 More post-earnings announcement drift following Friday
announcement
15
Limited attention to long-term information
 DellaVigna and Pollet (2007, AER)
 Demographic shocks today lead to predictable shifts in
consumption and industry profitability in 5 to 10 years
 Investors have limited attention to information beyond 5
years, resulting in return predictability
 Da and Warachka (2009, JFE)
 Equity analysts issue both short-term and long-term
earnings forecasts
 Market participants pay more attention to the short-term
forecasts than to the short-term forecasts
 Disparity in the forecasts predicts future return
16
Limited attention to economic links
 Cohen and Frazzini (2008)
Supplier’s
stock price
reacts to
shocks to its
customer
with a delay
17
 Cohen and Frazzini (2008)
18
Measurement
19
Measuring investor attention
 Measuring attention empirically is tricky
 Trading volume: Gervais, Kaniel, and Mingelgrin (2001); Barber
and Odean (2008); Hou, Peng, and Xiong (2008)
 Extreme returns: Barber and Odean (2008)
 Up/down markets: Hou, Peng, and Xiong (2008)
 Firms’ advertising expense: Grullon, Kanatas, and Weston (2004)
and Chemmanur and Yan (2009)
 The existence of news: Barber and Odean (2008)
 Repeated news stories: Tetlock (2008)
 Turnover and returns are noisy and “catch-all” proxies
and news coverage and advertising expense capture the
supply of attention or passive attention
20
Da, Engelberg, and Gao (2011, JF)
Google’s Search Volume Index (SVI)
21
Da, Engelberg, and Gao (2011, JF)
 Consider “AAPL” and “MSFT” (shown below)
 We focus on innovations in SVI of each search term
22
Da, Engelberg, and Gao (2011)
 We show that our attention measure is capturing retail
attention
 Intuitively it should be individual, retail investors
 Given we are dealing with retail attention, we consider
the Barber and Odean (2008) theory that shocks to
retail attention create positive price pressure
 An increase in retail attention predicts higher short-term return,
especially among smaller stocks and stocks traded more by retail
investors
 An increase in retail attention predicts higher first-day IPO
return and subsequent reversal (IPO long-run
underperformance)
23
SVI and CNBC’s Mad Money
1.12
1.1
1.08
1.06
1.04
1.02
1
0.98
0.96
mean SVI
median SVI
0.94
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
7
8
Jim Cramer makes recommendation
Engelberg, Sasseville and Williams (2008): it is mainly individual
investors whose attention the show is capturing
24
ASVI and Price Pressure
ASVI
Log Market Cap * ASVI
Log Market Cap
Percent Dash-5 Volume * ASVI
Percent Dash-5 Volume
APSVI
Absolute Abnormal Return
Advertising Expense / Sales
Log(1 + # of analysts)
Log(Chunky News Last Year)
Chunky News Dummy
Abnormal Turnover
Observations per week
R-Squared
Week 1
(1)
18.742***
(7.000)
-21.182***
(6.508)
2.653
(3.023)
3.552**
(1.639)
1.607
(1.644)
-2.532***
(0.930)
1.314
(1.879)
-4.012*
(2.237)
-3.747**
(1.548)
-5.157
(3.370)
3.610*
(2.025)
2.398**
(1.204)
Week 2
(2)
14.904**
(7.561)
-15.647**
(6.768)
3.858
(3.160)
1.904
(1.522)
1.351
(1.652)
-1.379
(0.990)
-2.389
(1.979)
-4.686**
(2.228)
-4.547***
(1.741)
-5.549*
(3.272)
1.378
(2.424)
2.309**
(1.144)
Week 3
(3)
3.850
(6.284)
-4.710
(6.516)
3.144
(3.063)
1.687
(1.612)
1.486
(1.659)
-0.701
(0.808)
-1.128
(1.563)
-3.959*
(2.172)
-3.961**
(1.769)
-4.349
(3.292)
-3.825
(2.483)
2.022
(1.404)
Week 4
(4)
-1.608
(6.903)
4.290
(6.398)
3.575
(3.186)
-2.744
(1.717)
0.364
(1.711)
-0.704
(0.639)
-0.463
(1.405)
-4.153*
(2.234)
-4.120**
(1.769)
-5.409
(3.558)
-0.058
(1.910)
0.316
(1.098)
Week 5-52
(5)
-28.912
(17.162)
16.834
(88.624)
-39.229
(67.405)
16.258
(23.822)
119.901***
(31.765)
2.286
(9.909)
-1.510
(28.505)
-162.210***
(52.414)
-173.875***
(29.683)
-14.999
(80.730)
32.466
(28.441)
10.531
(10.109)
1499
0.0142
1498
0.0119
1497
0.0112
1496
0.0111
1414
0.0170
First-day IPO Return
20.00%
18.00%
16.00%
Mean IPO First-day Return
16.98%
Median IPO First-day Return
14.00%
12.00%
12.00%
10.90%
10.00%
8.00%
6.07%
6.00%
4.00%
2.00%
0.00%
Low Pre-IPO ASVI
26
High Pre-IPO ASVI
Post-IPO Return [5w, 52w], High vs. Low ASVI
10.00%
7.55%
5.00%
1.39%
0.00%
-1.56%
-5.00%
-10.00%
-15.00%
Mean Size and B/M Portfolio Adj. Post-IPO Return
Median Size and B/M Portfolio Adj. Post-IPO Return
-20.00%
-19.51%
-25.00%
High First-day IPO Return, Low Pre-IPO ASVI
27
High First-day IPO Return, High Pre-IPO ASVI
Conclusion
 Investors are likely to have limited attention
 Limited investor attention affects prices both
theoretically and empirically
 Measuring attention is a challenging empirical task
28