Da et al. (2011) - In Search of Attention
Main contributions of the paper:
1. Da et al. (2011) propose a new and direct measure of retail investor attention using search frequency
in Google (Search Volume Index)
2. Their measure is correlated with but different from existing attention proxies and captures investors’
attention in a more-timely fashion
3. They test and confirm the attention theory of Barber and Odean (2008)
4. Their proxy also contributes to explaining short-term and long-term patterns in IPO returns
Existing Attention Measures as Starting Point
Attention proxies: Barber and Odean (2008)
▪ Extreme one-day returns X
▪ Abnormal trading volume X
▪ News coverage X
▪ Advertising expense
▪ Upper price limits
They have weaknesses their implicit assumptions:
▪ Investors pay attention to extreme returns/turnover and to coverage in the news. However:
➢ Return and trading volume can be driven by factors unrelated to attention
➢ News result in attention only if they are read
The main attention measure: Abnormal Google Search Volume Index (ASVI) for ticker symbols
▪ SVI is a direct measure of retail investor attention
▪ In contrast to existing proxies it measures revealed attention and is weakly correlated with other
measures
▪ ASVI: ASVIt=log(SVIt) – log[Med(SVIt-1, … ,SVIt-8)]
▪ Weekly search volume index for individual stocks from Google Trends
▪ Identification of a stock via ticker:
− avoids problem of multiple reference names (less ambiguous)
− captures interest in financial information
▪ Two problems with names:
− Investors may search name for reasons unrelated to investing (e.g., Apple)
− Investors may search the same firm using variations of its name
▪ Noisy tickers (e.g., GPS = Gap, Inc.) flagged
▪ SVI based on the ticker
▪ SVI based on company name: Name_SVI
▪ SVI based on main product of company: PSVI (based on advertisements)
▪ Data downloaded using a web crawling program
▪ SVI measures investors’ attention continuously over the year while news coverage of a typical firm is sporadic
,▪ If search volume is triggered by news event, SVI carries additional information about the amount of
attention generated
SVI and Other Attention Measures
Empirical approach:
➢ Vector Autoregression (VAR) is used to measure the relationship between SVI and other attention
measures
Results:
➢ SVI leads other three attention proxies: positive coefficients suggest that SVI captures investor
attention in more timely fashion than turnover, extreme returns or news.
➢ Investors continue to pay attention to stocks after extreme returns
Whose attention does SVI capture? → SVI Captures Attention of Retail Investors
Empirical approach:
▪ Data of retail orders and trades per market center
➢ SEC Rule 11Ac1-5 (Dash-5) and Rule 605 requires every market center to report on a monthly basis
➢ Market centers attract different retail investors given their information level
▪ Dash-5 includes:
➢ # shares traded, # orders received, and various dimensions of execution quality
➢ Disaggregated trading statistics: (100-499); (500-1,999); (2,000-4,999); (5,000-9,999) shares
▪ Compute monthly changes in orders and turnover and relate them to monthly changes in SVI
▪ Control for alternative attention proxies and stock characteristics
Results:
Interpret panel A:
A 1% increase in SVI leads to a 0.0925% increase in individual orders and a 0.0919% increase in turnover
Results in regression (3) and (4) are similar to (1) and (2) → Pool data (Panel B)
,Interpret panel B:
Effect stronger at market system that most likely attracts order flow from less informed individual
investors (Madoff)
SVI and Price Pressure
ASVI is a direct measure of retail attention, we can directly test the price pressure hypothesis of Barber
and Odean (2008): Large ASVI results in increased buying pressure that pushes stock prices up
temporarily
They test it in the context of Russell 3000 stocks and then in the context of IPOs:
1. Finding on Russell 3000 stocks
- Strong evidence of positive price pressure following an increase in individual attention as
measured by ASVI
- a significant and negative coefficient on the interaction term between Log Market Cap and ASVI
➔ Effect of ASVI is stronger among small stocks because they are more influenced by individual
investors
- Positive coefficient of the interaction between ASVI and Percent Dash-5 Volume (which
measures retail investors’ trading) ➔ a stronger price increase among stocks traded mainly by
retail investors ➔ further confirm that the channel in which ASVI affects stock price is mainly
through retail investors
1.1. A rational explanation for the effect of ASVI on stock price:
Positive effect of ASVI on price could also simply reflect positive fundamental information about the
firm. For example, suppose a company announces an innovation in its product to which consumers react
positively ➔ ASVI increases
This alternative explanation implies that there could be another factor driving both ASVI and stock price
➔ potentially reject the effect of ASVI on price
, If this information story is true, we would expect an even larger positive coefficient on APSVI, which
subsumes the predictive power of ASVI when we include APSVI in the regression. ➔ not confirmed in
the regression that puts ASVI and APSVI together!
1.2. Test the long-term reversal
If ASVI drive prices through attention, this is irrational ➔ we should expect a long-term reversal
Test result: ASVI seems to be the only measure of attention that predicts both the initial price increase
and subsequent long-run price reversal ➔ confirm the prediction above!
2. Finding on IPO sample
Two stylized facts about IPO returns:
- IPOs on average have large first-day returns
- IPOs exhibit long-run underperformance
Hypothesis: Since it is usually difficult to short-sell IPOs, buying pressure from retail investors can
contribute to higher first-day returns
Methodology:
- measure retail attention prior to the IPO using ASVI
- there is no ticker widely known to the public prior to the IPO ➔ use company name provided by SDC
Results:
(1) There are significant changes in SVI around the time of the IPO:
- significant upward trend in SVI starting 2 to 3 weeks prior to the IPO week, followed by a
significant jump in SVI during the IPO week
- SVI reverts to its pre-IPO level 2 to 3 weeks after the IPO
Consistent with IPO returns pattern!
(2) Relation between increased attention prior to IPO and first-day IPO return:
- IPOs with low ASVI during the week prior to the IPO: return = 10.90%
- IPOs with high ASVI during the week prior to the IPO: return = 16.98%
- The difference is statistically significant at the 1% level
- Both formal tests (ASVI standalone and with controls) show significant positive effect of ASVI on
IPO first-day returns
Consistent with the attention-induced price pressure hypothesis
Explanation: Since it is usually difficult to short-sell IPOs, buying pressure from retail investors can
contribute to higher first-day returns.
Implication from this explanation: when the price pressure due to excess retail demand
disappear, stock prices eventually reverse ➔ long-run underperformance
3. Alternative Interpretation for ASVI and IPO returns:
Main contributions of the paper:
1. Da et al. (2011) propose a new and direct measure of retail investor attention using search frequency
in Google (Search Volume Index)
2. Their measure is correlated with but different from existing attention proxies and captures investors’
attention in a more-timely fashion
3. They test and confirm the attention theory of Barber and Odean (2008)
4. Their proxy also contributes to explaining short-term and long-term patterns in IPO returns
Existing Attention Measures as Starting Point
Attention proxies: Barber and Odean (2008)
▪ Extreme one-day returns X
▪ Abnormal trading volume X
▪ News coverage X
▪ Advertising expense
▪ Upper price limits
They have weaknesses their implicit assumptions:
▪ Investors pay attention to extreme returns/turnover and to coverage in the news. However:
➢ Return and trading volume can be driven by factors unrelated to attention
➢ News result in attention only if they are read
The main attention measure: Abnormal Google Search Volume Index (ASVI) for ticker symbols
▪ SVI is a direct measure of retail investor attention
▪ In contrast to existing proxies it measures revealed attention and is weakly correlated with other
measures
▪ ASVI: ASVIt=log(SVIt) – log[Med(SVIt-1, … ,SVIt-8)]
▪ Weekly search volume index for individual stocks from Google Trends
▪ Identification of a stock via ticker:
− avoids problem of multiple reference names (less ambiguous)
− captures interest in financial information
▪ Two problems with names:
− Investors may search name for reasons unrelated to investing (e.g., Apple)
− Investors may search the same firm using variations of its name
▪ Noisy tickers (e.g., GPS = Gap, Inc.) flagged
▪ SVI based on the ticker
▪ SVI based on company name: Name_SVI
▪ SVI based on main product of company: PSVI (based on advertisements)
▪ Data downloaded using a web crawling program
▪ SVI measures investors’ attention continuously over the year while news coverage of a typical firm is sporadic
,▪ If search volume is triggered by news event, SVI carries additional information about the amount of
attention generated
SVI and Other Attention Measures
Empirical approach:
➢ Vector Autoregression (VAR) is used to measure the relationship between SVI and other attention
measures
Results:
➢ SVI leads other three attention proxies: positive coefficients suggest that SVI captures investor
attention in more timely fashion than turnover, extreme returns or news.
➢ Investors continue to pay attention to stocks after extreme returns
Whose attention does SVI capture? → SVI Captures Attention of Retail Investors
Empirical approach:
▪ Data of retail orders and trades per market center
➢ SEC Rule 11Ac1-5 (Dash-5) and Rule 605 requires every market center to report on a monthly basis
➢ Market centers attract different retail investors given their information level
▪ Dash-5 includes:
➢ # shares traded, # orders received, and various dimensions of execution quality
➢ Disaggregated trading statistics: (100-499); (500-1,999); (2,000-4,999); (5,000-9,999) shares
▪ Compute monthly changes in orders and turnover and relate them to monthly changes in SVI
▪ Control for alternative attention proxies and stock characteristics
Results:
Interpret panel A:
A 1% increase in SVI leads to a 0.0925% increase in individual orders and a 0.0919% increase in turnover
Results in regression (3) and (4) are similar to (1) and (2) → Pool data (Panel B)
,Interpret panel B:
Effect stronger at market system that most likely attracts order flow from less informed individual
investors (Madoff)
SVI and Price Pressure
ASVI is a direct measure of retail attention, we can directly test the price pressure hypothesis of Barber
and Odean (2008): Large ASVI results in increased buying pressure that pushes stock prices up
temporarily
They test it in the context of Russell 3000 stocks and then in the context of IPOs:
1. Finding on Russell 3000 stocks
- Strong evidence of positive price pressure following an increase in individual attention as
measured by ASVI
- a significant and negative coefficient on the interaction term between Log Market Cap and ASVI
➔ Effect of ASVI is stronger among small stocks because they are more influenced by individual
investors
- Positive coefficient of the interaction between ASVI and Percent Dash-5 Volume (which
measures retail investors’ trading) ➔ a stronger price increase among stocks traded mainly by
retail investors ➔ further confirm that the channel in which ASVI affects stock price is mainly
through retail investors
1.1. A rational explanation for the effect of ASVI on stock price:
Positive effect of ASVI on price could also simply reflect positive fundamental information about the
firm. For example, suppose a company announces an innovation in its product to which consumers react
positively ➔ ASVI increases
This alternative explanation implies that there could be another factor driving both ASVI and stock price
➔ potentially reject the effect of ASVI on price
, If this information story is true, we would expect an even larger positive coefficient on APSVI, which
subsumes the predictive power of ASVI when we include APSVI in the regression. ➔ not confirmed in
the regression that puts ASVI and APSVI together!
1.2. Test the long-term reversal
If ASVI drive prices through attention, this is irrational ➔ we should expect a long-term reversal
Test result: ASVI seems to be the only measure of attention that predicts both the initial price increase
and subsequent long-run price reversal ➔ confirm the prediction above!
2. Finding on IPO sample
Two stylized facts about IPO returns:
- IPOs on average have large first-day returns
- IPOs exhibit long-run underperformance
Hypothesis: Since it is usually difficult to short-sell IPOs, buying pressure from retail investors can
contribute to higher first-day returns
Methodology:
- measure retail attention prior to the IPO using ASVI
- there is no ticker widely known to the public prior to the IPO ➔ use company name provided by SDC
Results:
(1) There are significant changes in SVI around the time of the IPO:
- significant upward trend in SVI starting 2 to 3 weeks prior to the IPO week, followed by a
significant jump in SVI during the IPO week
- SVI reverts to its pre-IPO level 2 to 3 weeks after the IPO
Consistent with IPO returns pattern!
(2) Relation between increased attention prior to IPO and first-day IPO return:
- IPOs with low ASVI during the week prior to the IPO: return = 10.90%
- IPOs with high ASVI during the week prior to the IPO: return = 16.98%
- The difference is statistically significant at the 1% level
- Both formal tests (ASVI standalone and with controls) show significant positive effect of ASVI on
IPO first-day returns
Consistent with the attention-induced price pressure hypothesis
Explanation: Since it is usually difficult to short-sell IPOs, buying pressure from retail investors can
contribute to higher first-day returns.
Implication from this explanation: when the price pressure due to excess retail demand
disappear, stock prices eventually reverse ➔ long-run underperformance
3. Alternative Interpretation for ASVI and IPO returns:
