Institutional counterparties and performance

Ozgur S. Ince* University of South Carolina Ozgur.Ince@moore.sc.edu

Gregory B. Kadlec Virginia Tech kadlec@vt.edu

February 2019

Abstract We examine the changing composition of counterparties to institutional trades (e.g., retail investors, firms, other institutions) and its relation to institutional trade performance over time. In contrast to conventional wisdom, the shrinking pool of retail investors appears to have had little impact on institutional performance. The decline in retail investors has been gradual whereas the only discernable change in institutional performance is a sharp permanent drop in 2000 -- there is no correlation between retail holdings and institutional performance. Rather, our evidence suggests that the sharp drop in 2000 may be a consequence of Regulation Fair Disclosure. We find that institutions appear to have lost their informational advantage over retail investors following Reg-FD (consistent with a “leveling of playing of the field”), and are at a greater disadvantage trading with firms following Reg-FD (consistent with a “chilling effect” on firm disclosure).

*We would like to acknowledge the helpful comments of Nikos Artavanis, Turan Bali, David Brown, Scott Cederburg, John Chalmers, Roger Edelen, Laura Fields, Sandy Klasa, Stephen McKeon, David McLean, Brad Paye, Xiaoli Tan, and seminar participants at the 2018 Western Finance Association Meetings in San Diego, UT Smokey Mountain Finance Conference, University of Arizona, Georgetown University, and University of Massachusetts Amherst.

I. Introduction

The literature on institutional investment management examines the role of investment

strategy, investor flows, manager connections, agency conflicts, and scale in the performance of

institutional investment portfolios.1 Our study considers a central yet largely overlooked factor

that is likely to be relevant to institutional investor performance – the counterparty to their trades.

Both theory and empirical evidence point to distinct informational roles for institutional investors,

retail investors, firms, and corporate insiders -- all of which are counterparties to institutional

trades. To the extent that the composition of these counterparties has changed over time, it could

have implications for their performance. For example, there is growing suspicion that institutional

holdings in U.S. stocks has reached the point where institutions are largely trading amongst

themselves, and thus, their average alpha is converging to zero. This suspicion is echoed in several

recent studies:2

“Some argue that mistakes by retail investors are a reliable source of trading gains

for other investors. If so, competition for these gains must be fierce later in the

sample as an expanding group of professional investors fights for a shrinking pool

of mistakes.” French (2008)

“If one adopts the view that individuals are naive investors while institutions are

rational arbitrageurs, these data would seem to suggest that we are converging to

a world in which the smart-money players trade intensively with one another, with

the dumb money playing a much-diminished role.” Stein (2009)

1 Studies examine the role of momentum (Carhart, 1997), liquidity (Aragon, 2007), turnover (Yan and Zhang, 2009), investor flow (Edelen, 1999; Coval and Stafford, 2007), industry concentration (Kacperczyk, Sialm, and Zheng, 2005), deviation from an index (Cremers and Petajisto, 2009), geographic proximity (Coval and Markowitz, 1999),), board connections (Cohen, Frazzini, and Malloy, 2008), and scale (Chen, Hong, Huang, and Kubik, 2004; Pastor, Stambaugh, and Taylor, 2015) on institutional portfolio performance. 2 This suspicion is also expressed in earlier studies emphasizing the “arithmetic of active management” [see e.g., Malkiel (1973), Sharpe (1991), and Bogle (2005)].

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“Active trading by one institution largely offsets active trading by other

institutions, implying that institutions mostly profit from (or lose to) each other, not

individuals.” Lewellen (2011)

We evaluate the degree to which this conventional wisdom is true by documenting the

composition of institutional counterparties to trades in U.S. stocks and their relation to

performance over the period 1980 through 20133. More specifically, we link changes in

institutional portfolio holdings to trades with four types of counterparties (retail investors, firms,

insiders, and other institutions) and track their performance.4 Consistent with conventional

wisdom we find that: (1) institutions have earned higher returns trading with retail investors

compared to other counterparties, (2) the proportion of institutional trades with retail investors

has declined over time, and (3) the performance of institutional trades has declined over time.5

However, in contrast to conventional wisdom we find that the decline in retail investors as

counterparties has little to do with the decline in institutional performance.

To see why the shrinking pool of retail investors is incapable of explaining the decline in

institutional performance we start with a back-of-the-envelope calculation using our univariate

evidence on changes in retail investors as counterparties. During 1980-1999 retail investors were

counterparty to 24% of institutional trades and this fell to 16% during 2000-2013. Not

surprisingly, the decrease in institutional trades with retail investors was largely offset by an

increase in institutional trades with other institutions. If we assume that institutions earn all of

their alpha from trades with retail investors and zero alpha from trades with other institutions, we

3 Wharton Research Data Services reports problems in Thomson Reuters institutional holdings data after June 2013 and advises against using data from subsequent quarters. 4 We use institutional holdings (SEC 13F), insider transactions (SEC Form 4), and net share issuance (CRSP) to infer the net supply/demand of shares by each investor type for each stock each quarter (see Section 2). 5Lewellen (2011), documents a similar decline in the performance of the aggregate equity holdings of institutional investors.

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would expect to observe a decrease in institutional trade performance of 33% [(.16-.24)/.24].6

Given the fact that investment performance is noisy one should not expect too much from this

back-of-the envelope calculation/prediction. However, we are comparing the average

performance of all institutions over two 14-year periods, so one would expect it to be in the

ballpark. But that is not the case. During 1980-1999 the stocks institutions bought outperformed

the stocks they sold by 1.5% annually and during 2000-2013 the stocks they bought

underperformed the stocks they sold by -2.6% annually. Thus, there appears to be more to the

decline in institutional performance than the shrinking pool of retail investors – particularly when

it comes to explaining the negative gross trade performance since 2000.

Our analysis of the volume and performance of institutional trades by counterparty yields

important insight into this matter. First and foremost, we find that the drop in institutional

performance stems more from a drop in the average performance of institutional trades with retail

investors than from a drop in the volume of trades with retail investors (i.e. size of the retail pool).

During 1980-1999, the average gross annual buy-minus sell abnormal return of institutional trades

with retail investors was 2.4% (t-stat=2.7) versus -0.5 (t-stat=-0.6) during 2000-2013. This,

suggests that institutional performance would have fallen irrespective of the decrease in the volume

of trades with retail investors.

One potential explanation for the drop in institutions’ average performance trading with

retail investors is the attrition of less skilled retail investors over time as in the adaptive markets

hypothesis of Lo (2004). Under this hypothesis, institutions trade with a smaller and more

sophisticated pool of retail investors over time. Our evidence rejects this selective attrition

6 For expositional purposes, we use the term alpha when we refer to institutions’ performance even though we employ abnormal buy-and-hold returns of portfolio holdings as opposed to factor models to measure performance.Wealsotypicallyomitthe“buy-minus-sell”adjectivewhendiscussingtradeperformance.

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explanation. First, we find that the performance of retail investors when trading against other

non-institutional counterparties (firms and insiders) has not improved over time – casting doubt

on the notion that the pool of retail investors has become more sophisticated. Second, we find that

the performance of institutions trading with firms (equity offerings and share repurchases), has

also declined over time, which points to a more general explanation for the decline in institutional

performance than one restricted to retail investors.

While our evidence suggests that the decline in institutional performance was not driven

by the shrinking pool of retail investors, the arithmetic of investment performance outlined in

Malkiel (1973), Sharpe (1991), and Bogle (2005) implies that it should have had some impact.

However, the relation is surprisingly hard to discern. The time-series of the decline in institutional

trade performance appears virtually unrelated to the time-series of the decline in retail holdings

(growth in institutional holdings). The decline in retail holdings (i.e., 1 – institutional holdings) is

fairly monotonic over the sample period [figure 1], whereas the decline in institutional trade

performance is marked by a precipitous, and what appears to be a permanent drop in 2000 [figure

4]. More formally, the correlation between institutional trade performance and lagged changes in

institutional ownership is indistinguishable from zero for a wide array of measurement intervals.

Thus, while the growth of institutional holdings must ultimately come at the expense of their

aggregate performance, the link is not as obvious as one would expect, nor does it appear to be

capable of accounting for the sharp drop in performance in 2000.

It is difficult to pinpoint structural breaks in time series as noisy as investment performance.

However, maximum likelihood tests reveal that the breakpoints with the greatest statistical

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significance were the four quarters of 2000 with p-values ranging between 0.4% and 1.9%.7 We

consider three possible explanations for a structural shift in institutional trade performance in or

around the year 2000 – the dotcom crash, Regulation Fair Disclosure (Reg FD), and decimalization

of stock prices.

The dotcom crash began in March of 2000 and was associated with the somewhat rare

occurrence of large net outflows from institutional equity portfolios. We consider the possibility

that these outflows caused institutions to engage in fire sales [as in Coval and Stafford (2007)].

While the outflows likely had a negative impact on performance, we conclude that they are

unlikely to have caused the structural shift in 2000. First, the timing does not line up. The net

flows of equity portfolios did not become negative until late 2001, so the brunt of the fire sales

would have come at least a year after the initial drop in institutional performance. Moreover, we

find that the drop in performance occurred primarily in diversified (rather than narrowly focused)

portfolios, which are less vulnerable to fire sales. Finally, fire sales cannot account for why

institutional performance has remained persistently poor for the entire post-2000 period.

Regulation Fair Disclosure (Reg-FD) requires firms to disclose material information to all

investors at the same time and became effective in October of 2000. Studies provide evidence that

Reg FD reduced institutional investors’ privileged access to information.8 Our evidence suggests

Reg FD may have played a key role in the structural shift in institutional performance. As

previously noted, institutions earned an average annual buy-minus-sell abnormal return of 2.4%

(t-stat = 2.7) on trades with retail investors prior to Reg FD (i.e., 2000) versus -0.5% (t-stat = -0.6)

7 Given this non-stationarity in the performance of institutional trades before and after 2000, we split our sample into two sub-periods 1980-1999 and 2000-2013 for much of our analysis. 8 For additional evidence on Reg FD, see Bailey, Mao, and Zhong (2003), Bushee, Matsumoto, and Miller (2004), Chiyachantana, Jiang, Taechapiroontong, and Wood (2004), Eleswarapu, Thompson, and Venkataraman (2004), Ke, Petroni, and Yu (2008), and Cohen, Frazzini, and Malloy (2010).

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after Reg-FD. We also find that institutions’ performance trading against firms fell after Reg FD.

These two findings are consistent with Agrawal (2006) et al. and Duarte (2008) et al. who argue

that Reg FD “leveled the playing field” between institutional and individual investors by increasing

the quantity of information available to the public but had a “chilling effect” on the overall flow

of information from firms. As a more direct test, we examine the performance of institutional

trades around earnings announcements, which was a primary focus of Reg FD. We find the same

two effects in the context of earnings announcements, a decrease in informational advantage of

institutions over retail investors and an increase in informational advantage of firms over

institutional investors following Reg FD.9

Finally, we consider the possibility that the post-2000 drop in institutional performance

was a consequence of increased market efficiency associated with the switch to decimal pricing in

Nasdaq and NYSE listed stocks during late 2000 and early 2001. It appears that decimalization

reduced bid-ask spreads and improved short-horizon information assimilation as evident from

lower short-horizon serial correlation in stock returns [Boehmer and Kelley (2009), Chordia, Roll,

and Subrahmanyam (2011)]. However, evidence regarding other measures of transaction costs

such as price impact and longer-horizon mispricing such as characteristic-based predictability, is

less clear [Israel and Moskowitz (2013)]. Our findings regarding the role of decimalization in

institutional trade performance are also mixed. The decrease in institutions’ performance against

retail investors after 2000 is consistent with improved market efficiency but the decrease in

institutions performance against firms after 2000 seems inconsistent with improved market

efficiency.

9Baker, Litov Watcher and Wurgler (2010) document a similar decline in the performance of mutual funds’ trades surrounding earnings announcements following Reg-FD.

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A puzzling observation regarding the decline in institutional trade performance is that the

gross buy-minus-sell performance differential of institutional trades has been significantly

negative after 2000. An explanation for persistent underperformance would appear to require an

appeal to either manager irrationality or agency conflict, but our evidence points to a simpler

explanation. A substantial portion of the negative performance of institutional trades in the post-

2000 period can be accounted for by increased losses on trades with firms during this period.

Moreover, when we partition institutions into those with active versus passive strategies [as

classified by Bushee (2001)], we find that the significantly negative performance is confined to

passive institutions. Thus, the propensity of institutions to engage in underperforming trades with

firms could be due to the nondiscretionary mechanical acquisition (sale) of equity offerings

(repurchases) by passive indexers.

The remainder of our paper proceeds as follows. Section II introduces our data and

methodology. Section III provides statistics regarding the growth of institutional ownership and

composition of institutional counterparties over the period 1980-2013. Section IV examines the

relation between institutional counterparties and institutional trade performance. Section V

provides tests of alternative hypotheses regarding the decline in institutional performance. Section

VI concludes.

II. Data and Methodology

Our sample includes 626,576 quarterly stock-level observations compiled from the

holdings of 6,914 institutions in 18,991 U.S. listed stocks over the period 1980-2013. We stop at

the end of June 2013 due to errors in 13F holdings reported by Thomson Reuters after that date.

Quarterly data on institutional holdings is from 13F filings compiled by Thomson Reuters. Data

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regarding company insider transactions are from SEC Form 4 filings compiled by Thomson

Reuters. Data on monthly stock returns, total shares outstanding, share price, and delisting returns

are from CRSP monthly returns files. Finally, we use book value of equity from Compustat in

computing firms’ book-to-market ratios.

For each stock each quarter we link changes in the institutional portfolio holdings to trades

with four types of counterparties: other institutions, firms (equity offerings and repurchases),

corporate insiders, and the residual, which we loosely refer to as “retail investors”. 10 The residual

is a plug variable that balances the supply and demand of shares traded that is not attributable to

institutions, firms, or insiders so that the following condition is satisfied:11

Institutional demand + Insider demand + Firm demand + Residual demand = 0.

Institutional investor and corporate insider transactions are obtained directly from SEC filings

compiled by Thomson Reuters. We track firm demand as the negative of the net change in split-

adjusted shares outstanding during the quarter, which is a comprehensive measure of firms’ total

issuance and repurchase activity (see e.g., Stephens and Weisbach, 1998, Fama and French, 2008,

Pontiff and Woodgate, 2008, and Greenwood and Hanson, 2012). A positive value for this variable

indicates a contraction of shares outstanding as a result of repurchase activity and a negative value

indicates an increase in shares outstanding as a result of stock issuance. 12

10 Studies commonly attribute 1-%13F holdings to retail investors. See, e.g., Sias and Starks (1997), Nofsinger and Sias (1999), Dennis and Strickland (2002), Hotchkiss and Strickland (2003), Boehmer and Kelley (2009), Field and Lowry (2009), Ramalingegowda and Yu (2012), Ang, Shtauber, Tetlock (2013), Conrad, Kapadia, Xing (2013). 11 Note that, our assignment of counterparties does not imply that the two parties traded directly with each other in all cases, but it does reflect the net supply and demand of the two parties during the quarter. 12 We note that shares can be issued through a variety of mechanisms such as seasoned equity offerings, executive compensation, mergers, and convertible debt. Fama and French (2005) find that mergers constitute the largest component of share issuance. We do not distinguish between these various forms of issuance as our focus is on the aggregate demand for the shares by each of the four counterparties.

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We attribute the residual demand or supply of shares to “retail investors” with the caveat

that the coverage of institutional holdings in 13F filings is incomplete, and thus, 1 – %13F holdings

includes some amount of institutional holdings. First, institutions with assets less than $100

million are not required to file 13F. In the Appendix, we estimate that the number of these

institutions is large, however they typically account for less than 1% of total institutional holdings.

Second, many foreign institutions (most notably sovereign funds) fail to comply with 13F filing

requirements. Using data from the annual Treasury International Capital (TIC) survey of foreign

holdings of U.S. securities, we estimate that foreign investors held approximately 22.5% of U.S.

public equity in 2013 whereas 13F filings report foreign holdings of only 7.8% at that point in time

(see Appendix for details).13 These discrepancies suggest caution when interpreting the residual as

strictly “retail investors” in that some of the residual are non-reporting institutional investors,

especially towards the end of our sample period.

Finally, while our approach to inferring institutional trades from changes in quarterly

portfolio holdings is common in the literature, it has its limitations. First, we do not observe trades

that occur strictly within a given quarter. Edelen Evans, and Kadlec (2006) and Chakrabarty,

Moulton, and Trzcinka (2017) suggest that these cases are relatively rare accounting for roughly

10% of all trades. Nevertheless, Pucket and Yan (2000) find that institutions tend to earn higher

returns on intra-quarter trades than inter-quarter trades, and thus, estimates of gross trade

performance from changes in quarterly holdings may be downward biased. Second, the portfolio

holdings data from 13F filings does not include short positions. As a result, our estimates of

13 Institutional investors operating outside the U.S. are not exempt from 13F filing requirements. However, their compliance has been spotty, especially for sovereign funds. See, for example, “Regulating Sovereign Investments”, hearing before the S. Comm. on Banking, House, and Urban Affairs, 110th Cong. (2008), statement of Ethiopis Tafara, Director, Office of International Affairs, U.S. Securities and Exchange Commission.

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institutional trading activity do not include trades associated with entering or closing short

positions. And as with the case of inter-quarter trades, to the extent that these trades are more

profitable for institutions, trades inferred from changes in quarterly holdings will tend to understate

overall trade performance. With the possible exception of hedge funds, which tend to trade more

frequently and engage in short positions, we do not believe that these limitations bias our

inferences in a material way.

III. The composition of counterparties to institutions over time

We begin our analysis with an overview of the supply and demand of shares by various

counterparties as determined by the above allocations. Table 1 reports the quarterly demand for

shares (typically institutions and retail investors) and supply of shares (typically firms and insiders)

for the average stock by the various counterparties over the sample period. By construction, the

columns sum to zero to reflect the requirement that supply equals demand. From Table 1, the

growth in shares outstanding has remained fairly constant over time at roughly 1% of total shares

outstanding per quarter. Retail investor demand for new shares has declined from 0.61% per

quarter during 1980-1999 to 0.16% during 2000-2013 while institutional demand for new shares

has increased from 0.58% during 1980-1999 to 0.98% during 2000-2013.

The decreasing demand by retail investors documented in Table 1 implies that the role of

institutional investors as a counterparty to firm issuance/repurchases and insider transactions has

grown over time.14 While this increase role of institutions as counterparty to these informed parties

14 Sias and Whidbee (2010) are perhaps the first to note/examine the role of institutions as counterparties to insider transactions.

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is a mechanical consequence of the growth of institutional ownership, it is nevertheless noteworthy

in light of the well-documented negative relation between long-term stock returns and supply of

shares from firms (see, e.g., Loughran and Ritter, 1995; Spiess and Affleck-Graves, 1995;

Ikenberry et al., 1995) and from insiders (Jaffe, 1974; Seyhun, 1986). There is, however, mixed

evidence regarding the performance of institutional investors as counterparties to firm

issuance/repurchases (see e.g. Alti and Suleaman, 2012; DeLisle, Morscheck, and Nofsinger,

2014; Edelen, Ince, and Kadlec, 2018). We investigate the performance consequences of this

change in counterparty composition in the next section.

The arithmetic of investment performance as outlined in Malkiel (1973), Sharpe (1991),

and Bogle (2005) implies that the growth of institutional holdings must come at the expense of

their aggregate performance. Whether institutional holdings have reached the point where their

aggregate gross alpha is close to zero is an empirical question that we seek to answer. Figure 1

charts institutional holdings of U.S. stocks over the sample period, which serves as a graphical

account of the cumulative net demand by institutions of Table 1. The bold line depicts total

institutional holdings from 13F filings. With the exception of a few deviations following the

crashes of 1987, 2001, and 2008, institutional ownership has been on a fairly constant upward

trajectory over the sample period. Institutions held 34% of US stocks in 1980, 46% in 1990, 58%

in 2000 and 70% in 2013 based on SEC 13F filings.

The dashed line in Figure 1 depicts institutional holdings from 13F filings plus an estimate

of the holdings of foreign institutions that fail to file 13Fs. The estimate uses data from the annual

Treasury International Capital (TIC) survey of foreign holdings of U.S. securities, conducted

jointly by the U.S. Treasury Department, the Federal Reserve Bank of New York, and the Board

of Governors of the Federal Reserve System (see Appendix for details). Assuming that the bulk

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of foreign holdings are managed by institutions, 13F data understates institutional holdings of US

equities by roughly 5% during early part of the sample period and by as much as 15% during the

latter part of the sample period. According to these estimates, institutions held 40% of US stocks

in 1980, 53% in 1990, 63% in 2000 and 85% in 2013. By either count (13F or TIC), institutions

now dominate the market for U.S. equity as noted in a number of studies.

While the fraction of shares held by institutional investors is suggestive, the alpha potential

of institutional investors ultimately depends on the extent to which they trade among themselves

versus with other counterparties. Figure 2 documents the propensity of institutions to trade with

other institutions over the sample period. For each stock, we take the smaller of the number of

shares bought or sold by institutions during a given quarter and divide it by the greater of the

number of shares bought or sold by institutions on the other side of the trade. Figure 2 plots the

four-quarter value-weighted moving average of this measure of inter-institutional trading. During

the period 1980-1999, 69% of institutional trades were crossed with other institutions, as compared

to 77% during 2000-2013. This confirms that institutions are largely trading amongst themselves,

however, that has been the case for most of the sample period. One would not expect the increase

of 8% from 1980-1999 to 2000-2013 to have a material impact on their performance.

The notion that institutions’ aggregate gross alpha converges to zero as their holdings

approaches 100% [see e.g., Malkiel (1973), Sharpe (1991), and Bogle (2005)] is based on the

implicit assumption that the net institutional demand (supply) for shares is met by supply (demand)

from retail investors. However, this is not the case. The stock market is an open system with firms

issuing and repurchasing shares on a regular basis, and thus, serving as important counterparties

to institutional investors. Figure 3 charts the counterparties to institutions’ aggregate net change

in holdings (i.e. trades not crossed with other institutions) over the sample period. Specifically,

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we plot the four-quarter value-weighted moving average of the percent net change in institutional

holdings attributable to retail investors, firms, and insiders. Figure 3 shows that retail investors’

share of institutions’ net trading volume has declined from 81% in 1980 to 62% in 2013. The void

left by the migration of retail investors from the market has been filled by an increasing propensity

to trade with firms, whose share of institutions’ net trading volume increased from 17% to 36%

and insiders (from 0% to 5%).15 Given the informational advantage of firms and insiders over other

investors, the increasing role of these counterparties is likely to have a further detrimental impact

on institutional performance beyond that of the increase in the zero-sum inter-institutional trading

documented in Figure 2. We investigate this possibility in the next section.

IV. Institutional Trade Performance

In this section we examine the performance of institutional trades over time. We begin with

their unconditional performance and then consider their performance against each counterparty.

Each quarter we sort stocks into institutional demand quintiles, where institutional demand is

calculated as the change in number of split-adjusted shares held by institutional investors during

the quarter divided by the beginning-of-quarter total shares outstanding. We determine quintile

cutoffs separately within each market capitalization decile (using NYSE cutoffs) to ensure that

small capitalization stocks are not overrepresented. Stocks in the highest demand quintile are

placed in the "Buy" portfolio and stocks in the lowest demand quintile are placed in the "Sell"

portfolio. We then compute average size and book-to-market matched buy and hold abnormal

15A counterparty’s share of institutional trades is constrained between zero (if the counterparty did not trade any shares of the stock during the quarter or traded on the same side as institutions) and one (if the counterparty traded at least as many shares as institutions on the opposite side). As a result, the values in Figure 3 do not necessarily sum to 100%.

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returns during the subsequent four quarters.16 The t-statistics are based on time-series standard

errors adjusted for serial correlation using the Newey-West procedure with a four-quarter lag.

A. Unconditional Institutional Performance

Figure 4 documents the unconditional performance of institutional trades over the sample

period 1980-2013. Specifically, we chart an 8-quarter moving average of the abnormal return

differential of institutional buy and sell trades. Figure 4A reports equal-weighted abnormal returns

and Figure 4B reports value-weighted abnormal returns. During the period 1980–1999,

institutions generally earned positive gross abnormal buy-minus-sell return differential on their

trades. The equal-weighted annual abnormal return differential of institutional buy versus sell

trades was 3.3% with 86% of the quarters having positive returns and the value-weighted annual

abnormal return differential was 1.47% with 56% of the quarters having positive returns. As noted

in Lewellen (2011), institutional portfolio performance has been poor since 2000. Our trade-based

evidence confirms this. The equal-weighted annual abnormal return differential of institutional

buy versus sell trades during 2000-2013 was -3.71% with 9% of the quarters having positive

returns and the value-weighted annual abnormal return differential was -2.61% with 19% of the

quarters having positive returns. An important insight from our study is that the gradual decline in

10-year rolling average performance of institutional holdings documented in Lewellen (2011) is

revealed to be due to a sudden and permanent shock to the performance of institutional trades

around 2000 (see Figure 4).

16 We examine returns over an annual horizon rather than a quarterly horizon to minimize potential price-pressure effects from correlated institutional demand. An annual horizon is also closer to the average holding period of the typical institutional investor. Results using a quarterly return horizon are very similar.

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The time-series plots of Figures 1 and 4 raise questions regarding the relation between the

growth in institutional holdings, which has been fairly constant over time, and institutional trade

performance, which is marked by a precipitous drop in 2000. To more formally assess this relation,

we estimate the time-series correlation between changes in aggregate institutional ownership and

future institutional trade performance over various measurement intervals for changes in

institutional ownership and future returns ranging from quarterly to annual. Consistent with the

lack of a visual relation between these two time-series, the correlation is insignificantly different

from zero for all intervals considered. We also conduct a formal maximum likelihood structural

break analysis to determine if and when a statistically significant structural break in institutional

performance occurred during the sampler period (1980-2013).17 The analysis reveals that the four

quarters of 2000 were the most likely break points during the sample period with p-values ranging

between 0.4% and 1.9%.18 Thus, for much of our analysis we partition the sample into two sub-

periods (1980-1999 and 2000-2013) surrounding this structural break. We investigate potential

reasons for this structural break in Section V.

Table 2 provides a more detailed account of the performance of institutional trades over

time by reporting the performance of stocks bought by institutions and sold by institutions

separately. In Table 2 and all subsequent tables, we value-weight abnormal returns to capture the

economic significance of trends in aggregate institutional performance. In addition, we partition

stocks into large-cap (top 20% in market capitalization using NYSE cutoffs), mid-cap (next 30%),

17 We use the SAS SSM procedure to fit a multivariate state space model using maximum likelihood. Estimation results are available upon request. 18 It is common for observations neighboring the true breakpoint to exhibit significant change-point statistics, when the underlying series is noisy. Therefore, we do not attempt to determine the precise quarter during 2000 in which the structural break occurred.

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and small-cap (bottom 50%) to capture potential differences in institutional performance across

stocks of different size.

From Table 2, the drop in performance from 1980-1999 to 2000-2013 is evident for all

three market capitalizations. Abnormal returns of institutional trades fell by 3.19% (t-stat=-2.1)

for large-caps, 5.24% (t-stat=-3.9) for mid-caps, and 8.16% (t-stat=-5.5) for small-caps across the

two sub-periods. Consistent with the evidence in Lewellen (2011), institutions’ aggregate trade

performance prior to 2000 was indistinguishable from that of the market for large capitalization

stocks but significantly positive for small capitalization stocks.

B. Performance with Counterparties

In this section we document the performance of institutional trades with each counterparty

over the sample period. Each quarter we sort stocks into quintiles based on the change in number

of shares held by each of the three counterparties to institutions (firms, insiders, and the residual)

during the quarter divided by the beginning-of-quarter total shares outstanding. Stocks in the

highest demand quintile are placed in the "Buy" portfolio and stocks in the lowest demand quintile

are placed in the "Sell" portfolio of each counterparty. We then calculate the value-weighted

abnormal return during the subsequent four quarters of the institutional buy-minus-sell portfolio

against each counterparty (i.e., institutional buy and counterparty sell minus institutional sell and

counterparty buy). To ensure that the conditional performance is not contaminated by correlated

trading between counterparties, we exclude high and low demand stocks that appear in another

counterparty’s high and low demand portfolios. Keeping these correlated trades in the portfolios

yields similar results.

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Table 3 reports the average performance of institutional trades with retail investors.

Consistent with the conventional wisdom regarding the relative informedness of institutional and

retail investors, institutions earned significant positive abnormal returns trading with retail

investors over the period 1980-1999, with a value-weighted average annual abnormal return of

2.38% (t-stat = 2.66). By contrast, institutions’ average performance trading with retail investors

over the period 2000-2013 was -0.52% (t-stat = -0.56), a statistically significant drop of 2.9% (t-

stat = -2.73).

The decline in institutions’ performance against retail investors may be due to factors

related to institutional investors, retail investors, or more general market conditions. One way to

shed light on this issue is to examine the performance of institutions in their trades with other

counterparties (i.e. firms and insiders). Table 4 reports the average performance of institutional

trades with firms and insiders. From Table 4, institutions’ performance in trades with firms also

deteriorated over the period 2000-2013 for all but large stocks, similar to the decline in their

performance against retail investors. More specifically, institutions’ performance trading with

firms dropped by -8.93% (t-stat=-2.48) for midcap stocks and -8.29% (t-stat=-3.10) small stocks.

Institutions’ performance trading with insiders also declined (by -5.55%), but the drop was

statistically significant only for mid-cap stocks.

The intuition behind the arithmetic of investing outlined in Malkiel (1973), Sharpe (1991),

and Bogle (2005) is that the growth in institutional ownership implies a shrinking pool of retail

investors from which to garner alpha [e.g., French (2008), Stein (2009), and Lewellen (2011)].

However, our evidence suggests that the decline in institutional trade performance over the period

1980-2013 has more to do with factors not accounted for by this arithmetic: (1) the decline in the

17

average performance in trades with retail investors and firms, and (2) the increased propensity to

engage in losing trades with firms.

It is possible that the poor performance of the least skilled retail investors led them to

delegate their investments to institutional money managers as in the adaptive markets hypothesis

of Lo (2004). If this is the case, not only are institutions trading with a smaller pool of retail

investors over time, they are trading with a more sophisticated pool of retail investors over time.

Our evidence to this point is inconsistent with the adaptive markets explanation on two counts.

First, the drop in institutions’ trade performance was sudden (structural shift in 2000), whereas the

decline in retail holdings was gradual. Second, institutions’ performance in trades with both retail

investors and firms dropped, pointing to a more general explanation than one based on retail

investors alone.

We provide further insight into this selective attrition hypothesis by examining the

performance of trades of retail investors with other non-institutional counterparties (i.e. firms and

insiders). To the extent that retail investors have become more sophisticated through attrition, one

should observe their performance against other counterparties to improve over time (just as it did

trading against institutions). In Table 5, we find that is not the case. Retail investors’ performance

against firms and insiders does not exhibit a statistically significant improvement over time, in

either the full sample or any of the market capitalization categories. Thus, collectively our evidence

rejects the adaptive markets selective attrition hypothesis.

18

V. The Structural Shift in Institutional Performance

In this section we consider three possible explanations for a structural shift in institutional

trade performance during 2000 – the dotcom crash, Regulation Fair Disclosure (Reg FD), and

decimalization.

A. The Dotcom Crash

The dotcom crash began in March of 2000 and continued through October of 2002. The

crash was marked by the somewhat rare occurrence of large net outflows from institutional equity

portfolios (Figure 5). Coval and Stafford (2007) study the implications of widespread mutual fund

selling in response to large net outflows (so-called “fire sales”). They find evidence of negative

performance for stocks held by funds experiencing systematic outflows. It is likely that similar

widespread selling occurred in response to the outflows following the dotcom crash, and thus, it is

plausible that the drop in institutional trade performance was a consequence of institutions selling

securities at depressed prices.

While dotcom related outflows are likely to have had a negative impact on institutional

trade performance, they are unlikely to have caused the sharp drop in performance observed in

2000. The timing of the outflows and drop in performance do not line up. The net flows of funds

to institutional equity managers was positive in 2000 and 2001 and did not turn substantially

negative until late 2002 and early 2003. Thus, the brunt of such fire sales would appear to have

come after the drop in performance. Moreover, from Table 8 we find that the drop in performance

occurred primarily in diversified (rather than narrowly focused) portfolios, which are less

vulnerable to fire sales. Finally, under the redemption/firesale argument one would expect the

19

drop in institutional trade performance to be temporary, but that is not the case, the poor

performance persisted for the entire post-2000 period.

The dotcom crash was also associated with a decrease in the direct holdings of equity by

retail investors. According to The Federal Reserve Board’s Survey of Consumer Finances for

2013, the percentage of U.S. households that own stocks directly dropped sharply following the

dotcom crash, from 21% in 2001 to 14% in 2013. This reduction in retail investors as

counterparties might have had a more permanent effect on institutions’ ability to generate alpha.

However, as with the outflows of institutional portfolios, the decline in direct holdings of retail

investors [the mirror image of institutional holdings in Figure 1] did not occur until after the drop

in institutional performance. And again, the drop in institutional performance stemmed more from

a drop in the average performance of institutional trades with retail investors and firms than from

a drop in the volume of trade with retail investors. This latter fact is more consistent with a shock

to the information environment (e.g., Reg-FD) or market efficiency (e.g., decimalization) than a

gradual change in the composition of market participants.

B. Regulation Fair Disclosure (Reg FD)

Regulation Fair Disclosure (Reg FD), which became effective on October 23, 2000,

mandates that publicly traded companies disclose material information to all investors at the same

time. A primary objective of Reg FD was to level the informational playing field between

institutional and retail investors. Several studies document that trading activity and return

volatility prior to corporate disclosures changed following Reg FD in a manner that is consistent

20

with a reduction in the informational advantage of institutional investors.19 Likewise, Cohen,

Frazzini, and Malloy (2010) document a reduction in the informational advantage of stock analysts

following Reg FD. However, there may be some unintended consequence of Reg FD in that some

firms have reduced their disclosure of information — a so called “chilling effect” [Agrawal (2006)

et al and Duarte (2008)].

The timing of Reg FD appears to line up well with the structural break in institutional

performance in 2000 and our evidence regarding the performance of institutional trades is

consistent with both the “level playing field” and “chilling effect” of Reg FD. As previously

discussed, Table 3 documents that the average performance of institutional trades with retail

investors fell after 2000. Tables 6 and 7 provide more direct evidence regarding the impact of Reg

FD on institutions’ informational advantage by documenting the performance of institutional

trades around earnings announcements, which was a specific point of emphasis for Reg FD. Table

6 shows that institutions’ trades with retail investors have earned lower abnormal returns around

earnings announcements following Reg FD. From Table 6, before Reg FD institutions earned a

statistically significantly positive average daily market-adjusted return of 5 bps (t-stat=2.65)

during the three days surrounding the four subsequent earnings announcements versus an

insignificant 4 bps (t-stat=1.25) following Reg FD. Moreover, the decline is greatest for small cap

stocks, which are likely to exhibit the greatest information asymmetry, with a decline from 10 bps

(t-stat=4.80) to 1 bps (t-stat=0.44), a difference of -9 bps (t-stat=-2.80). Thus, our earnings

announcement evidence also points to a reduced informational advantage for institutions over

retail investors.

19See e.g., Bailey, Mao, Zhong (2003), Bushee, Matsumoto, and Miller (2004), Chiyachantana, Jiang, Taechapiroontong, and Wood (2004), Eleswarapu, Thompson, and Venkataraman (2004) and Ke, Petroni, and Yu (2008).

21

The “chilling effect” argument suggests that in complying with Reg FD, some firms may

choose to not release as much information. If so, one would expect institutions to be at a greater

informational disadvantage to firms following Reg FD, which seems to be the case [in Table 4].

To further investigate this potential chilling effect, we replicate the analysis of Table 6 for

institutional trades with firms and insiders surrounding earnings announcements. Prior to 2000,

institutions earned an average daily market-adjusted return of 5 bps (t-stat=0.79) in mid-cap stocks

and -3 bps (t-stat=-0.84) in small stocks when trading against firms, versus -22 bps (t-stat=-3.91)

in mid-cap stocks and -31 bps (t-stat=-4.40) in small stocks following 2000. Thus, firms appear to

have a greater informational advantage over institutions after Reg FD. By extension one might

expect to observe a similar decline in institutions’ performance against insiders. However, from

Panel B of table 6, this is not the case. Perhaps this is because insider trading laws are an effective

deterrent for insiders taking advantage of their information asymmetry in their personal accounts,

but do not prevent insiders from using their informational advantage via firms’ issuance and

repurchase decisions.

C. Decimalization of Equity Prices

Barras, Scaillet, and Wermers (2010) suggest that the growth of the fund industry may have

coincided with greater levels of stock market efficiency rendering stock-picking more difficult. A

significant market event that is believed to have led to an improvement in market efficiency was

the conversion of U.S. equity markets to decimal pricing in February (NYSE/ASE) and April

(Nasdaq) of 2001. It appears that decimalization reduced bid-ask spreads and improved short-

horizon information assimilation as evident from lower short-horizon serial correlation in stock

returns [Boehmer and Kelley (2009), Chordia, Roll, and Subrahmanyam (2011)]. However,

evidence regarding other measures of transaction costs such as price impact and longer-horizon

22

mispricing such as characteristic-based predictability, is less clear [Israel and Moskowitz (2013)].

Our findings regarding the role of decimalization in institutional trade performance are also mixed.

The decrease in institutions’ performance against retail investors after 2000 is consistent with

improved market efficiency but the decrease in institutions performance against firms after 2000

seems inconsistent with improved market efficiency.

D. Further insights into the decline in performance

Our evidence suggests that the decline in institutional trade performance over the period

1980-2013 has more to do with changes in institutions’ informational advantage over retail

investors (Reg FD) than with the availability of retail investors as counterparties. In this section

we examine other potential factors behind institutions declining performance against retail

investors and firms.

D.1 The composition of “retail investors”

It is possible that the incidence of non-reporting 13F institutions, which end up in the

residual (i.e., “retail investors”), has increased over time. To the extent that these institutions

outperform retail investors, this would give the appearance of an improvement in retail investor

performance over time. The Appendix provides a detailed analysis of non-reporting by domestic

and foreign institutions. We estimate that domestic institutions that fall below the 13F reporting

requirement are trivial. In aggregate, they comprise less than 3% of institutional assets in 1980

and have been declining ever since due to the fact that the reporting threshold ($100 million) has

remained the same over time. However, the incidence of non-reporting foreign institutions in the

residual has become a material issue over time, due to the growth in foreign holdings of U.S. stocks

23

and the decreasing compliance of foreign institutions in filing 13Fs following the crash of 2008.

We estimate that non-reporting foreign institutions hold 5% of the total value of the U.S. stock

market (8% of the residual) in 1980, 6% of the market (13% of the residual) in 2000, and 16% of

the market (54% of the residual) in 2013. If we assume that the performance of these institutions

is comparable to those that file 13F, the performance of institutional trades against the residual

would decline over time, though this effect would not be particularly severe until 2008 and it could

not account for the negative performance of institutions after 2000.

D.2 The negative performance of the post-2000 era

A final fact that we highlight regarding the decline in institutional trade performance is that

it is much greater than what one would expect from the decline in retail investors. In particular,

the gross abnormal return of institutional trades during the entire post-2000 period is negative. An

explanation for persistently negative gross performance would appear to require some appeal to

either manager irrationality or agency conflict, but our evidence points to a simpler explanation.

The standard analysis of institutional trading attributes one minus the percent shares held by

institutions to retail investors. This approach ignores trades with a particularly large and well-

informed counterparty -- firms via equity offerings and repurchases. As shown in figure 2 there

has been a substantial increase institutional trades with firms over the sample period and these

trades tend to be negative performance propositions.

So, we are left with the question of why institutional investors increasingly engage in losing

trades with firms. Institutions are not a homogeneous group, it is possible that different types of

institutional investors are impacted by shocks to the information environment (Reg FD) and market

efficiency (decimalization) to varying degrees based on the extent to which they trade against

informed counterparties. To investigate this possibility we partition institutions into three

24

investment style categories based on Bushee's (2001) classification of: i) transient (diversified

portfolios with high turnover), ii) quasi-indexers (diversified portfolios with low turnover), and iii)

dedicated (concentrated portfolios with low turnover). Table 8 reports institutional trade

performance for institutions partitioned into these three groups.

From Table 8, transient institutions earned positive abnormal returns during the period

1980-1999, 2.96% (t-stat=2.4), but their outperformance disappears post-2000. This is consistent

with a loss of informational advantage (Reg FD). By contrast, quasi-indexers earned insignificant

abnormal returns during 1980-1990, and significantly negative abnormal returns post-2000, -

4.34% (t-stat=-3.0). The negative performance is consistent with passive institutions’ greater

propensity to participate in trades with firms and earning lower returns on these trades than active

institutions. This mechanical acquisition (or sale) of shares despite the fact that they are likely

overvalued (undervalued) is a common criticism of passive indexing [Arnott et al. (2005), Treynor

(2005)]. The underperformance of passive institutions’ trades with firms may also be a partial

explanation for Edelen, Ince, and Kadlec (2015) finding that institutional investors tend to take the

wrong side of anomaly-based trades -- it may be driven by passive institutions’ trades with firms.

Finally, from Table 8, dedicated institutions earned insignificant abnormal returns during both the

1980-1999 and 2000-2013 sub-periods.

VI. Conclusion

A number of studies examine the implications of the growth of institutional ownership for

asset pricing and market efficiency [e.g., Del Guercio (1996), Gompers and Metrick (2001),

Barberis and Shleifer (2003), Stein (2009), Lewellen (2010)]. Our study examines the implications

of the growth in institutional ownership for their aggregate return performance. Contrary to

25

conventional wisdom, we find little evidence of a link between aggregate institutional ownership

and aggregate institutional return performance. While the arithmetic of investing necessitates such

a link, it is undetectable and inconsequential against a backdrop of the structural shift in

institutional performance that occurred in 2000.

With regard to the structural shift in 2000, our evidence suggests that institutional

investors’ ability to earn positive abnormal returns trading in U.S. equities was greatly diminished

by their loss of privileged access to information due to Reg-FD. Their performance has further

declined through their increased losses in trades with firms, which also appears to be a consequence

of Reg-FD.

Pastor and Stambaugh and Taylor (2015) document a negative relation between industry

scale and performance in the mutual fund industry and raise questions regarding the source of the

diseconomies. While the arithmetic of investment implies that industry growth must reduce the

aggregate returns of institutional investors, it is not the primary factor in the decline in institutional

performance that we document.

A final note regarding the interpretation of our results. In contrast to Lewellen (2011) who

examines the performance of the aggregate holdings of institutions, our study examines the

performance of the aggregate trades of institutions. Thus, his study speaks to the performance of

institutions’ cumulative trades, whereas our study speaks to the performance of institutions’ recent

trades. The former has advantages in its comprehensive assessment of performance, our approach

has advantages in its ability to detect changes in the performance of their trades. Nevertheless, the

two analyses, while related, are not directly comparable, and have somewhat different

interpretations.

26

Appendix

When interpreting the results regarding so-called “retail investors” it is important to keep

in mind that the residual is a plug category for ownership not classified as other institutions, firms,

and insiders. It contains omissions in 13F filings from both non-reporting domestic institutions

and non-reporting foreign institutions. We evaluate the incidence of non-reporting domestic

institutions by extrapolating the left-hand tail of the size distribution of 13F filing institutional

investors, which is left-censored below the $100 million reporting cutoff. We systematically

evaluate the fit of a variety of distributions using the uncensored data and find the lognormal

distribution to be the best fit. We can then compute the unconditional mean of the fitted distribution

each quarter between 1980-2013 and estimate the percentage of total institutional holdings

censored below $100 million by comparing the unconditional mean to the observed condition

mean. In untabulated results, we find that institutions that fall below the 13F reporting requirement

are trivial. In aggregate, we estimated that these institutions’ share of total institutional holdings

fell from around 2.5% in 1980 to 0.5% in 2013.

In contrast, the foreign component of the residual is increasing and economically

meaningful. We use data from the annual Treasury International Capital (TIC) survey of foreign

holdings of U.S. securities, conducted jointly by the U.S. Treasury Department, the Federal

Reserve Bank of New York, and the Board of Governors of the Federal Reserve System.

Importantly, these surveys provide a much more complete coverage of foreign holdings of US

equity compared to the SEC 13F filings by foreign entities for two reasons: First, the annual survey

captures holdings of all foreigners while SEC 13F filings apply only to foreign institutions above

a certain size. Second, and more importantly, compliance is much better for the annual surveys,

which are conducted under the authority of the International Investment and Trade in Services

27

Survey Act (22 U.S.C. 3101 et seq.) with mandatory reporting requirements and significant

penalties for failure to report. In contrast, the SEC lacks an effective enforcement mechanism

against foreign entities (see, e.g., Regulating Sovereign Investments, Hearing Before the S. Comm.

on Banking, Hous., and Urban Affairs, 110th Cong. (2008, statement of Ethiopis Tafara, Director,

Office of International Affairs, U.S. Securities and Exchange Commission).

Figure 1 shows that SEC 13F filings substantially understate the true foreign ownership of

US equities. For example, as of 2013, TIC data implies that foreigners owned 22.5% of the US

public equity market while non-US institutions held only 6.1% of the market according to 13F

filings. By construction, the difference is captured in the residual category, even though the

majority of the foreign holdings are likely to be managed by institutions as opposed to foreign

retail investors.

28

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Figure 1. Institutional ownership over timeThis chart depicts the percentage of the U.S. public equity market held by 13F filinginstitutional investors (solid line) andtotal institutional ownership including non-13F-filingforeign investors (dotted line). We estimate the holdings of non-filing foreign institutionsusing data from the Treasury International Capital (TIC) survey as described in theAppendix.

0%10%20%30%40%50%60%70%80%90%

100%

1980 1984 1988 1992 1996 2000 2004 2008 2012

13F 13F + non-filing foreign

33

Figure 2. Intra-institutional trades over timeThe quarterlyshare of aggregate institutional trading volumeduring the calendarquarter countered by other institutional investors on the other side of the trade.For each stock-quarter observation, we first determine the smaller of theinstitutional dollar value of the shares demanded or supplied during the quarterand then divide it by the gross dollar value of shares demanded or supplied onthe other side of the trade. This intra-institutional trade share is bound betweenzeroand100% by construction. We then take the value-weightedaverage of thetrade share across all stocks during that quarter using the beginning-of-quartermarket capitalization as the weight. The figure depicts the four-quarter movingaverage of the intra-institutional trade share.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

100%

1981 1985 1989 1993 1997 2001 2005 2009 2013

34

Figure 3. Composition of counterparties to institutional tradesThe quarterly share of institutional trading volume countered by retail investors(black solid line), the firm (black dotted line), andinsiders (gray dotted line) onthe other side. Counterparty share is computed for each stock-quarter as the netdollar value of the counterparty's trade during the quarter divided by the netdollar value of institutional trades on the other side. Counterparty share is set tozero if the net counterparty demand is on the same side as the net institutionaldemand (i.e., both sides buying or selling together), and to one if the netcounterparty demand(supply)exceeds the net dollar valueof institutional supply(demand) on the other side. We then take the value-weighted average of thecounterparty share across all stocks during the quarter using the beginning-of-quarter market capitalization as the weight. The figure depicts the four-quartermoving average of the counterparty shares.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

1981 1985 1989 1993 1997 2001 2005 2009 2013

Retail Firm Insiders

35

Institutional performance is measured as the average abnormal (size & B/Mmatched) buy-and-hold stock returns during the subsequent year earned by thedifference portfolio that goes long the stocks in the highest institutional demandquintile andshort the stocks in the lowest institutional demandquintile duringacalendar quarter. The figures depict the eight-quarter moving average of theabnormal returns, equal-weighted in Panel A and value-weighted in Panel B.The dashed lines show the average quarterly return before and after December1999.

Figure 4. Institutional performance over time

Institutional performance is measured as the average abnormal (size & B/Mmatched) buy-and-hold stock returns during the subsequent year earned by thedifference portfolio that goes long the stocks in thehighest institutionaldemandquintile and short the stocks in the lowest institutional demandquintile duringacalendar quarter. The figures depict the eight-quarter moving average of theabnormal returns, equal-weightedin PanelA andvalue-weighted in Panel B.ThedashedlinesaretheaveragereturnsbeforeandafterDecember1999.

Panel A: Equal-weighted returns

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

Panel B: Value-weighted returns

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 2012

36

Figure 5: Net flows of mutual funds

 

Figure 4 (placeholder): Fund flows [Need to create our own version of this table.  Obtain ICI data?] 

 

 

37

This table provides mean values of quarterly demand and supply of stocks by fourinvestor types: i) institutional investors, ii) firms via equity issues and repurchases, iii)firm insiders (officers and directors), and iv) the residual. Institutional demand is thenet percentage of a firm's shares bought by institutional investors during the calendarquarter (net number of shares bought divided by total shares outstanding as of thebeginning of the quarter). Firm demand is the percentage change in the firm's totalshares outstanding during the quarter timesminus one,with apositive valueindicatinga net repurchase and a negative value indicating a net issuance. Insider demand is thenet percentage of a firm's shares bought by insiders during the quarter. Residualdemand is a plug variable balancing the supply and demand of each firm's shares,computed as the net supply of new shares by the firm (negative of firm demand) plusthe net supply of shares by firm insiders (negative of insider demand) minusinstitutional demand.

Table 1: Demand and supply of shares by various investor types This table provides mean values for quarterly demand and supply of stocks by fourdifferent investor types: i) 13F institutional investors, ii) firms themselves via equityissues and repurchases, iii) firm insiders (officers and directors), and iv) the residual.Institutional demand is the net percentage of a firm's shares purchased by institutionalinvestors during a calendar quarter (net number of shares purchased during the quarterscaled by shares outstanding at the beginning of the quarter). Firm demand is thepercentage change in the firm's total shares outstanding during the calendar quartertimesnegative one,with positivevalues indicating anet repurchaseand negative valuesindicatinganet equity issuance during the quarter. Insider demand is the net percentageof a firm's shares acquired by firm insiders during the calendar quarter. Residualdemand is a plug variable balancing the supply and demand of each firm's shares,computed as the net supply of new shares by the firm (negative of firm demand) plus net supply of shares by firm insiders (negative of insider demand) minus institutionaldemand.

Table 1: Demand and supply of shares by various investor types

Sample Period: 1980s 1990s 2000-13

Institutional demand 0.40% 0.76% 0.98%

Firm demand -0.83% -1.40% -1.02%

Insider demand -0.05% -0.10% -0.12%

Residual demand 0.48% 0.74% 0.16%

This table provides mean values of quarterly demand and supply of stocks by fourinvestor types: i) institutional investors, ii) firms via equity issues and repurchases, iii)firm insiders (officers and directors), and iv) the residual. Institutional demand is thenet percentage of a firm's shares bought by institutional investors during the calendarquarter (net number of shares bought divided by total shares outstanding as of thebeginning of the quarter). Firm demand is the percentage change in the firm's totalshares outstanding during the quarter timesminus one,with apositive valueindicatinga net repurchase and a negative value indicating a net issuance. Insider demand is thenet percentage of a firm's shares bought by insiders during the quarter. Residualdemand is a plug variable balancing the supply and demand of each firm's shares,computed as the net supply of new shares by the firm (negative of firm demand) plusthe net supply of shares by firm insiders (negative of insider demand) minusinstitutional demand.

This table provides mean values for quarterly demand and supply of stocks by fourdifferent investor types: i) 13F institutional investors, ii) firms themselves via equityissues and repurchases, iii) firm insiders (officers and directors), and iv) the residual.Institutional demand is the net percentage of a firm's shares purchased by institutionalinvestors during a calendar quarter (net number of shares purchased during the quarterscaled by shares outstanding at the beginning of the quarter). Firm demand is thepercentage change in the firm's total shares outstanding during the calendar quartertimesnegative one,with positivevalues indicating anet repurchaseand negative valuesindicatinganet equity issuance during the quarter. Insider demand is the net percentageof a firm's shares acquired by firm insiders during the calendar quarter. Residualdemand is a plug variable balancing the supply and demand of each firm's shares,computed as the net supply of new shares by the firm (negative of firm demand) plus net supply of shares by firm insiders (negative of insider demand) minus institutionaldemand.

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Table 2: Performance of institutional trades over timeThis table reports value-weighted abnormal future stock returns earned by stocks with high institutional buying, high institutional selling, and the difference portfoliothatgoes long instocks in the highest institutionaldemand quintile and short in stocks in the lowest institutionaldemand quintile. Each quarter we first sort stocks intomarket capitalization deciles (using NYSE cutoffs) and then within each size decile sort stocks into quintiles basedon the change in the fraction of sharesoutstandingheld by 13F institutional investors. The stocks in the highestquintile are placed in the "Buy"portfolio and those in the lowest quintile are placed in the "Sell" portfolio.We report the size and B/M matched, value-weighted, abnormalbuy and hold annual returns during the subsequent four quarters. T-statistics are based on time-seriesstandard errors adjusted for serial correlation using the Newey-West procedure with a four-quarter lag.

Sample period: 1980-99 2000-13 Diff 1980-99 2000-13 Diff 1980-99 2000-13 Diff 1980-99 2000-13 Diff

Institutions Buy (Q5) 0.95% -1.35% 0.79% -0.68% 0.87% -2.24% 2.63% -3.36%(1.6) (-1.0) (1.2) (-0.4) (0.8) (-2.0) (2.3) (-4.0)

Institutions Sell (Q1) -0.52% 1.26% -0.44% 1.28% -0.75% 1.38% -1.21% 0.96%(-0.9) (2.5) (-0.6) (1.8) (-1.0) (3.1) (-2.3) (1.6)

Difference (Q5-Q1) 1.47% -2.61% -4.08% 1.23% -1.96% -3.19% 1.62% -3.62% -5.24% 3.84% -4.32% -8.16%(1.6) (-2.3) (-3.7) (1.1) (-1.2) (-2.1) (1.1) (-3.3) (-3.9) (2.6) (-3.4) (-5.5)

Small stocksAll stocks Large stocks Midcap stocks

This table reports value-weighted abnormal future stock returns earned by stocks with high institutional buying, high institutional selling, and the difference portfoliothatgoes long instocks in the highest institutionaldemand quintile and short in stocks in the lowest institutionaldemand quintile. Each quarter we first sort stocks intomarket capitalization deciles (using NYSE cutoffs) and then within each size decile sort stocks into quintiles basedon the change in the fraction of sharesoutstandingheld by 13F institutional investors. The stocks in the highestquintile are placed in the "Buy"portfolio and those in the lowest quintile are placed in the "Sell" portfolio.We report the size and B/M matched, value-weighted, abnormalbuy and hold annual returns during the subsequent four quarters. T-statistics are based on time-seriesstandard errors adjusted for serial correlation using the Newey-West procedure with a four-quarter lag.

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Table 3: Performance of institutional trades against retailThis table reportsvalue-weighted abnormal futurestock returnsearned by portfolios thatgo long instocks withhighdemand (top quintile) from institutions and low demand (bottom quintile) from theresidual, and short in stocks with low demand (bottom quintile) from institutions and highdemand(top quintile) from the residual during a calendar quarter. Panel A reports the results for the fullsample,Panel B for largestocks (top 20% of market capitalizationusing NYSE cutoffs), Panel C formid-capstocks (next 30%), and Panel D for small-cap stocks (bottom 50%). Institutional demand ismeasured as the change in the fraction of shares outstanding held by 13F institutional investors.Demand from the residual is measured as inTable 1. Abnormal returnsare size and B/M matched,value-weighted, buy and hold returns during the subsequent four quarters. T-statisticsare basedontime-series standard errors adjusted for serial correlation using the Newey-West procedure with afour-quarter lag.

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 2.38% -0.52% -2.90%

(2.66) (-0.56) (-2.73)

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 2.12% -0.19% -2.31%

(1.81) (-0.12) (-1.42)

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 1.98% -0.61% -2.59%

(1.62) (-0.76) (-2.02)

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 4.79% -2.00% -6.79%

(3.57) (-1.28) (-3.97)

Panel A: All stocks

Panel B: Large stocks

Panel D: Small stocks

This table reportsvalue-weighted abnormal futurestock returnsearned by portfolios thatgo long instocks withhighdemand (top quintile) from institutions and low demand (bottom quintile) from theresidual, and short in stocks with low demand (bottom quintile) from institutions and highdemand(top quintile) from the residual during a calendar quarter. Panel A reports the results for the fullsample,Panel B for largestocks (top 20% of market capitalizationusing NYSE cutoffs), Panel C formid-capstocks (next 30%), and Panel D for small-cap stocks (bottom 50%). Institutional demand ismeasured as the change in the fraction of shares outstanding held by 13F institutional investors.Demand from the residual is measured as inTable 1. Abnormal returnsare size and B/M matched,value-weighted, buy and hold returns during the subsequent four quarters. T-statisticsare basedontime-series standard errors adjusted for serial correlation using the Newey-West procedure with afour-quarter lag.

Panel C: Mid-cap stocks

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This table reports value-weighted abnormal future stock returns earned by portfolios that go long in stocks with high demand (topquintile) from institutions and low demand (bottom quintile) from a counterparty during a calendar quarter, and short in stocks withlow demand (bottom quintile) from institutions and high demand (top quintile) from the counterparty. Institutional demand ismeasured as the change in the fraction of shares outstanding held by 13F institutional investors. The counterparties are either the firm(equity issuance vs. repurchase) or firm insiders (officers and directors). Demand from counterparties are measured as in Table 1.Abnormal returnsare size and B/M matched, value-weighted, buy and hold returnsduring the subsequent year. T-statistics are basedon time-series standard errors adjusted for serial correlation using the Newey-West procedure with a four-quarter lag.

Table 4: Performance of institutional trades against informed counterparties

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -6.00% -7.27% -1.27% -2.12% -7.67% -5.55%

(-3.89) (-2.63) (-0.50) (-0.55) (-1.72) (-1.23)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -5.63% -4.95% 0.68% -11.90% -5.66% 6.24%

(-2.03) (-1.57) (0.18) (-1.61) (-0.82) (0.76)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -2.70% -11.63% -8.93% 3.51% -15.12% -18.63%

(-0.94) (-3.40) (-2.48) (0.53) (-2.60) (-2.30)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -2.50% -10.79% -8.29% -3.95% -3.39% 0.56%

(-1.14) (-3.85) (-3.10) (-0.81) (-0.93) (0.10)\

Against firm Against insiders

This table reports value-weighted abnormal future stock returns earned by portfolios that go long in stocks with high demand (topquintile) from institutions and low demand (bottom quintile) from a counterparty during a calendar quarter, and short in stocks withlow demand (bottom quintile) from institutions and high demand (top quintile) from the counterparty. Institutional demand ismeasured as the change in the fraction of shares outstanding held by 13F institutional investors. The counterparties are either the firm(equity issuance vs. repurchase) or firm insiders (officers and directors). Demand from counterparties are measured as in Table 1.Abnormal returnsare size and B/M matched, value-weighted, buy and hold returnsduring the subsequent year. T-statistics are basedon time-series standard errors adjusted for serial correlation using the Newey-West procedure with a four-quarter lag.

Panel B: Large stocks

Panel C: Midcap stocks

Panel D: Small stocks

Panel A: All stocks

Panel B: Large stocks

Panel C: Midcap stocks

Panel D: Small stocks

Panel A: All stocks

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Table 5: Performance of retail investors against informed counterpartiesThis table reports the average dailymarket-adjusted returnsduring the three days surrounding stocks' earnings announcements duringthe year followingthe formation of quarterly portfolios that go long instocks withhigh demand (top quintile) from residual investorsand low demand (bottom quintile) from informed counterparties, and short in stocks with low demand (bottom quintile) from residualinvestors and high demand (top quintile) from counterparties. Residual and informed demand are measured as inTable 1. T-statisticsare based on time-series standard errors adjusted for serial correlation using the Newey-West procedure with a twelve-month lag.

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -5.47% -5.51% -0.04% 2.15% -5.12% -7.27%

(-3.08) (-1.91) (0.02) (0.49) (-1.76) (-2.05)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -7.17% -5.44% 1.73% 2.47% -5.82% -8.29%

(-2.84) (-1.72) (0.63) (0.48) (-1.83) (-1.70)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -1.76% -5.35% -3.59% 6.47% -4.09% -10.56%

(-0.75) (-1.96) (-1.31) (1.04) (-0.90) (-1.95)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -6.05% -7.69% -1.64% -9.48% -6.77% 2.71%

(-6.57) (-3.07) (-0.84) (-3.57) (-2.15) (0.72)

Panel D: Small stocks Panel D: Small stocks

Panel B: Large stocks Panel B: Large stocks

Panel C: Midcap stocks Panel C: Midcap stocks

Against firm Against insidersPanel A: All stocks Panel A: All stocks

This table reports the average dailymarket-adjusted returnsduring the three days surrounding stocks' earnings announcements duringthe year followingthe formation of quarterly portfolios that go long instocks withhigh demand (top quintile) from residual investorsand low demand (bottom quintile) from informed counterparties, and short in stocks with low demand (bottom quintile) from residualinvestors and high demand (top quintile) from counterparties. Residual and informed demand are measured as inTable 1. T-statisticsare based on time-series standard errors adjusted for serial correlation using the Newey-West procedure with a twelve-month lag.

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Table 6: Earnings announcement performance against the residualThis table reports the average dailymarket-adjusted returnsduring the threedays surrounding stocks'earnings announcements during the year followinghe formation of portfolios that go long instockswith high demand (top quintile) from institutions and low demand (bottom quintile) from residualinvestors, and short in stocks with low demand (bottom quintile) from institutions and highdemand(top quintile) from residual investors during a calendar quarter. Institutional demand is measured asthe change in the fraction of shares outstanding held by 13F institutional investors. T-statistics arebased on time-series standarderrors adjusted for serial correlation using the Newey-West procedurewith a twelve-month lag.

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 0.05% 0.04% -0.01%

(2.65) (1.25) (-0.36)

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 0.07% 0.06% -0.01%

(2.21) (1.21) (-0.13)

1980-1999 2000 - 2013 DifferenceInst Buy - Sell -0.01% -0.01% 0.00%

(-0.67) (-0.16) (0.24)

1980-1999 2000 - 2013 DifferenceInst Buy - Sell 0.10% 0.01% -0.09%

(4.80) (0.44) (-2.80)

Panel A: All stocks

This table reports the average dailymarket-adjusted returnsduring the threedays surrounding stocks'earnings announcements during the year followinghe formation of portfolios that go long instockswith high demand (top quintile) from institutions and low demand (bottom quintile) from residualinvestors, and short in stocks with low demand (bottom quintile) from institutions and highdemand(top quintile) from residual investors during a calendar quarter. Institutional demand is measured asthe change in the fraction of shares outstanding held by 13F institutional investors. T-statistics arebased on time-series standarderrors adjusted for serial correlation using the Newey-West procedurewith a twelve-month lag.

Panel B: Large stocks

Panel C: Mid-cap stocks

Panel D: Small stocks

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Table 7: Earnings announcement performance against informed counterpartiesThis table reports the average dailymarket-adjusted returnsduring the three days surrounding stocks' earnings announcements duringthe year following the formation of quarterly portfolios that go long in stocks withhigh demand (top quintile) from institutions andlow demand (bottom quintile) from the counterparty, and short in stocks with low demand (bottom quintile) from institutions and highdemand (top quintile) from the counterparty. Institutional demand is measured as the change in the fraction of shares outstanding heldby 13F institutional investors. The counterparties are the firm (equity issuance vs. repurchase) and insiders. Demand fromcounterparties is measured as inTable 1. T-statistics are based on time-series standarderrors adjusted for serial correlation using theNewey-West procedure with a twelve-month lag.

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -0.02% -0.09% -0.07% -0.05% -0.01% 0.04%

(-0.34) (-1.22) (-1.11) (-0.62) (-0.12) (0.33)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell 0.02% -0.01% -0.03% -0.14% 0.15% 0.29%

(0.25) (-0.11) (-0.29) (-0.99) (1.36) (1.61)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell 0.05% -0.22% -0.27% 0.08% -0.22% -0.30%

(0.79) (-3.91) (-3.29) (0.83) (-1.80) (-1.71)

1980-99 2000 - 2013 Difference 1980-99 2000 - 2013 DifferenceInst Buy - Sell -0.03% -0.31% -0.28% -0.06% -0.09% -0.03%

(-0.84) (-4.40) (-3.99) (-0.88) (-1.01) (-0.25)

Panel D: Small stocks Panel D: Small stocks

Panel B: Large stocks Panel B: Large stocks

Panel C: Midcap stocks Panel C: Midcap stocks

Against firm Against insidersPanel A: All stocks Panel A: All stocks

This table reports the average dailymarket-adjusted returnsduring the three days surrounding stocks' earnings announcements duringthe year following the formation of quarterly portfolios that go long in stocks withhigh demand (top quintile) from institutions andlow demand (bottom quintile) from the counterparty, and short in stocks with low demand (bottom quintile) from institutions and highdemand (top quintile) from the counterparty. Institutional demand is measured as the change in the fraction of shares outstanding heldby 13F institutional investors. The counterparties are the firm (equity issuance vs. repurchase) and insiders. Demand fromcounterparties is measured as inTable 1. T-statistics are based on time-series standarderrors adjusted for serial correlation using theNewey-West procedure with a twelve-month lag.

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This table reports value-weighted average abnormal future stock returns earned by a quarterlyportfolio that goes long in stocks with high demand (top quintile) and short in stocks with lowdemand (bottomquintile) from threetypes of institutional investors basedon Bushee's classification(Bushee and Noe, 2000; Bushee 2001): i) transient (diversified with high turnover), ii) quasiindexers (diversified with low turnover), and iii) dedicated (concentrated with low turnover).Institutional demand is measured as the net change in the number of shares held by a giveninstitutional investor type during the quarter scaled by shares outstanding at the beginning of thequarter. Abnormal returns are size and B/M matched, vaue-weighted, annual buy and hold returnsduring the subsequent year following portfolio formation. T-statistics are based on time-seriesstandarderrors adjusted for serial correlation using the Newey-West procedurewith a twelve-monthlag.

Table 8: Institutional performance by institution type

Sample period: 1980-99 2000-13 DiffTransient 2.96% -0.72% -3.68%

(2.4) (-1.1) (-3.1)

Quasi indexers -0.51% -4.34% -3.83%(-0.6) (-3.0) (-3.4)

Dedicated 0.79% 0.74% -0.05%(1.2) (1.0) (-0.0)

This table reports value-weighted average abnormal future stock returns earned by a quarterlyportfolio that goes long in stocks with high demand (top quintile) and short in stocks with lowdemand (bottom quintile) from threetypes of institutional investors basedon Bushee's classification(Bushee and Noe, 2000; Bushee 2001): i) transient (diversified with high turnover), ii) quasiindexers (diversified with low turnover), and iii) dedicated (concentrated with low turnover).Institutional demand is measured as the net change in the number of shares held by a giveninstitutional investor type during the quarter scaled by shares outstanding at the beginning of thequarter. Abnormal returns are size and B/M matched, vaue-weighted, annual buy and hold returnsduring the subsequent year following portfolio formation. T-statistics are based on time-seriesstandarderrors adjusted for serial correlation using the Newey-West procedurewith a twelve-monthlag.