Negative returns on addition to S&P 500 index and positive returns on deletion?

New evidence on attractiveness of S&P 500 vs. S&P 400 indexes

Anand M. Vijh and Jiawei (Brooke) Wang 1

Abstract

In recent years, the majority of additions to and deletions from the S&P 500 index have been

stocks that were previously or subsequently included in the S&P 400 index. The announcement

returns of these changes have been the opposite of what has been documented for all S&P 500

additions and deletions in an extensive literature. During 2016-2019, such ‘upward additions’

to the S&P 500 index resulted in an average announcement excess return of -2.31% over a

three-day period while ‘downward deletions’ resulted in an excess return of +1.21%. We

explain these new results by the increasing ownership of S&P 400 stocks by institutional

investors, the majority of whom are active fund managers. Our results thus show the increasing

benefits of being included in the mid-cap S&P 400 index relative to being included in the large-

cap S&P 500 index.

First version: August 17, 2020

1 Both authors are from Tippie College of Business, Department of Finance, University of Iowa, Iowa City, IA 52242,

USA. Email address: Anand-Vijh@uiowa.edu (corresponding author), and Jiawei-Wang@uiowa.edu.

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Negative returns on addition to S&P 500 index and positive returns on deletion?

New evidence on attractiveness of S&P 500 vs. S&P 400 indexes

1. Introduction

Since mid-1980’s, one of the most established event study results has been that stocks earn positive

returns on addition to the S&P 500 index and negative returns on deletion from that index.2 For example,

Chen, Noronha, and Singal (2004) examine a comprehensive sample of additions and deletions during

1962-2000. They document a highly significant one-day announcement excess return of 5.45% for additions

and -8.46% for deletions during October 1989 to December 2000, a period during which the Standard &

Poor’s Corp. started pre-announcing changes to the index ahead of actual additions and deletions. The

addition effect moderated during later years but remained positive (Soe and Dash 2008, Patel and Welch

2017). A contemporaneous study by Bennett, Stulz, and Wang (2020) goes further and documents an

insignificant excess return for additions over a longer 11-day window bracketing the announcement date

during 2008-2017. Finally, the popular press has assumed all along that addition to the S&P 500 index is

good news for any stock, which we infer from numerous articles that we read as part of this research. In

contrast with the previous academic literature and the common perception in popular press, we document

that more recently for a large subset of changes to S&P 500 index the market reaction has become negative

for additions and positive for deletions.

That large subset consists of changes from S&P 400 to S&P 500 index that constitute 63 out of 88

additions, and changes from S&P 500 to S&P 400 index that constitute 40 out of 45 deletions during 2016-

2019.3 Following Zhou (2011), we label these cases as ‘upward additions’ and ‘downward deletions’.

(These terms are used to describe movements to indexes of higher or lower market capitalization stocks

and not as pre-judgment of their valuation impacts.) The 63 upward additions result in highly significant

2 A partial list of papers that document either the positive addition effects or the negative deletion effects includes:

Harris and Gurel (1986), Shleifer (1986), Jain (1987), Pruitt and Wei (1989), Dhillon and Johnson (1991), Beneish

and Whaley (1996), Lynch and Mendenhall (1997), Wurgler and Zhuravaskaya (2002), Denis, McConnell,

Ovtchinnikov, and Yu (2003), Hegde and McDermott (2003), Chen, Noronha, and Singal (2004), Soe and Dash

(2008), Zhou (2011), and Schnitzler (2018). 3 Our samples are comprehensive, but subject to certain necessary criteria that data should be available and that S&P

500 index funds should be required to buy added stocks or sell deleted stocks.

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excess returns of -1.59% and -2.31% over one-day and three-day windows centered on the announcement

date, and the 40 downward deletions result in significant excess returns of 0.61% and 1.21% over the same

windows.4 For both additions and deletions, the returns evidence during 2016-2019 contrasts with the

returns evidence during 2001-2015 that is significant in the opposite direction. The change has been gradual

rather than sudden, with periods of insignificance before flipping direction, and from our reading, it cannot

be attributed to any policy change by the S&P U.S. Index Committee. To top the evidence, consider the

following: During June 2017 to December 2019, a total 36 stocks were added to the S&P 500 index that

were previously included in the S&P 400 index. The one-day announcement excess returns for all 36 stocks

are negative and the three-day announcement excess returns for 34 out of 36 stocks are also negative, with

corresponding mean values of -2.17% and -3.35% (t-statistics -11.02 and -7.82). From casual impression,

such (nearly) unanimous event-study returns are rarely seen in the finance literature.5

To complete the evidence on returns, we do not find parallel results for the minority of stocks that

were added to or deleted from the S&P 500 index, but were not previously or subsequently included in the

S&P 400 index. We label these cases as ‘pure additions’ and ‘pure deletions’. The announcement excess

returns of pure additions are strongly positive during both subperiods of 2001-2015 and 2016-2019, while

the returns of pure deletions are strongly negative during the first subperiod and insignificant during the

second subperiod (when there were only five cases). In the following paper, we first argue that the combined

evidence cannot be explained by several existing hypotheses proposed to explain the S&P 500 addition and

deletion effects. This is not surprising since the existing hypotheses were motivated to explain the then

positive returns of additions and negative returns of deletions. We then argue that our combined evidence

for ‘upward additions’ and ‘downward deletions’ points to the changing attractiveness of the large-cap S&P

500 index relative to the mid-cap S&P 400 index (and further the small-cap S&P 600 index). This issue has

not received much attention in the previous literature.

4 All excess returns in this paper are calculated as the difference between buy-and-hold stock returns and S&P 500

index returns. 5 We acknowledge that the choice of both 2016 to 2019 and June 2017 to December 2019 windows suffer from some

ex-post selection bias as these windows were decided after looking at the returns data. However, this is common in

the related literature. The excess returns of 27 additions during January 2016 to May 2017 are also negative and

significant, but smaller in magnitude.

3

Chen et al (2004) summarize many existing hypotheses that we examine in the current context.

First, following the price pressure hypothesis, if there is an imbalance between buying by S&P 500 index

funds and selling by S&P 400 funds of upward additions, then there may be a temporary price increase if

the buy volume is greater and price decrease if the sell volume is greater. However, based on the amount

of indexed assets, it does not appear that there has been a shift from net buying to net selling between the

two subperiods. Besides, after years of suffering the effect of price pressures, index funds have designed

strategies to stretch their buying and selling over longer periods. Second, the liquidity and transaction cost

hypothesis seems to have lost some relevance in recent years with lower bid-ask spreads and higher trading

volumes in most stocks. Besides, we do not find much difference between long-term before and after trading

volumes for both upward additions and downward deletions. Third, the investor awareness hypothesis has

attracted attention in recent studies. Chen et al propose that adding stocks to the S&P 500 index makes both

individual and institutional investors more aware of those stocks and more likely to buy them. However,

they also say that investors do not easily become unaware of deleted stocks. In the present context, it is

difficult to imagine that news of addition to the S&P 500 index, regardless of their previous indexing status,

would make investors less aware of those stocks during 2016-2019, leading to their price decline. Therefore,

this hypothesis also cannot explain our results.

Fourth, starting with Shleifer (1986), the downward sloping demand curve hypothesis has been

used to explain a permanent upward price effect of additions due to increased demand by S&P 500 index

funds. In the form that it is proposed by many authors, it cannot explain the negative announcement returns

of upward additions during 2016-2019. That is because S&P 500 index funds have always held a greater

proportion of their constituents stocks than S&P 400 index funds have held of their constituent stocks,

which leads to a net positive demand from the combined set of index funds in all years. Yet, we argue that

an expanded version of the downward sloping demand curve hypothesis can partly explain our results. The

key innovation is that we consider demand from both passive index funds and actively managed funds,

unlike previous literature that only considers demand from passive index funds.

Our analysis starts with Blume and Keim (2017) who document the changing nature of institutional

stock investing from 1980 to 2010. During earlier part of their study period, institutions over-weighted their

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portfolio in large-cap stocks beyond the proportion of such stocks in the market portfolio. However, by the

later part of their study period, institutions were over-weighting mid-cap and small-cap stocks. The trend

was more pronounced for hedge funds. Blume and Keim attribute this shift in institutional investing and

holding to increased recognition of how risk of smaller stocks can be reduced effectively by diversification,

recognition of small-stock premium, and greater opportunity for finding mispricing among small stocks

that attracts active investors. They report a pronounced inverted-U relation between total institutional

holding and firm size using a cubic function of log firm value. However, they do not analyze the role of

index membership that we bring in our analysis.

We first confirm that the trend of increased institutional holdings of mid-cap and small-cap stocks

compared to large-cap stocks continues in our sample as shown by an inverted-U curve. Then we show that,

in the year 1999, slightly before the beginning period of our analysis, the average total institutional holding

of stocks in the S&P 500, S&P 400, S&P 600, and none of the three indexes stocks stood at 63.7%, 60.5%,

56.4%, and 24.5%. By the end of the period in 2019, these figures had changed to 78.9%, 86.0%, 84.3%,

and 47.8%, leaving relatively little stock in the hands of retail (non-institutional) investors, at least in the

case of stocks belonging to the three S&P indexes.6 The transition was gradual from 1999 to 2019 and not

sudden. We make two inferences. First, in all years, any S&P index membership makes a significant

difference to the total institutional ownership of firms.7 Second, in recent years mid-cap index stocks have

the highest institutional ownership, followed by small-cap index stocks, and then large-cap index stocks.

The above univariate results, however, mix the effects of firm size and index membership. Firm

size does not change much on moving a stock from one index to the other. So to separate these effects and

compare the three indexes, we enhance the Blume and Keim (2017) model specification by adding a dummy

variable for each index in cross-sectional regressions carried out during 1999-2019. The coefficients of all

three dummy variables are always positive, but decrease over time, showing the positive but decreasing

influence of any S&P index membership on total institutional holdings. Further, the difference between

6 Blume and Keim (2017) discuss why the institutional holdings may be overstated across the board due to certain

Section 13F reporting requirements of SEC (discussed later in Section 4). 7 Notice stocks not included in S&P 1500 index may still be held by other types of index funds, including Russel 1000,

2000, or 3000 index funds, total stock market index funds, and extended market index funds.

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coefficients of S&P 400 and S&P 500 dummy variables is positive and increasing over time. In other words,

holding firm size constant, the influence of S&P 400 index membership is declining, but at a rate that is

about one-fourth percent less per year than the rate for S&P 500 index membership. We obtain similar

results for the effect of S&P 600 vs. S&P 500 index membership on total institutional ownership.

We interpret the totality of our evidence as pointing to the increasing attractiveness of S&P 400

index membership relative to S&P 500 index membership over time. We argue that the increasing total

institutional ownership of S&P 400 stocks relative to S&P 500 stocks is partly responsible for the negative

market reaction to stocks that move from the former to the latter index. This argument follows from the

evidence presented by Sias, Starks, and Titman (2006) that a decrease in institutional holdings decreases

firm value. In addition, we point out that moving stocks from S&P 400 to S&P 500 index should reduce

their active institutional ownership even more than it reduces their total institutional ownership. That is

because passive indexing linked to S&P 500 index has been steadily higher than that linked to S&P 400

index by about 5% over the entire sample period. Several papers highlight the positive effect of institutional

activism on firm value, so that particular decrease should further contribute to negative market reaction.

Unfortunately, since active institutional owners are in no hurry to change their holdings soon after a change

in index membership, it is difficult to illustrate the long-term anticipated changes in their holdings with a

short-window before and after test around the event date. However, we do show that the yearly difference

between average total institutional ownership of S&P 400 and S&P 500 stocks and the yearly average three-

day announcement excess return of upward additions are very negatively related.

We have not talked much about the announcement returns of downward deletions of S&P 500

stocks that were subsequently included in the S&P 400 index in the introduction because they tend to be

the mirror image of upward additions to some extent. We have also not talked much about pure additions

(i.e., from outside the three indexes to the S&P 500 index) or pure deletions (the opposite) because their

announcement returns continue to be positive and negative, respectively, with not much change between

subperiods. In addition, we prefer to separately analyze the upward additions/downward deletions and pure

additions/deletions throughout the paper because mixing these two samples misses important insights.

Finally, we conjecture that there would be additional reasons for reversal of announcement returns for

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upward additions and downward deletions documented in this paper besides the changing institutional

ownership of stocks belonging to the two indexes. For example, the corporate finance effects related to

earnings performance, investments, equity issues, governance, and compensation, similar to those

documented by Bennett et al (2020) may be changing over time, and the market may be recognizing them

with some lag.

Section 2 describes the data and methods, and Section 3 presents the main evidence on returns and

trading volumes. Section 4 describes why the existing hypotheses cannot explain the changing evidence

and Section 5 presents new evidence on institutional ownership of index stocks. Section 6 concludes.

2. Data and methods

2.1. Sample of additions and deletions

Our sample of changes to the S&P 500 index starts with the Compustat Index Constituents file.

This file lists the S&P index history of all Compustat stocks. For each stock, it gives FROM and THRU

dates for all indexes in which it has been included over the years. Using this file, we compile a list of stocks

with FROM dates starting in 2001. The FROM date is the effective date (ED) of addition in a chosen index.

We exclude additions before 2001 because those are too old for studying recent trends, and because they

have been thoroughly investigated by Chen et al (2004) and others. We next compile a list of all stocks with

THRU date starting in 2001. This is the last date when a stock was included in a chosen index, so the next

trading date is the ED of deletion from that index. This is our starting sample of additions to and deletions

from the S&P 500 index. We also identify from the Compustat Index Constituents file whether the stock

was previously or subsequently included in the S&P 400 or S&P 600 indexes.

For each observation, we next scan media reports on Factiva using the firm name and S&P 500 as

keywords up to one month before ED. This tells us the precise date on which S&P Dow Jones Indices LLC

(former Standard and Poor’s Corp, henceforth also referred to simply as S&P) announces planned changes

to its indexes. This announcement occurs after close of trading around 5 p.m. EST, so the next trading day

becomes the announcement date (AD) for calculating returns. The media reports give the previous index

status of a firm as well as the reasons for change. For each addition and deletion, we ask whether it would

result in S&P 500 index funds buying or selling the stock. In some cases, an existing S&P 500 firm spins

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off a subsidiary firm that is added to the index. The S&P 500 index funds would receive the new stock as a

dividend, so we exclude such stocks. In some other cases, an S&P 500 firm acquires another firm and

restructures as a new firm that is added to the index. We exclude such cases because there may be little or

no incremental buying by index funds, and because the index addition effects may be confounded with

restructuring effects. For deletions, we exclude cases where the firm ceases to exist shortly after ED because

it is acquired or bankrupted.

We further require that the firm can be found on CRSP (Center for Research in Security Prices)

stock file and that daily returns data are available from one month before AD to one month after ED on that

file. Usually, this criterion excludes cases in which the firm has undergone significant restructuring as

mentioned above. It has no effect on upward additions or downward deletions that are ongoing firms for

some time before AD or after ED. Almost all such changes occur because a firm included in the S&P 500

index ceases to meet the minimum market value criterion, and another firm typically from the S&P 400

index meets the criterion. For example, since February 20, 2019, S&P Dow Jones Indices requires a

minimum market value of $8.2 billion in the S&P 500 index, $2.4 billion in the S&P 400 index, and $0.66

billion in the S&P 600 index.

Our final sample contains a total 365 additions and 180 deletions during 2001 to 2019. This includes

227 upward additions, 138 pure additions, 119 downward deletions, and 61 pure deletions. Three upward

additions during 2007-2008 are from the S&P 600 index; the remaining upward additions and all downward

deletions are from or to the S&P 400 index. For expositional convenience, we refer to all upward additions

as coming from the S&P 400 index. The proportion of upward additions and downward deletions in the

total sample is significantly greater in the second subperiod of 2016-2019, suggesting that S&P Dow Jones

Indices has been more aggressively rebalancing its indexes to meet its market value criteria.

2.2. Institutional ownership data

All U.S. and foreign institutions with greater than $100 million holdings of U.S. stocks are required

to file Form 13F with the SEC (Securities and Exchanges Commission) listing their ownership of various

stocks at the end of each quarter. Refinitiv (a new firm owned by Blackstone Group and Thomson Reuters)

collects such data and makes them available as the s34 database. This database lists how many shares of

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each stock are owned by each institutional manager. We calculate the total institutional ownership of each

stock by aggregating the shares owned by all institutional managers. We winsorize this ownership variable

each quarter at the 1 and 99 percent levels to compress outliers that may be data errors. For benchmarking,

we merge s34 file with CRSP file and retain only stocks with share codes 10, 11, or 12 (ordinary common

shares of U.S. firms, but also firms incorporated outside U.S.).

2.3. Calculation of excess returns

We calculate all excess returns in this paper as the differences between buy-and-hold returns of any

stock and the S&P 500 index over any chosen window. Using alternate market-model type of excess returns

would not be appropriate in our event study because additions are preceded by strongly positive excess

returns of 34% and deletions are preceded by strongly negative excess returns of -25% during a 252-day

period ending on AD-2. That would understate (overstate) all event-period returns for upward additions

(downward deletions) by setting too high (too low) a benchmark.

3. Market reaction to stocks added to or deleted from the S&P 500 index

3.1. Additions to the S&P 500 index

We start by examining recent evidence on market reaction to stocks added to the S&P 500 index

that has been the focus of many previous studies. We examine several windows before AD to after ED and

compactly report a few windows in Table 1. We report results for the aggregate sample and for subsamples

broken by time and by upward vs. pure additions.

Changes to the index are widely disseminated through media reports after close of trading on

previously unknown days. So on the following day, which we designate as the announcement date, or AD,

we find the clearest evidence of market reaction. This evidence also tends to be statistically the most

significant as it is measured over one day. Column (2) of Table 1 shows that for all 365 additions during

2001-2019 the average one-day excess return on AD equals 1.82% with a highly significant t-statistic of

10.98. It is smaller than the market reaction of 5.45% for additions during 1989-2000 documented by Chen

et al (2004), but still quite substantial (91 cents for a $50 stock).

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Consistent with Zhou (2011), we next show that AD returns differ across upward additions and

pure additions. Columns (3) and (7) of Table 1 show that, during the aggregate period, the average excess

return on AD equals 0.80% for upward additions and 3.49% for pure additions (t-statistics 4.40 and 13.17).

The difference between the two is a highly significant 2.69% (t-statistic 8.37, not shown in the table).

A one-day window on AD can miss out some of the announcement returns. Sometimes there is

additional return in the same direction on AD-1, especially for deletions that are predictable to some extent

(stocks that no longer meet inclusion criteria), and sometimes there is additional return on AD+1 (delayed

market reaction). For this reason, we make a three-day window from AD-1 to AD+1 the workhorse of our

investigation. This three-day excess return differs even more between upward additions and pure additions,

with average value of 0.46% and 4.33% during the aggregate period (t-statistics 1.72 and 11.70).

We next look for time trends. The top panel of Figure 1 shows yearly average AD-1 to AD+1 excess

returns for upward additions and the bottom panel shows the same for pure additions. Once again, the

evidence differs between the two types of additions. For upward additions, we find a strong downward

trend in yearly average excess returns. During 2001-2009, the excess returns are positive, consistent with

previous evidence during 1989-2000 but smaller, and during 2010-2015 the returns are insignificant. The

most surprising evidence occurs during 2016-2019, when the returns are significantly negative in each year,

with average values of -1.15%, -1.55%, -4.26%, and -2.35%, despite samples of only 19, 15, 17, and 12

observations. Such evidence has not been documented before.

The bottom panel of Figure 1 shows that there is no significant trend in AD-1 to AD+1 returns of

pure additions. These average excess returns are positive each year, ranging between 1.83% and 6.98%.

Based on Figure 1 evidence, we next divide both subsamples of upward additions and pure additions into

further subsamples by time, spanning 2001-2015 and 2016-2019.

Back to Table 1, Columns (4) and (5) show that for 164 upward additions during 2001-2015 the

average excess returns over the AD-1 to AD+1 window equal 1.52%, and for 63 cases during 2016-2019

the same average excess returns equal -2.31% (t-statistics 5.03 and -6.31). Column (6) shows that the

difference of -3.84% is highly significant (t-statistic -8.04). The AD only evidence is just a little smaller in

magnitude but as significant, with average excess returns of 1.71% and -1.59% and a difference of -3.30%.

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In comparison, Columns (7), (8), and (9) show that the difference between subperiod excess returns for

pure additions is close to zero over both windows. Clearly, something has changed, and it is likely related

to the differential attraction of being included in the S&P 500 index vs. the S&P 400 index.

Table 1 also presents the return evidence for alternate measurement windows. On average, AD and

ED are apart by 5.3 trading days in our sample. If index funds trade heavily on ED, then there may be an

excess return on that day. For upward additions, the one-day average excess returns on ED are 0.16% and

0.67% during the two subperiods (t-statistics 0.83 and 3.36), and for pure additions the corresponding

returns are -0.87% and -0.39% (t-statistics -4.44 and -1.72). There is no new information on ED, and we

cannot think of a consistent story based on buying by S&P 500 index funds and/or selling by S&P 400

index funds that would explain all of these ED returns.

Table 1 shows that over AD-1 to ED window the average excess returns for upward additions equal

1.33% and -1.94% during subperiods, both significant, and similar to AD or AD-1 to AD+1 returns. On

average, AD-1 to ED window has a length of 7.3 trading days. We next examine a long AD-1 to ED+20

window, which has an average length of 27.3 trading days (5.6 weeks). The excess returns of upward

additions are insignificant over this window, likely due to the difficulty of drawing inference over a long

window.8 Wurgler and Zhuravaskaya (2002) state that reliable inference is possible only over 10 days or

so in their sample, even though they had bigger announcement returns.9 Thus, insignificant returns over

this long window should not be regarded as evidence that the addition effects are temporary.10

Finally, Table 1 also reports 252-day (one-year) buy-and-hold excess returns ending just before

AD-1 and starting just after ED+20. The prior-year excess returns average 41.64% for all upward additions,

significant at 1% level, and insignificantly different between subperiods. This shows that upward additions

occur after a strong price run-up. For pure additions, the prior-year returns are about half as large, still very

significant. The subsequent-year excess returns are close to zero in all subsamples of Table 1.

8 The daily standard deviation of excess returns during a one-year period ending on AD-2 averages 2.26% for our

aggregate sample. That implies an average standard deviation of excess returns of 2.26 × √27.3 = 11.81% over this

long window and makes it difficult to derive inference with relatively small price effects and small sample sizes. 9 Wurgler and Zhuravaskaya examine 259 additions during 1979-1989 and report an average AD return of 3.16%. 10 Although not reported in Table 1, over an AD-1 to ED+5 window (average length 12.3 trading days), average excess

returns of upward additions equal 0.85% and -1.68% during the two subperiods (t-statistics 1.50 and -3.45).

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For brevity, we do not mention in the text, but for all excess returns, we also report percent positive

cases in Table 1 and the associated statistical significance level using a binomial test. The evidence with

percent positive cases reinforces the evidence with average excess returns.

3.2. More negative returns for more recent cases

We browsed through individual cases and noticed that the announcement returns of more recent

upward additions are even more negative. Among 63 upward additions during 2016-2019, 27 occur during

January 2016 to May 2017 and 36 occur during June 2017 to December 2019. As first mentioned in the

introduction, the AD only excess returns for all 36 cases are negative, and their AD-1 to AD+1 excess

returns are negative in 34 cases. The average excess returns over these two windows equal -2.17%

and -3.35% (t-statistics -11.02 and -7.82). The corresponding returns for the 27 cases during January 2016

to May 2017 are also significantly negative -0.82% and -0.93% (t-statistics -2.36 and -1.73), but smaller.

(These sub-subperiod results are not shown in the table.) The combined evidence strongly suggests that in

recent years the market’s perception of the relative benefits of inclusion in the S&P 400 and S&P 500

indexes has changed.

3.3. Deletions from the S&P 500 index

Technically, there are as many deletions from the S&P 500 index as additions to the index before

imposing the sampling criteria. In fact, the changes begin with deletions. Historically, S&P had been

reluctant to drop stocks from their flagship index for poor return performance. During those earlier years,

most stocks were dropped because they were acquired, substantially restructured, or bankrupted. However,

this has changed, and increasingly S&P is moving stocks out of the index when they no longer meet the

minimum market value criteria.11 Of course, the acquired and bankrupted stocks are still deleted from the

index, but these are excluded from our sample.

We next examine the market reaction to stocks that are deleted from the S&P 500 index. We find

that the results for downward deletions are the mirror image of results for upward additions during both

11 From time to time, S&P may also delete stocks for other reasons, such as deletion of seven foreign stocks in 2002

following a policy change to include only U.S. stocks.

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subperiods. These results are shown in Table 2 and Figure 2. For brevity, we discuss only a few of them in

the text.

The AD only and AD-1 to AD+1 excess returns for all downward deletions during the aggregate

period are insignificant. Looking further, these returns average -0.86% and -1.19% for 79 deletions during

2001-2015, both significant (t-statistics -2.54 and -2.79). In contrast, the corresponding returns average

0.61% and 1.21% for 40 downward deletions during 2016-2019, also significant (t-statistics 1.86 and 1.92).

The differences between the two subperiod returns are highly significant. Once again, the evidence has

flipped in recent years. More importantly, these returns are the supportive mirror image of upward additions

during both subperiods. There is a consistent pattern, and that pattern suggests shifting importance of being

included in the S&P 500 index vs. the S&P 400 index.

The evidence for pure deletions also continues to contrast with that for downward deletions, which

further emphasizes the importance of considering whether a deleted stock is subsequently included in the

S&P 400 index or not. For all 61 pure deletions during the aggregate period, the AD only and AD-1 to

AD+1 average excess returns are a large negative -5.59% and -10.22%. Because only 5 of these deletions

occur during the second subperiod, the evidence for first subperiod is similar to that for the aggregate period

while it is difficult to draw meaningful inferences concerning the differences across subperiods. The last

interesting evidence concerns the average excess returns during the subsequent year, which are insignificant

during either subperiod for downward deletions, but large and significantly positive for pure deletions.

Given our focus on rebalancing between the two indexes, insignificant subsequent year’s returns during

both subperiods for upward additions as well as downward deletions suggest that their announcement

returns are not a harbinger of subsequent returns.

4. Do old hypotheses explain new results?

4.1. Price pressure hypothesis

The price pressure hypothesis was proposed by Harris and Gurel (1986) and it refers to a temporary

price effect caused by large traders the majority of whom trade in the same direction, i.e., majority of them

buying or majority of them selling soon after AD. There are two requirements for the price pressure

hypothesis to explain the opposite price effects of upward additions during the two subperiods: first, that

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there should be heavy trading activity during both subperiods, and second that during the earlier subperiod

institutional buying should dominate and during the later subperiod institutional selling should dominate.

Table 3 examines the first requirement. It presents average incremental stock turnover on select

event dates for subsamples of additions and deletions. This variable is defined precisely in the table legend.

It is essentially the increase in normalized stock turnover during an event period relative to a benchmark

period. We find that upward additions are followed by large increases in stock turnover on several days

during the event period, such as an average 361% increase on AD during the first subperiod. There is not

much difference between increased turnover on AD or ED across subperiods despite a significant increase

in indexed assets over time as shown below. However, there is a greater increase in AD+1 turnover during

the second subperiod. Table 3 also shows that increases in turnover are smaller for downward deletions

than for upward additions, but again there is no systematic difference across subperiods. Overall, tests of

incremental stock turnover provide no resolution to the opposite announcement returns of upward additions

and downward deletions during the two subperiods.

Table 4 examines the second requirement. S&P 500 index funds are forced to buy soon after both

upward additions and pure additions to minimize tracking error in their performance, and S&P 400 index

funds are forced to sell soon after upward additions for the same reason. Imagine a scenario that S&P 500

index funds own a greater proportion of their constituent stocks than S&P 400 index funds own of their

constituent stocks during the first subperiod, and that the opposite is true during the second subperiod.

Under this scenario, for upward additions, there would be net buying and a positive return during the first

subperiod and there would be net selling and a negative return during the second subperiod. It is easy to see

that this scenario would also explain the symmetric opposite returns for downward deletions during both

subperiods as well as consistently positive returns for pure additions and consistently negative returns for

pure deletions. However, Table 4 shows that this helpful scenario does not exist. Instead, S&P 500 index

funds own a greater proportion of the outstanding shares of their constituent stocks than S&P 400 index

funds own of their constituent stocks throughout 2004-2019 (period for which we could obtain data on

indexed assets from S&P Dow Jones Indices). The difference between the two proportions usually lies

between four and six percent and it is reasonably stable.

14

We infer that price pressure caused by buying and selling by index funds cannot explain our results.

Notice we have considered only trading by passive index funds in advancing this argument and not trading

by actively managed funds. That is because there is no particular reason why actively managed funds should

trade more heavily and in the same direction right around event dates and cause price pressures.

4.2. Liquidity and transaction costs

There has been an enormous decrease in transaction costs and increase in trading volume in recent

years, so we believe that this hypothesis has partly lost its relevance. Further, back to Table 3, stock turnover

increases a little subsequent to upward additions during both subperiods over an ED+21 to ED+80 window,

and the difference is not significant. Therefore, this hypothesis cannot explain opposite returns during

subperiods. In contrast, stock turnover increased for pure deletions during the first subperiod but not during

the second subperiod, and the difference was significant. Yet their announcement returns were similar

during the two subperiods. That plus similar evidence for changes in stock turnover of downward deletions

affirm our interpretation.

4.3. Investor awareness hypothesis

Additions to the S&P 500 index are significant events that are widely reported in the media. Casual

impression suggests that firms take pride in claiming this membership and analysts, investors, and lenders

consider this membership to be a factor in their decisions. Chen et al. (2004) propose the investor awareness

hypothesis to explain large positive announcement returns of additions and insignificant returns of deletions

(over a long AD to ED+60 days window) in their sample. They reason that investors become more aware

of stocks added to the index, which increases demand for those stocks. On the other hand, investors do not

easily become unaware of stocks deleted from the index that they were previously aware of, so demand for

those stocks remains unchanged. Increased demand increases prices of added stocks and unchanged demand

leaves prices of deleted stocks unchanged. Following their argument, the investor awareness hypothesis

cannot explain any negative event-study returns and therefore cannot explain our results.

15

5. Can a new twist on the old downward sloping demand curve hypothesis explain new results?

Shleifer (1986), Lynch and Mendenhall (1997), and Wurgler and Zhuravaskaya (2002) among

others argue that addition of stocks to the S&P 500 index increases demand for those stocks from passive

index funds. Due to unavailability of perfect substitutes for individual stocks, they argue that this increased

demand results in a permanent price increase of added stocks. None of these papers considers demand from

constituents other than index funds; in particular active funds (i.e., actively managed funds). In this paper,

we argue that increasing demand from active funds for S&P 400 stocks relative to S&P 500 stocks offers

some resolution to the changing announcement returns of upward additions. We refer to this shift as the

increasing attractiveness of S&P 400 stocks relative to S&P 500 stocks.

5.1. Univariate evidence on total institutional ownership

We start by examining the total institutional ownership of stocks included in the three indexes over

time. We use Refinitiv’s s34 database described in Section 2.2. Table 5 shows that for stocks belonging to

each index the total institutional ownership has risen from 1999 to 2019. Measured at the end of each year,

the average total institutional ownership of stocks belonging to S&P 500 index has risen from 63.7% in

1999 to 78.9% in 2019, a change of 15.2%. In comparison, the corresponding ownership of stocks belonging

to S&P 400 index has risen from 60.5% to 86.0%, a change of 25.5%, and that of stocks belonging to S&P

600 index has risen from 56.4% to 84.3%, a change of 27.9%. Apparently, there is not so much direct

ownership remaining in the hands of individual investors.12 The total institutional ownership of stocks that

are not included in any of the three indexes has also risen over the same period, from 24.5% to 47.8%, but

remains lower than that of stocks included in the indexes.

These results are not entirely surprising in view of the findings of Blume and Keim (2017). They

find that from 1980 to 2010 there was a pronounced shift in institutional ownership of large vs. small(er)

12 It is well known that the s34 data compiled from Section 13F filings overstate the institutional ownership to some

extent. The main reason for that is the way in which institutions are required to report their stock holdings when they

lend those holdings to other investors. Blume and Keim (2017) explain that the SEC requires the lending institution

to continue reporting that it owns the stock because it is exposed to its price risk. In addition, the ultimate buyer of

that loaned stock from the borrower is also required to report ownership of stock (if it is an institution covered by

Section 13F requirements). However, the borrower of shares (or the short-seller) in this transaction cannot report

negative ownership, which leads to double counting of shares and overstates the total institutional ownership (to

sometimes above 100%).

16

stocks. Over time, they find that institutional ownership of mid-cap stocks has become greater than that of

both large-cap and small-cap stocks (see their Figure 5). They do not consider the role of any type of S&P

index membership in institutional ownership. However, given the likely overlap between mid-cap stocks

defined by them and S&P 400 stocks, our results on the shifting balance of institutional ownership between

S&P 500 and S&P 400 stocks may be partly expected from their results. These two indexes are more

important to our study, because all except three upward additions originate from S&P 400 index, and all of

the downward deletions end up in S&P 400 index. In addition, we find similar results for S&P 600 stocks

relative to S&P 500 stocks, which we report for completeness. These last results are likely to be new relative

to the results of Blume and Keim (2017), because the smallest stocks analyzed by them include S&P 600

stocks, but many more stocks not included in any S&P index. Overall, firm size and the type of index

ownership are confounded variables, and we try to disentangle their effects in the next subsection.

On a related note, Table 4 suggests that S&P 500 stocks have higher passive institutional ownership

than S&P 400 stocks (about 5% recently) while Table 5 shows that there is an opposite trend for total

institutional ownership (about 7% recently). However, we hesitate to say that implies exactly 12% higher

active institutional ownership for S&P 400 stocks. That is because there may be additional passive

ownership by total market index funds, extended market index funds, style index funds, and Russell 1000/

2000/3000 index funds that differs between S&P 500 and S&P 400 stocks. Besides, our argument that the

negative announcement returns of upward additions reflect increasing institutional demand for S&P 400

stocks relative to S&P 500 stocks can be supported by only looking at total institutional holdings. We

believe that is a more complete implication of the downward sloping demand curve hypothesis than looking

at the demand from either passive index funds or active funds alone.

5.2. Separating the effects of S&P index membership and firm size on total institutional ownership

Following from above, Table 5 does not separate the effects of firm size and index membership on

(total) institutional ownership. That separation is important because firm size does not change by much as

a result of moving a stock from S&P 400 index to S&P 500 index, or vice versa, but index membership

does change. Below we show that the univariate relation between index membership and institutional

ownership presented in Table 5 remains highly significant after controlling for the effect of firm size.

17

Blume and Keim (2017) analyze the effect of firm size on total institutional ownership with the

following cross-sectional regression:

Total institutional ownership (%) = b0 + b1 AdjSize + b2 AdjSize2 + b3 AdjSize3 + e (1)

They define AdjSize as the log firm size in million dollars minus average of all log firm sizes across the

sample. The intercept b0 thus gives the fitted institutional ownership of a firm whose log firm size is equal

to the average of all log firm sizes. Blume and Keim find that such a cubic specification works significantly

better than a linear or a quadratic specification and it adequately fits the data. Their coefficient estimates

show that the fitted shape is an inverted curve with an inflexion point (i.e., hump) near the mid-cap size

range. Furthermore, the inflexion point moves left and closer to AdjSize = 0 over time, highlighting that

the institutional focus has shifted away from large firms and towards smaller firms over time.13

We enhance the Blume and Keim specification by adding three dummy variables as follows:

Total institutional ownership (%) = b0 + b1 AdjSize + b2 AdjSize2 + b3 AdjSize3 +

+ b4 SP500 + b5 SP400 + b6 SP600 + e (2)

SP500, SP400, and SP600 are dummy variables that take the value one for stocks belonging to the

corresponding index, and zero otherwise. The coefficients of these variables thus measure the incremental

effect of S&P index memberships on institutional ownership after controlling for the effect of firm size.

We estimate cross-sectional regression specified by Equation (2) every quarter from 1999 to 2019.

However, simple data integrity tests reveal that the Refinitiv s34 data for third and fourth quarter of 2019

are incomplete, so we stop with the second quarter of 2019.14 That gives a total 82 quarterly regressions.

However, for brevity we report the results of only 21 regressions in Table 6, Panel A, for the fourth quarter

of each year from 1999 to 2018, plus the second quarter of 2019. We report all the coefficient estimates but

omit the t-statistics because with rare exception they are all significant (likely due to large sample sizes).

13 Notice AdjSize = 0 is not mid-cap due to the much greater number of small stocks in the sample. 14 These data integrity tests examine the average institutional ownership across all stocks in our sample. In fact, the

s34 data available to us in the beginning of this experiment seemed incomplete for all quarters of 2018 and 2019,

whereupon we contacted the Refinitiv representatives. They found that our concerns were right, and they updated

2018 and 2019 data. However, our second round of data integrity tests showed that the data for third and fourth quarters

of 2019 were still incomplete, because there remained an implausible sharp decline in total institutional ownership.

Conversations with a colleague who frequently uses institutional data confirmed that it usually takes some time for

the most recent data to be fully updated. Blume and Keim (2017) also found some issues with s34 data.

18

A few preliminary inferences are as follows. First, the regressions have a great fit as shown by

adjusted-R2 values that exceed 0.5 in majority of cases. Second, the number of observations corresponding

to the number of public firms in the U.S. markets decline steadily over time. Third, the intercept increases

over time, from around 0.3 to 0.6, showing increasing institutional ownership of average size firm that is

not a member of any S&P index. Fourth, b1 is always positive and b2 and b3 are always negative, upholding

an inverted-curve relation with firm size. Fifth, the inflexion point is in the range of $4 to $11 billion without

adjusting for the trend in market values. Recall that currently the minimum firm size for inclusion in the

S&P 500 index is $8.2 billion, which means that the inflexion point that gives the fitted maximum

institutional ownership based purely on firm size is only a little above this bound.

The more important inferences for us concern the coefficients of dummy variables that capture the

incremental effects of different S&P index memberships. Some of these coefficient estimates are attributed

to ownership by passive index funds. However, despite the greater amount of passive indexing linked to

S&P 500 than to S&P 400 in Table 4, membership of the latter index has a greater effect on total institutional

ownership than membership of the former index. This is shown by the higher magnitude of b5 relative to

b4. The effect of S&P 600 index membership captured by b6 is still higher.

We note that b4, b5, and b6 all decrease over time. In other words, the incremental effect of all S&P

index memberships on total institutional ownership decreases over time. Further, the rate of decline is lower

for S&P 400 index than for S&P 500 index. We test this formally in Table 6, Panel B, by examining the

time trend in coefficient estimates. Over 82 quarters of data, b4 decreases at a rate of 0.618% per year and

b5 decreases at a rate of 0.384% per year. The difference between the two rates of decline equals 0.234%

per year, significant at 1% level. By the end of our sample period, that translates into a 5.7% higher total

institutional ownership associated with S&P 400 index membership relative to S&P 500 index membership

after controlling for the effect of firm size (calculated as difference in intercepts plus difference in rates of

decline multiplied by number of years). This shows the increasing attractiveness of the former relative to

the latter (in a multivariate setting). It means that over time, institutional owners as a group will decrease

their ownership of stocks that are moved from the S&P 400 index to the S&P 500 index. If traders anticipate

this decreased demand on the announcement date, they would lower the stock price.

19

5.3. Relating announcement returns to changes in institutional ownership

One may ask for direct evidence on whether changes in total institutional ownership of individual

stocks from before AD to after ED are related to their announcement returns. Unfortunately, tests of this

proposition face a serious challenge. Whereas index funds are required to buy added stocks or sell deleted

in the close vicinity of effective dates to reduce tracking error, active funds face no such urgency. Their

target ownership is a long-term higher or lower demand. In the short run, one could argue that they prefer

to wait, perhaps due to higher volatility surrounding changes, or because the added stocks have appreciated

significantly over the last year, or because it takes time to analyze stocks. One could also argue the opposite

that they like to trade during volatile periods when prices can deviate more from fundamentals. For these

reasons, if we try to relate announcement returns of individual stocks to changes in their institutional

ownership over a two-quarter window, we find insignificant results, which we do not report.

As an alternative to above tests, we relate yearly average announcement excess returns over AD-1

to AD+1 window for upward additions to yearly average difference in total institutional ownership of all

S&P 400 and S&P 500 stocks. This evidence is shown in the top panel of Figure 3. With 19 yearly

observations from 2001 to 2019, the regular Pearson correlation equals -0.73 and the Spearman rank

correlation equals -0.82, both significant at 1% level. The bottom panel of Figure 3 shows the evidence for

downward deletions, and the corresponding correlations equal 0.57 and 0.68, significant at 5% and 1%

levels. (Downward deletions are less numerous and there are none during 2003 and 2005, which reduces

the sample size to 17 years, and makes the red line in bottom panel not continuous.) These results support

our hypothesis that the seemingly anomalous announcement returns of stocks moving from S&P 400 to

S&P 500 index in recent years, or vice versa, can be explained, in part, by the differences in their total

institutional ownership.

5.4. Why S&P 400 stocks may be more attractive to (active) institutional managers

Last, we answer the above question that follows from our analysis. Although S&P Dow Jones

Indices LLC or its predecessor Standard & Poor’s Corp claim that future prospects of stocks do not enter

their selection process, some of their inclusion criteria are related to the future prospects of included stocks.

For example, they require that a stock be profitable over a lagged four-quarter period before inclusion, and

20

that IPO firms be listed for at least 12 months before being eligible for inclusion. We believe this makes

S&P stocks a select subset of all U.S. public stocks. Further, we believe S&P 400 stocks are a more select

subset than S&P 500 stocks, and for that reason, they may attract more attention from active institutional

money managers. This is explained as follows.

Consider year-end 2010, approximately the midpoint of our sample and somewhat removed from

the financial crisis of 2008-2009. S&P required a minimum market value of $3.5 billion, $0.85 billion, and

$0.25 billion for inclusion in the S&P 500, S&P 400, and S&P 600 indexes at that time.15 We examine the

market values of all CRSP stocks with share codes 10, 11, or 12 at the end of 2010. We find that 707 stocks

had market value higher than $3.5 billion, making them eligible for inclusion in S&P 500. That gives a type

of selectivity ratio of 500/707 = 0.71 for the large-cap index. Another 933 stocks had a market value

between $0.85 billion and $3.5 billion, which gives a selectivity ratio of 400/933 = 0.43 for the mid-cap

index, and 981 stocks had market value between $0.25 and $0.85 billion, which gives a selectivity ratio of

600/981 = 0.61 for the small-cap index. (An additional 1,752 stocks fell below $0.25 billion and were

ineligible for inclusion in any index.) We infer that S&P 400 stocks are a more select subset of eligible

stocks than S&P 500 stocks, and to a smaller extent so are S&P 600 stocks.16 We conjecture that active

institutional managers are attracted to this selectivity. This explanation is in similar spirit to versions of a

certification hypothesis advanced by Dhillon and Johnson (1991) and Denis et al (2003).17

Bellucci, Preston, and Soe (2019) offer many other arguments in favor of the S&P 400 mid-cap

index. In particular, they find that each year from 2003 to 2018, between 55% and 95% of mid-cap mutual

fund managers underperformed the S&P 400 index, based on their three-year cumulative returns (see their

Exhibit 14). Buying individual S&P 400 stocks could therefore improve the performance of the average

15 Although S&P imposes these criteria for addition of stocks to the indexes, it does not necessarily drop stocks that

fall below the threshold. At the end of 2010, the 5th percentile of the range of market values of S&P 500, S&P 400,

and S&P 600 stocks stood at $2.88 billion, $0.95 billion, and $0.18 billion, in each case lower than the threshold for

addition. 16 The selectivity ratios of S&P 500, S&P 400, and S&P 600 indexes equal 0.81, 0.60, and 0.68 at the end of 2019,

showing continuity of evidence. The ratios are higher in 2019 than in 2010 due to a general decline in the number of

listed stocks. 17 Dhillon and Johnson (1991) find that call options and bonds of added stocks also realize positive excess returns,

which they attribute to positive information implied by the S&P decision. Denis et al (2003) show that relative to

benchmarks, the added firms realize greater improvements in earnings forecasts as well as actual earnings.

21

mid-cap mutual fund manager. Such arguments from their paper combined with our evidence suggest that

S&P 400 stocks may attract greater interest from active fund managers. In turn, this can explain why upward

additions from that index to the S&P 500 index lead to negative excess returns at times.

6. Conclusion

An extensive literature has investigated the market reaction to stocks that are added to or deleted

from the large-cap S&P 500 index. Almost unanimously, this literature documents positive excess returns

upon addition and negative excess returns upon deletion, although recently a few authors have commented

on the diminishing market reaction that had become insignificant over some periods. In departure from this

previous literature, we document that the evidence has reversed in recent years, for the majority of cases

where a stock was previously or subsequently included in the mid-cap S&P 400 index. In other words

leaving S&P 400 for S&P 500 is bad news, and the opposite move is good news. This paper documents the

new evidence on returns and explores likely reasons behind it.

We examine several hypotheses proposed in previous literature and find that for the most part they

cannot explain the new evidence. Then we argue that an extension of one of these hypotheses, namely the

downward sloping demand curve hypothesis, offers a resolution. The secret lies in recognizing that it is not

just demand from passive index funds, but also the demand from active fund managers that should

determine the current market prices. We show that on combining the two sources of demand, the total

institutional ownership of S&P 400 stocks has been steadily increasing relative to that of S&P 500 stocks.

This may be due to the greater selectivity of S&P 400 stocks that can be drawn from a proportionally bigger

pool of eligible mid-cap stocks. Regardless of the reasons, anticipation of lower demand from institutional

owners upon addition of a stock to the S&P 500 index, even if in the long run, should decrease the stock

price on the announcement of change, and vice versa. Finally, we recognize that there would be other

reasons for this paradigm shift in the market reaction to S&P 500 inclusions and exclusions. Investigating

such reasons would be a fruitful topic for future research.

22

References

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applications, Research paper from S&P Dow Jones Indices.

Beneish, Messod, and Robert Whaley, 1996, An anatomy of the “S&P 500 game”: The effects of changing

the rules, Journal of Finance 51, 1909-1930.

Bennett, Benjamin, Rene Stulz, and Zexi Wang, 2020, Does joining the S&P 500 index hurt firms? Working

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Blume, Marshall, and Donald Keim, 2017, The changing nature of institutional stock investing, Critical

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Chen, Honghui, Gregory Noronha, and Vijay Singal, 2004, The price response to S&P 500 index additions

and deletions: Evidence of asymmetry and a new explanation, Journal of Finance 59, 1901-1929.

Denis, Diane, John McConnell, Alexei Ovtchinnikov, and Yun Yu, 2003, S&P 500 index additions and

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Dhillon, Upinder, and Herb Johnson, 1991, Changes in the Standard and Poor’s 500 list, Journal of Business

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Harris, Lawrence, and Eitan Gurel, 1986, Price and volume effects associated with changes in the S&P 500:

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Hegde, Shantaram, and John McDermott, 2003, The liquidity effects of revisions to the S&P 500 index: An

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Jain, Prem C., 1987, The effect on stock price of inclusion in or exclusion from the S&P 500, Financial

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Lynch, Anthony, and Richard Mendenhall, 1997, New evidence on stock price effects associated with

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Patel, Nimesh, and Ivo Welch, 2017, Extended stock returns in response to S&P 500 index changes, Review

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Pruitt, Stephen, and John Wei, 1989, Institutional ownership and changes in the S&P 500, Journal of

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Shleifer, Andrei, 1986, Do demand curves for stocks slope down? Journal of Finance 41, 579-590.

Sias, Richard, Laura Starks, and Sheridan Titman, 2006, Changes in institutional ownership and stock

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Soe, Aye, and Srikant Dash, 2008, The shrinking index effect: A global perspective, Research paper from

Standard & Poor’s Corp.

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Wurgler, Jeffrey, and Katia Zhuravskaya, 2002, Does arbitrage flatten demand curves for stocks? Journal

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Zhou, Haigang, 2011, Asymmetric changes in stock prices and investor recognition around revisions to the

S&P 500 index, Financial Analysts Journal 67, 72-84.

24

Figure 1: Excess returns of stocks added to the S&P 500 index, 2001-2019. The sample includes 227 upward additions

in the top panel (stocks that were previously included in the mid-cap S&P 400 or small-cap S&P 600 index) and 138 pure

additions in the bottom panel (stocks that were not previously included in S&P 400 or S&P 600 index). Excess returns

over a three-day window centered on AD (announcement date) are calculated as the difference between buy-and-hold

stock returns and S&P 500 index returns. We present average annual excess returns to determine the trend over time,

which is also shown by the dotted line. The slope of trend-line equals -0.287% per year for upward additions and -0.060%

for pure additions (t-statistics -6.52 and -1.05).

-5.00

-3.00

-1.00

1.00

3.00

5.00

7.00

2001 2003 2005 2007 2009 2011 2013 2015 2017 2019Per

cent

exce

ss r

eturn

Year

AD-1 to AD+1 excess returns of upward additions over time

-5.00

-3.00

-1.00

1.00

3.00

5.00

7.00

2001 2003 2005 2007 2009 2011 2013 2015 2017 2019Per

cent

exce

ss r

eturn

Year

AD-1 to AD+1 excess returns of pure additions over time

25

Figure 2: Excess returns of stocks deleted from the S&P 500 index, 2001-2019. The sample includes 119 downward

deletions in the top panel (stocks that were subsequently included in the mid-cap S&P 400 index) and 61 pure deletions

in the bottom panel (stocks that were not subsequently included in S&P 400 or S&P 600 index). Excess returns over a

three-day window centered on AD (announcement date) are calculated as the difference between buy-and-hold stock

returns and S&P 500 index returns. We present average annual excess returns to determine the trend over time, which is

shown by the dotted line. The slope of trend-line equals 0.253% per year for downward additions and 1.033% for pure

deletions (t-statistics 2.74 and 1.93). However, in many years there are very few (sometimes zero or one) deletions,

especially for the sample of pure deletions in the bottom panel.

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

2001 2003 2005 2007 2009 2011 2013 2015 2017 2019

Per

cent

exce

ss r

eturn

Year

AD-1 to AD+1 excess returns of downward deletions over time

-40.00

-35.00

-30.00

-25.00

-20.00

-15.00

-10.00

-5.00

0.00

5.00

2001 2003 2005 2007 2009 2011 2013 2015 2017 2019

Per

cent

exce

ss r

eturn

Year

AD-1 to AD+1 excess returns of pure deletions over time

26

Figure 3: Difference in institutional ownership of S&P 400 and S&P 500 and yearly average AD-1 to AD+1 excess

returns. The samples of upward additions (top panel) and downward deletions (bottom panel) are described in Tables 1

and 2. Those tables also describe calculation of excess returns. The (total) institutional ownership data are described in

Table 4. There are no downward deletions in our sample during 2003 and 2004, hence the break in trend line. The average

excess return for downward deletions in 2004 equals -2.62%. The sample of downward deletions is much smaller, hence

the greater variability in return series.

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Avg (

AD

-1,A

D+

1)

exce

ss r

etu

rn f

or

up

war

d a

dd

itio

ns

(red

lin

e)

Dif

fere

nce

in

in

st o

wn

ersh

ip o

f S

&P

40

0 a

nd

S&

P 5

00

(blu

e b

ars)

Year since 2000

Difference in institutional ownership of S&P 400 and S&P 500 stocks

and excess returns for upward additions, by year

-6.0

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Avg (

AD

-1,A

D+

1)

exce

ss r

etu

rn f

or

do

wn

war

d d

elet

ion

s

(red

lin

e)

Dif

fere

nce

in

in

sti

ow

ner

ship

of

S&

P 4

00

an

d S

&P

50

0

(blu

e b

ars)

Year since 2000

Difference in institutional ownership of S&P 400 and S&P 500 stocks

and excess returns for downward deletions, by year

27

Table 1

Excess returns surrounding the addition of stocks to the S&P 500 index, 2001-2019

The initial sample of additions to the S&P 500 index with effective date (ED) during 2001-2019 is retrieved from the Compustat Index Constituents file. For each

added stock, we examine news items on Factiva up to one month before ED to ascertain the conditions surrounding the addition and the first date when the news of

addition appears in the press (usually after trading hours). Announcement date (AD) is the first trading day after the first news date. We apply the following criteria

for including an added stock to our sample: 1. AD is available and precedes ED. 2. The S&P 500 index funds would be required to buy the stock. In a few cases, an

S&P 500 firm spins off a subsidiary that is also included in the index, but S&P 500 index funds would not be required to buy that stock that they receive as a distribution,

so we exclude such stocks. Similarly, in a few cases, an existing S&P 500 stock is restructured and listed as an addition, which we exclude. 3. Stock return data are

available from CRSP for at least one month before AD and one month after ED (although we make an exception for five stocks that were included during December

2019 even though we have CRSP data only until the end of that month). Upward additions are those in which a stock now added to the S&P 500 index was previously

included in the S&P 400 index (224 cases) or S&P 600 index (3 cases), and pure additions are those in which a stock was previously not included in any S&P index.

Excess return over any measurement window is calculated as the difference between buy-and-hold stock return and S&P 500 index return over that window. In each

cell, the first number shows the mean excess return, the second number in parentheses shows the t-statistic and its significance level, and the third number (if any)

shows fraction positive and the significance level for its being different from 0.50. The t-statistic of the difference between mean excess returns is calculated assuming

unequal standard deviations of the two populations. Superscripts a, b, and c show statistical significance at 10%, 5%, and 1% levels.

Measurement

window

All additions,

all years

Upward additions (S&P 400/600 to S&P 500) Pure additions (outside S&P 1500 to S&P 500)

All years

Subperiod 1

2001-2015

Subperiod 2

2016-2019

Difference

between

subperiods All years

Subperiod 1

2001-2015

Subperiod 2

2016-2019

Difference

between

subperiods

Column number (2) (3) (4) (5) (6) (7) (8) (9) (10)

N 365 227 164 63 138 113 25

AD(-253,-2) 34.11

(11.51)c

0.82 c

41.64

(9.69)c

0.86 c

38.01

(10.91)c

0.85 c

51.09

(4.07)c

0.90 c

13.08

(-1.00)

21.73

(6.96)c

0.75 c

22.58

(6.17)c

0.77 c

17.84

(3.66)c

0.68 a

-4.74

(-0.78)

AD only 1.82

(10.98)c

0.71 c

0.80

(4.40)c

0.62 c

1.71

(8.76)c

0.81 c

-1.59

(-7.83)c

0.13 c

-3.30

(-11.72)c

3.49

(13.17)c

0.86 c

3.47

(11.46)c

0.85 c

3.55

(6.83)c

0.92 c

0.08

(0.13)

AD-1 to AD+1 1.92

(8.08)c

0.69 c

0.46

(1.72)a

0.57 b

1.52

(5.03)c

0.73 c

-2.31

(-6.31)c

0.17 c

-3.84

(-8.07)c

4.33

(11.70)c

0.88 c

4.37

(10.16)c

0.87 c

4.15

(6.47)c

0.96 c

-0.21

(-0.27)

ED -0.11

(-0.91)

0.47

0.30

(1.99)b

0.56 a

0.16

(0.83)

0.54

0.67

(3.36)c

0.63 b

0.51

(1.82)a

-0.78

(-4.72)c

0.31 c

-0.87

(-4.44)c

0.31 c

-0.39

(-1.72)a

0.32 a

0.47

(1.57)

AD-1 to ED 2.06

(6.16)c

0.62 c

0.42

(1.00)

0.49

1.33

(2.40)b

0.62 c

-1.94

(-5.32)c

0.17 c

-3.27

(-4.94)c

4.75

(10.28)c

0.83 c

5.03

(9.23)c

0.81 c

3.46

(5.77)c

0.92 c

-1.58

(-1.95)a

AD-1 to ED+20

(average length 27.3

trading days)

0.73

(1.56)

0.53

-0.33

(-0.61)

0.48

-0.16

(-0.23)

0.51

-0.80

(-1.10)

0.40

-0.65

(-0.65)

2.44

(2.85)c

0.62 c

2.35

(2.37)b

0.63 c

2.80

(1.91)a

0.56

0.45

(0.25)

ED+21 to ED+272 0.74

(0.47)

0.48

1.09

(0.53)

0.45

2.14

(0.90)

0.45

-1.88

(-0.47)

0.43

-4.02

(0.87)

0.17

(0.07)

0.52

1.02

(0.36)

0.51

-3.66

(-0.65)

0.48

-4.67

(-0.75)

28

Table 2

Excess returns surrounding the deletion of stocks from the S&P 500 index, 2001-2019

The sample of deletions from the S&P 500 index starts the same way as the sample of additions to the S&P 500 index as described in Table 1. Effective date (ED) of

deletion is the first day when the stock is not a part of the S&P 500 index. Announcement date (AD) is the first trading day after the news of deletion first appears in

Factiva (usually after trading hours). We impose criteria similar to those listed in Table 1. In particular, we require that stock return data should be available from

CRSP for at least one month before AD and one month after ED (although we make an exception for five stocks deleted during December 2019 even though CRSP

data is available only until the end of that month). This data requirement excludes stocks that were deleted from the S&P 500 index because of acquisition shortly after

ED by another firm, a private equity firm, or a management group. It also excludes stocks that were deleted because of an imminent bankruptcy shortly after ED or a

substantial restructuring leading to creation of a new firm. Downward deletions are those in which a stock deleted from the S&P 500 index is subsequently included

in the S&P 400 index, and pure deletions are those in which a stock is not subsequently included in any S&P index. Excess return over any measurement window is

calculated as the difference between buy-and-hold stock return and S&P 500 index return over that window. In each cell, the first number shows the mean excess

return, the second number in parentheses shows the t-statistic and its significance level, the third number (if any) shows fraction positive and the significance level for

its being different from 0.50. The t-statistic of the difference between mean excess returns is calculated assuming unequal standard deviations of the two populations.

Superscripts a, b, and c show statistical significance at 10%, 5%, and 1% levels.

Measurement

window

All deletions,

all years

Downward deletions (S&P 500 to S&P 400/600) Pure deletions (S&P 500 to outside S&P 1500)

All years

Subperiod 1

2001-2015

Subperiod 2

2016-2019

Difference

between

subperiods All years

Subperiod 1

2001-2015

Subperiod 2

2016-2019

Difference

between

subperiods

Column number (2) (3) (4) (5) (6) (7) (8) (9) (10)

N 180 119 79 40 61 56 5

AD(-253,-2) -25.04

(-9.83)c

0.23 c

-23.74

(-8.11)c

0.20 c

-16.25

(-4.28)c

0.30 c

-38.53

(-11.28)c

1.00 c

-22.28

(-4.36)c

-27.57

(-5.62)c

0.28 c

-29.32

(-5.76)c

0.27 c

-8.02

(-0.45)

21.29

(1.14)

AD only -2.12

(-3.84)c

0.39 c

-0.37

(-1.43)

0.44 c

-0.86

(-2.54)b

0.33 c

0.61

(1.86)a

0.65 a

1.47

(3.12)c

-5.59

(-3.80)c

0.28 c

-6.15

(-3.88)c

0.24 c

0.59

(1.16)

0.80

6.74

(-4.05)c

AD-1 to AD+1 -3.71

(-4.05)c

0.42 b

-0.38

(-1.04)

0.48

-1.19

(-2.79)c

0.38 b

1.21

(1.92)a

0.68 b

2.40

(3.16)c

-10.22

(-4.23)c

0.31 c

-10.71

(-4.14)c

0.29 c

-4.73

(-0.87)

0.60

5.97

(0.99)

ED 0.99

(1.64)

0.53

0.36

(1.14)

0.51

0.61

(1.42)

0.54

-0.14

(-0.34)

0.45

-0.74

(-1.27)

2.24

(1.33)

0.57

2.47

(1.37)

0.56

-0.37

(-0.09)

0.60

-2.85

(0.64)

AD-1 to ED -4.81

(-4.13)c

0.41 b

-1.34

(-1.69)a

0.49

-2.14

(-1.96)a

0.43

0.23

(0.26)

0.60

2.38

(1.66)a

-11.59

(-4.00)c

0.25 c

-12.19

(-3.90)c

0.23 c

-4.86

(-1.19)

0.60

7.33

(1.42)

AD-1 to ED+20 -1.91

(-1.14)

0.43 a

-0.95

(-0.72)

0.47

-0.29

(-0.16)

0.52

-2.37

(-1.56)

0.35 a

-2.08

(-0.88)

-3.71

(-0.89)

0.36 b

-5.80

(-1.42)

0.36 b

19.67

(0.93)

0.40

25.47

(1.18)

ED+21 to ED+272 13.54

(2.04)b

0.48

-3.55

(-0.76)

0.40 b

-0.72

(-0.12)

0.43

-9.61

(-1.27)

0.32 b

-8.89

(-0.93)

46.59

(2.82)c

0.63 b

52.00

(2.92)c

0.65 b

-12.94

(-1.14)

0.40

64.95

(3.08)c

29

Table 3

Average incremental stock turnover relative to a benchmark period for additions to and

deletions from the S&P 500 index

The samples of additions to and deletions from the S&P 500 index are described in Tables 1 and 2, which also define

announcement date (AD), effective date (ED), upward additions, pure additions, downward deletions, and pure deletions.

For each trading day, we first calculate stock turnover as its dollar trading volume reported on CRSP divided by market

value of its outstanding shares. Second, we calculate market turnover as market value weighted average turnover for all

NYSE-listed stocks that day. Third, we divide the daily stock turnover by the NYSE turnover each day to calculate the

stock turnover ratio (which adjusts for fluctuations in market-wide turnover). Fourth, we calculate the benchmark stock

turnover ratio by averaging over a 60-day period ending on AD-2. Fifth, over a given measurement window, we calculate

incremental stock turnover as the average stock turnover ratio divided by the benchmark stock turnover ratio, minus one.

The table below reports the average incremental stock turnover calculated across all stocks in a given sample and its t-

statistic. The t-statistic of difference between average incremental stock turnovers over two subperiods is calculated

assuming unequal standard deviations. Superscripts a, b, and c show statistical significance at 10%, 5%, and 1% levels.

Measurement window

Upward additions Pure additions

Subperiod 1

2001-2015

Subperiod 2

2016-2019 Difference

Subperiod 1

2001-2015

Subperiod 2

2016-2019 Difference

N 156 56 94 23

AD 3.61

(5.98)c

3.13

(3.59)c

-0.49

(-0.46)

4.10

(7.77)c

4.54

(6.19)

0.45

(0.49)

AD+1 3.00

(5.20)c

8.08

(4.08)c

5.08

(2.46)b

2.97

(3.44)c

7.67

(3.20)c

4.70

(1.85)a

ED 1.46

(7.57)c

1.44

(11.26)c

-0.02

(-0.09)

2.40

(8.56)c

1.63

(5.71)c

-0.77

(-1.93)a

ED+21 to ED+80 0.10

(4.17)c

0.17

(3.90)c

0.07

(1.04)

0.20

(3.03)c

-0.03

(-0.49)

0.23

(2.52)b

Window Downward deletions Pure deletions

Subperiod 1

2001-2015

Subperiod 2

2016-2019 Difference

Subperiod 1

2001-2015

Subperiod 2

2016-2019 Difference

N 79 38 54 4

AD 0.99

(7.13)c

0.88

(2.30)b

-0.11

(-0.26)

3.32

(3.48)c

1.15

(1.16)

-2.17

(-1.58)

AD+1 1.41

(3.11)c

1.93

(2.46)b

0.52

(0.57)

2.39

(4.28)c

3.31

(1.10)

0.91

(0.30)

ED 1.82

(6.70)c

1.07

(3.89)c

-0.75

(-1.93)a

2.01

(6.32)c

2.40

(2.03)b

0.39

(0.32)

ED+21 to ED+80 0.08

(1.26)

0.07

(1.41)

-0.01

(-0.17)

0.19

(1.63)

-0.27

(-4.85)c

-0.45

(-3.57)c

30

Table 4

S&P indexed assets over time

At the end of each year, S&P Dow Jones Indices (S&P DJI) estimates the total assets indexed to its large-cap S&P 500,

mid-cap S&P 400, and small-cap S&P 600 indices, using both industry data and a questionnaire sent to a variety of asset

owners. They describe that indexed assets represent assets in institutional funds, ETFs, retail mutual funds, and other

investable products that seek to replicate or match the performance of the respective indexes. They provided this

information to us from 2004 onwards. We further estimate the total market value of equity of all firms included in the

respective indices as of year-end using Compustat Index Constituents file. The ratio of indexed assets to total market

value of equity of all firms multiplied by 100 gives the percent values reported in the three columns before last. These

percent values exclude holdings of constituent stocks by index funds of other kinds, such as total market index funds,

extended market index funds, Russell 1000, 2000, or 3000 index funds, etc.

Year

Indexed assets in billion dollars

Percent of total market value of equity of

all firms included in respective indexes

held by index funds

Difference between

S&P 500 and S&P

400 percent

ownership S&P 500 S&P400 S&P 600 S&P 500 S&P400 S&P 600

2004 1,109 64 32 9.9 5.9 6.1 4.0

2005 1,261 75 36 10.7 6.4 6.3 4.3

2006 1,316 71 36 9.9 5.8 5.8 4.1

2007 1,470 68 33 10.9 5.6 5.8 5.3

2008 915 42 19 11.1 5.8 5.4 4.3

2009 1,102 67 23 10.7 7.0 5.3 3.7

2010 1,318 80 27 11.0 6.8 5.1 4.2

2011 1,484 81 23 12.4 7.3 4.6 5.1

2012 1,576 94 26 11.6 7.4 4.6 4.2

2013 1,878 98 31 10.9 6.1 4.0 4.8

2014 2,157 119 33 11.2 7.1 4.4 4.1

2015 2,145 112 34 11.3 7.3 4.9 4.0

2016 2,955 133 62 14.4 7.7 7.7 6.7

2017 3,411 157 78 14.0 8.3 9.1 5.7

2018 3,612 173 74 15.9 10.9 10.1 5.0

2019 4,590 211 90 16.1 10.7 10.2 5.4

31

Table 5

Average total institutional ownership by the type of S&P index fund

We retrieve institutional ownership data for all stocks from Refinitiv’s (formerly Thomson-Reuters) s34 database. This

database gives institutional ownership of each stock by all managers at the end of each quarter, which we sum to obtain

the total institutional ownership for that stock. We obtain the subset of stocks that are listed on CRSP database and for

which institutional ownership is available. Using Compustat Index Constituents file, we next attach an S&P index code

to each stock depending on whether it was included in the S&P 500, S&P 400, or S&P 600 index, or none of these at that

quarter-end. We winsorize the institutional data each quarter at 1 and 99 percent levels. The table below gives the average

total institutional ownership at year-end for stocks belonging to each index code. The Refinitive s34 data for third and

fourth quarters of 2019 is incomplete, so for 2019 only we substitute data as of second quarter-end in place of year-end.

Year

Average total institutional ownership (%)

S&P 500 S&P 400 S&P 600 Not in S&P 1500

1999 63.7 60.5 56.4 24.5

2000 64.7 62.8 59.2 24.1

2001 66.7 68.3 66.6 25.9

2002 69.2 69.5 70.1 28.0

2003 71.8 73.4 74.4 32.5

2004 75.3 78.7 79.5 36.2

2005 75.6 79.6 81.7 39.3

2006 78.2 83.5 86.4 42.1

2007 81.4 87.1 89.3 44.6

2008 78.8 82.8 82.1 41.3

2009 77.7 81.4 80.8 40.3

2010 77.0 81.8 81.1 41.9

2011 71.0 76.5 75.3 40.6

2012 73.0 79.3 76.3 41.9

2013 76.1 80.5 78.1 43.9

2014 76.1 82.4 78.9 44.9

2015 78.5 84.3 81.8 48.3

2016 79.8 86.8 84.1 49.1

2017 79.6 86.3 84.6 48.5

2018 77.1 84.5 82.9 46.2

2019 78.9 86.0 84.3 47.8

32

Table 6

Incremental effect of different index memberships on total institutional ownership

Panel A of this table shows results of year-end cross-sectional regressions of total institutional ownership of all CRSP stocks with share code 10, 11, or 12 (ordinary

common shares) for which institutional ownership data are available from Refinitiv’s s34 database. We start with Blume and Keim (2017) regression specification of

institutional ownership that only includes firm size variables and add dummies for membership of S&P 500, S&P 400, and S&P 600 indexes. Specifically, each quarter-

end, we carry out the following regression:

Total institutional ownership (%) = b0 + b1 AdjSize + b2 AdjSize2 + b3 AdjSize3 + b4 SP500 + b5 SP400 + b6 SP600 + e

AdjSize is defined as log firm size in million dollars minus average of log firm size across all observations in a quarter. SP500, SP400, and SP600 are dummy variables

that take the value one for stocks belonging to the corresponding index, and zero otherwise. Although the regression is carried out each quarter, for brevity we report

results only for the fourth quarter. For 2019 only, the third and fourth quarter’s data are defective, so we report second quarter’s results instead. Inflexion point shows

the market value in million dollars for which the effect of firm size on total institutional ownership is maximized. Given large sample sizes, almost all t-statistics are

highly significant, so we do not report them.

Panel B of this table further regresses quarterly coefficients of SP500, SP400, and SP600 dummies on time measured in years. T-statistics in this table are shown in

parentheses. Superscripts a, b, and c show statistical significance at 10%, 5%, and 1% levels.

Panel A: Cross-sectional regressions of total institutional ownership (shown only for fourth quarter)

Coefficients Inflexion point

in $ million Year N Intercept AdjSize AdjSize2 AdjSize3 SP500 SP400 SP600 Adj-R2

1999 6525 29.6 7.16 -0.37 -0.12 22.0 19.5 21.9 0.468 7018

2000 6262 30.0 8.37 -0.17 -0.15 17.4 17.0 21.8 0.536 8057

2001 5691 33.2 9.64 -0.20 -0.20 14.7 17.5 25.4 0.566 7613

2002 5286 36.5 9.50 -0.48 -0.20 18.3 18.1 26.8 0.562 4520

2003 5052 42.1 10.41 -0.86 -0.21 16.5 17.1 27.0 0.549 5969

2004 5059 47.3 11.76 -1.03 -0.25 13.9 16.2 26.9 0.556 6714

2005 4950 51.1 12.17 -1.12 -0.24 9.6 12.9 25.4 0.547 7240

2006 4926 54.5 11.71 -1.35 -0.23 12.2 15.3 27.5 0.538 6790

2007 4830 57.0 11.13 -1.26 -0.21 13.6 17.3 29.3 0.514 6573

2008 4556 53.0 9.85 -0.87 -0.21 15.2 17.9 25.9 0.518 4102

2009 4283 54.0 11.43 -1.02 -0.24 9.6 13.2 24.1 0.581 6723

2010 4089 56.5 11.85 -1.24 -0.27 8.0 11.7 22.8 0.582 7407

2011 3799 53.3 10.66 -1.08 -0.20 4.9 10.7 20.3 0.396 7948

2012 3726 54.8 11.40 -1.03 -0.22 3.3 11.0 19.6 0.419 9969

2013 3780 56.3 10.91 -1.31 -0.18 7.8 11.5 18.8 0.430 10374

2014 3920 59.3 10.97 -1.36 -0.18 5.2 10.8 17.7 0.451 11075

2015 3825 62.1 11.10 -1.36 -0.17 4.7 9.4 17.8 0.474 10032

2016 3697 64.0 10.39 -1.44 -0.16 6.8 11.1 17.8 0.534 9596

2017 3684 63.3 9.68 -1.47 -0.14 9.1 12.5 19.8 0.549 10061

2018 3970 59.1 9.30 -1.23 -0.14 9.5 14.8 21.9 0.536 9574

2019 3993 61.1 9.43 -1.29 -0.13 9.4 14.3 22.0 0.538 10735

33

Panel B: Regressions of the coefficients of SP500, SP400, and SP600 dummy variables from Panel A on time in years since 1998 end

Regressions of Difference

Variable

Coefficient of

SP500

Coefficient of

SP400

Coefficient of

SP600

SP400 vs. SP500

SP600 vs. SP500

Intercept 17.3

(30.57)c

18.3

(45.07)c

26.4

(38.83)c 1.0

(1.39)

9.1

(10.29)c

Time in years since 1998 end -0.618

(-13.06)c

-0.384

(-11.33)c

-0.331

(-5.82)c 0.234

(4.02)c

0.287

(3.88)c

N 82 82 82

Adjusted-R2 0.68 0.61 0.29