Short Selling on the NYSE
James J. Angel
Georgetown University
Room G4 Old North
Washington, D.C. 20057
(202) 687-3765
Current Draft: October 27, 1997
I wish to thank seminar participants at NYU, Georgetown University, and the Financial
Management Association meetings for helpful comments, and I wish to thank Georgetown
University and the Georgetown University Center for Business and Government Research for
funding assistance.
Short Selling on the NYSE
Abstract:
Despite centuries of controversy, little has been known about who engages in short selling and the
impact of short sales on stock prices. Index arbitrage trades represent a much higher percentage of
short sales than regular sales, while individuals do relatively less short selling, except in the smaller
stocks. The uptick rule impedes short sales over 90 percent of the time and reduces the number of
short sale orders during periods of rapid price decline. Short sales have less impact than regular short
sales on subsequent bid quotes and the same impact on offer quotes.
Short Selling on the NYSE
He that sells what isn't his'n,
Must buy it back, or go to prison.
- Daniel Drew, circa 1875 (via White (1910, page 180))
Short selling, the sale of a security for which delivery is made with a borrowed security, has
long been controversial in financial markets. Many short sellers engage in the practice to profit from
an anticipated decline in price, but this is not necessarily the case for all short sales. Market makers
often short stock as part of their normal market making activities. Some short sellers may be hedging
the price risk of long positions in other assets such as convertible securities. Others may be
arbitraging price differences between cash stocks and stock index futures contracts. Still others may
be shorting securities that they already own (shorting "against the box"), for tax purposes.1
Despite the long controversy over short selling, along with outright bans or other restrictions
on the practice, little is known about who actually engages in short selling and what impact short sales
have on financial markets. This paper documents several interesting features of short sales. Contrary
to the image of the bearish speculator, index arbitrage and program trading activity comprise almost
half of the short orders placed and over a third of the short order volume placed through the NYSE
SuperDot system. Individuals generally engage in less short selling than other investor types.
Even though short selling comprises approximately eight percent of total reported sales
(NYSE (1996)), little is known about how the short sale process affects security prices. Does a short
1
sale convey more or less information than a regular sale? It is tempting to think that short sellers may
be better informed than other investors, and that, measured by the impact on price, a short sale should
convey more information than a regular sale does. However, the opposite is true: short sale orders
have the same or significantly less effect on subsequent quotes and trades than do regular sale orders.
Little has also been known about the empirical impact of the uptick rule, which prohibits short
sales at prices lower than the previous trade. This study documents that it allows an immediate market
short sale only an average of 6.8 percent of the time, and that it does indeed seem to result in less
short sales during periods of rapid market decline.
The next section chronicles some of the historic and current restrictions on short selling and
then looks at previous academic research. Section II describes the NYSE order data used for this
study, while Section III describes the results.
I. The History of Short Selling: Restrictions and Prior Research
A. Restrictions on Short Selling
Traditionally, critics of short selling have blamed it for destabilizing stock prices and causing
price declines, especially by facilitating "bear raids." As NYSE economist J. Edward Meeker (1932,
page 115), points out, "The agitation against short selling of securities seems a perennial affair, and
naturally exhibits itself most strongly after some panic or sharp break in prices has occurred." This
observation holds true for the current era, in which the 1991 crash of the Japanese market gave rise
to complaints about short selling by foreign institutions, as reported by Wada (1992).
Other arguments against the practice, on moral grounds, assert that selling what is not owned
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is wrong, or that short selling is just a form of gambling.2 This moral distrust of the practice along
with the fear that it disrupts markets have led to numerous attempts to ban or restrict short selling.
As far back as 1610, the Dutch banned short selling at the request of the East India Company, which
blamed short selling for declines in its share price.3 The law was widely flouted, so in 1689 the Dutch
government instead imposed a tax on the profits from short sales. In the 18th and 19th centuries,
short selling was banned at various times in England, France, and Germany. Again, these rules were
seldom enforced, and traders found that they could easily evade them. In the United States in 1812,
New York State imposed an ineffective ban on short sales. Curiously enough, even though laws had
been enacted for over 200 years against selling securities that were not owned, the phrase short
selling did not come into use until the 1850s, according to Zweig (1991).
During World War I, the warring powers banned short selling on their stock exchanges, both
to prevent enemy agents from disrupting security markets and to prevent speculative excesses. In
September 1931, the turmoil surrounding England's decision to abandon the gold standard led the
NYSE to ban short selling, but it reversed the ban after only two days. During the financial
convulsions of the 1930s, there was widespread debate on the merits of short selling, culminating in
the issuance of Rules 10a-1 and 10a-2 by the Securities and Exchange Commission. The "uptick"
rule prohibits a short sale in an exchange-listed stock if it would result in a price lower than the last
trading price.4 But this rule, too, can be avoided, through overseas trading or through trading in
options.5 The original uptick rule did not apply to OTC or Nasdaq stocks. Recently the SEC (1994)
approved an experimental "bid-test" rule for Nasdaq stocks that prohibits short sales at prices at or
below the inside bid when that price is lower than the previous inside bid.
Short selling is still generally restricted in Asia, according to Evans (1993). Short selling is
3
possible for Japanese securities, but much of the lendable supply of Japanese securities is held outside
Japan. Restrictions on short selling have just been relaxed in Hong Kong; most Asian nations,
however, still severely restrict it.
In addition to the uptick rule in the United States, a variety of other regulations restrict short
selling. In general, retail investors do not earn interest on the proceeds of short sales, and must post
additional margin to protect the lenders of securities from losses.6 Larger investors can negotiate
partial use of the proceeds. The brokerage firm will keep part of the interest on the proceeds to cover
its expenses, which include fees paid to the lender of the securities. Stock lending fees vary according
to the relative scarcity of the security. A large and liquid U.S. stock such as ATT may command a
fee of about 10-20 basis points of the value, while a foreign equity may cost 300 or more basis
points.7
The supply of securities available for shorting can also be problem, especially for institutional
investors who wish to trade in size. Much of the supply of securities available for lending comes from
brokerage firm margin accounts. Thus, stocks that are not marginable under Federal Reserve rules
may be more difficult to find.8 Hansell (1992) reports that only about 600 to 800 stocks out of a
universe of 6,000 domestic stocks are readily available for borrowing in the amounts sought by
institutional investors. Some issues that are popular among short sellers may be particularly Ahard-toborrow@ as described by Kansas (1994). Tax rules can also impede the process, especially in
countries that impose dividend withholding taxes, since in those countries the shorts may be
responsible for the gross dividend instead of the net dividend.9
Furthermore, numerous investors are prohibited from making short sales. The charters of
many mutual funds and closed-end investment companies prohibit short sales. Pension plans
4
governed by ERISA may worry that short investments will not be considered "prudent" and avoid
them. One might expect that these restrictions on short selling by institutions would leave individuals
and brokerage firms trading for their own accounts the major short sellers. Individuals, however, also
face restrictions: short sales are generally prohibited in IRA accounts, and individuals usually do not
earn interest on the proceeds of their short sales. Thus, it is an empirical question as to which type
of investors are most active on the short side of the market.
B. Previous Research on Short Selling
Despite the centuries of controversy, there has been surprisingly little empirical work on short
sales, although much theoretical work has explored the implications for asset pricing models of
restrictions on short selling.10 Although market lore suggests that many apparent inefficiencies in the
market are caused by the restrictions on short selling, Diamond and Verrecchia (1987) demonstrate
theoretically that restrictions on short selling do not bias prices upward.11 Miller (1977, 1987, 1990),
on the other hand, claims that short sale restrictions lead to upward biases in security prices: Since
investors have differences of opinion, prices will be set by the most optimistic investors. Short sale
restrictions keep the most pessimistic investors from trading upon their beliefs, biasing prices upward.
Despite a scarcity of relevant data, over the years there have been some empirical studies on
short selling. Macaulay and Durand (1951) use NYSE data from the 1930s to investigate the impact
of short selling on prices. They conclude that short selling did not cause advances or declines in the
overall market, but that a large increase in the short position for a given stock was correlated with
greater price volatility for the stock. Most of the published studies have used the information on
short interest in individual stocks which is published once a month in the Wall Street Journal, and is
5
also contained in Standard and Poor's Daily Stock Price Record.12 Figlewski (1981) constructs
portfolios based on this data for 414 of the S&P 500 companies from 1973 to 1979 and finds that the
portfolios with high short interest positions produced substantially lower returns than did the
portfolios with low short interest positions. Asquith and Meulbroek (1995) also find that higher short
interest is associated with lower subsequent returns. Peterson and Waldman (1984) combine the short
interest data with IBES data and conclude that differences of opinion, as expressed in the dispersion
of earnings forecasts, lead to increases in short selling. Brent, Morse, and Stice (1990) find that high
beta stocks and stocks with options or convertible debt have higher levels of short interest, and that
a seasonal pattern occurs that is "weakly consistent" with tax-loss selling. They find that changes in
short interest do not help to explain stock returns in the following month. Choie and Hwang (1994)
also use the short interest data and find that stocks with relatively large short interest underperform
the S&P 500 ten days prior to the publication of the information and for 20 days afterward.
Woolridge and Dickenson (1994) find that short sellers do not earn abnormal returns and provided
additional by increasing short positions when markets were going up.
The Securities and Exchange Commission (1963, 1976) has conducted its own studies from
time to time on short sales. The Commission's 1963 Special Study concludes that the uptick rule does
not prevent short sellers from selling in a down market, since there are enough upticks even in a down
market for significant short activity to occur. The study recommends stronger restrictions on short
selling. However, in 1976 the SEC proposed an experiment (which was never conducted) of
temporarily abolishing the uptick rule to see what would happen. Former SEC commissioner Irving
Pollack (1986) conducted a study for the NASD, finding that short interest in Nasdaq securities is
usually lower than for exchange-listed stocks, and that short interest represented less than one percent
6
of the outstanding shares for about 80 percent of all Nasdaq stocks, as opposed to about 76 percent
for exchange-listed stocks.
Other empirical work has used data on aggregate short positions, in particular the specialists'
short sales ratio, which is the ratio of short sales by stock exchange specialists to all short sales,
published weekly in Barrons' "Market Laboratory."13 Reilly and Whitford (1982) find no predictive
power in the specialists' short sales ratio, although Bowlin and Rozeff (1987) claimed that average
stock returns are higher in periods following low values of the ratio than in periods following lower
values. Bhattacharya and Gallagher (1991) also apply causality tests to the specialists' short sales
ratio and find that short sales by specialists lead other short sales, but that because of the time lag in
publication, other investors cannot profit from this information.
The NYSE (1996) itself publishes a few statistics about short selling in its annual Fact Book.
Short sales represent about 8.1 percent of reported 1995 sales volume. Member firms (including
specialists) trading for their own accounts accounted for 53.7 percent of these short sales and
specialist firms made 36.2 percent of them. However, the Fact Book provides little beyond these
broad statistics.
II. Data on Short Sale Orders Submitted to the NYSE
This study of short selling uses SuperDot orders from the NYSE TORQ database that
identifies which orders were short. The database contains data for 144 NYSE firms from November
1, 1990 through January 31, 1991. These firms comprise approximately 15 firms from each market
capitalization decile of the NYSE. The data include not only the trades and quotes familiar to
7
microstructure researchers through the ISSM database, but also information on orders that were
transmitted to the NYSE through the electronic SuperDot system. The order information contains
the time each order was placed; whether the order was to buy, sell, sell short, or cancel a previous
order; the order size in number of shares, the limit or stop price if applicable; and information
identifying the account type that placed the order.14 Furthermore, the file contains the execution
history of each order: whether the order was executed, and if so when, as well as the price and
number of shares of each part of the order. This study seeks to document facts about the effects of
these short sales. The questions asked include: Who places short orders? How do short orders differ
from other sales? What is the price impact of a short order and how does it compare with a regular
sale?
In addition to regular buy and sell orders, the data set identifies short orders, and includes
tick-sensitive orders such as buy-minus and sell-plus orders.15 Short sales exempt from the short-sale
restrictions, such as short sales by odd-lot dealers, are also identified. Contrary to widespread belief,
neither trades by the NYSE specialist nor most trades by index arbitrageurs, are exempt from the
uptick rule.16
This data also reveal the account type which placed each order, although the specific identity
of each trader is not revealed. Specifically, the data identifies whether an order is for an individual,
a proprietary order for the account of the brokerage firm, or an agency order in which the brokerage
firm is an agent for an institutional investor or another brokerage firm. Accounts engaged in index
arbitrage or other program trading are also identified. This information is missing for approximately
six percent of the orders. Appendix 1 contains a more complete description of the account type
information.
8
These results are for orders placed through the NYSE SuperDot system and do not reflect
orders handled outside the SuperDot system, such as orders hand processed on the NYSE floor or
orders sent to regional exchanges. Since the size of orders that can be handled through the SuperDot
system is limited, the orders studied here are smaller than average NYSE orders. Conversations with
specialists on the New York, Boston, and Pacific stock exchanges revealed no evident pattern of bias
in the types of short orders that are executed through the SuperDot system, although the regional
specialists indicated they did not see many short orders.
It should be noted as well that the order file contains orders that were sent to the NYSE as
opposed to actions by the NYSE specialist; thus short sales made by the specialist are not included.
The short sale orders examined here represent a relatively pure and homogeneous set of nonspecialist orders that have not been subject to special handling like large orders that are "worked" on
the floor.
One potential problem with the data is that some trades marked as short sales may not
actually have been short sales. Some firms with multiple trading desks may not know for certain if
they are net long or short, and they may mark some sell trades as short so that they do not run afoul
of the identification requirements for short sales and the uptick rule. Other investors may want to sell
stock only on an uptick and so mark the trade as a short sale, even though they fully intend to deliver
stock that they own for settlement. Although it is possible to enter such a tick-sensitive order as a
sell-plus order, at that time the software systems at some firms could not handle sell-plus orders. For
these reasons, the number of short sales reported may overstate the true number of short sales
conducted on the NYSE.
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III. Results
This study addresses the following areas:
A. Identities of Short Sellers
The account type data indicate that index arbitrage orders were a larger fraction of short
orders than of overall orders, and that individuals were under represented in the ranks of the short
sellers. All of the 674,405 regular way orders in the TORQ database were examined for all 144 firms
in the database. Table I presents frequency breakdowns of the orders, by order and customer type,
and Table II presents the results for volume. Short sales were 4.8 percent of the total SuperDot
orders (6.8 percent of order volume) submitted to the NYSE, which is 10.2 percent of the total sell
orders (13.8 percent of total sell volume). Note that exempt short sales were a negligible fraction
(.09 percent) of the total SuperDot sale orders. Over one-third of the short orders and over onefourth of the short volume were a result of index arbitrage trades conducted for brokerage firms= own
accounts. Individuals were responsible for only 11.3 percent of the total short orders, even though
they placed 46.1 percent of the total orders through the SuperDot system. Agency orders were also
Please insert Tables I and II approximately here.
a higher fraction of the short orders than the overall order mix.
An interesting trading pattern appears across deciles of market capitalization. Table III
displays the relative frequencies of short orders placed by each account type in each capitalization
decile. Results in the largest decile mirror the overall results: Index arbitrageurs were the largest
10
users of short SuperDot orders, while individuals were under represented. As market capitalization
decreases, index arbitrage trades placed by brokerage firms represented over half of the short sale
orders in the fourth and fifth deciles. However, in the sixth decile and below the pattern reverses:
The share of orders placed for index arbitrage and program trading fell dramatically, and the share
placed by individuals climbed significantly. The lower rate of index arbitrage and program trading
in the smaller stocks is not surprising, since most of the stocks in the S&P 500 index are in the larger
deciles of market capitalization. Even when index arbitrage orders are excluded, the relative share
of short orders from individuals rises substantially in the smaller deciles. Results for volume were
Please insert Table III approximately here.
similar and are not reported here.
B. Order Placement Strategy of Short Sellers
It is also interesting to see whether short sales differ from regular sales in the order placement
strategies that investors follow. Since the uptick rule may make the execution of short sales
problematic, investors may change their order placement strategies accordingly. Table IV displays
the relative use of market and limit orders. Short sellers used fewer market orders and fewer
"marketable limit" orders, that is, limit orders whose limit prices would allow them to be filled
immediately at the current quotes, than did those who placed regular buy and sell orders. Market
orders were used to place 60.3 percent of the regular sell orders, but only 54.0 percent of the short
sale orders.
11
Please insert Table IV approximately here.
C. Sizes of Short Sales
Short sell orders tend to be larger than regular sell orders. Table V presents summary
statistics on size for intraday orders. The mean SuperDot buy order was for 808 shares with a median
of 300 shares. Long sell orders averaged 852 shares, with a median of 300 shares, while short sell
orders averaged 1,307 shares, with a median of 750 shares. Even though index arbitrageurs place
a major fraction of short sale orders, their orders are not the only forces driving the larger-thanaverage size of short sales. As seen in Table VI, agency trades for institutions and the proprietary
Please insert Tables V and VI approximately here.
trades for brokerage firms are larger than the individual and index arbitrage trades.
D. Time-of-Day Patterns
Time-of-day patterns in both trading volume and the bid-ask spread are well known. There
is also a time-of-day pattern in the placement of short sales. To investigate this, the orders were
grouped into 30-minute intervals. Table VII reveals that short orders as a percentage of total orders
were higher during the first hour of trading and lower mid-day, with an upturn in the last half hour
of trading. From 9:30 until 10:00 AM, short orders formed 6.7 percent of the order flow; they fell
to a low of 3.8 percent from 12:00 to 12:30, and picked up to 4.8 percent between 3:30 and 4:00
PM.
12
Please insert Table VII approximately here.
E. Impact of the Uptick Rule
Since the uptick rule was designed to prevent short sales from depressing prices, it is
interesting to examine whether it actually impedes short sales in a declining market. To do so, I
looked at the percentage of clock time each day that a short sale could have been executed in
compliance with the uptick rule. By comparing the last New York sale price with the best bid and
offer, it is possible to determine whether a short order could have been legally executed at the bid or
at other prices between the bid and offer. Table VIII displays the results. Overall, a short market
order could have been legally executed immediately at the best bid price only 6.8 percent of the time.
However, short orders can often be filled legally at other prices within the bid-ask spread. This
indicates that the uptick rule at least slows down the execution of short sales most of the time. For
40.4 percent of the time, a short order could legally have been filled at the offer price. Thus, a short
market order would have been first in line to execute against the next incoming market buy order.
Since trades frequently take place between the posted bid and offer prices, this finding indicates that
for almost half the time the uptick rule would slow down -- but not block -- many short sales. For
another 46.5 percent of the time a short sale could legally have been made at the offer price. Only
5.8 percent of the time was there no way to make a legal short trade at or within the current quotes.
Please insert Table VIII approximately here.
For reference, 5.8 percent is about 23 minutes out of the 390 minute trading day.
13
The uptick rule becomes more of a barrier, however, on days when a stock's price is
declining. The daily stock returns for the stocks in this sample were placed in five categories based
on their returns. For stocks that dropped 5 percent or more in a day, the uptick rule banned short
trades (in the sense of not permitting them at the offer price or below) 10.0 percent of the time (about
39 minutes per day) and allowed immediate execution of a market short order at the bid price only
2.4 percent of the time. Conversely, on days when a stock's price increased by 5 percent or more,
immediate execution of a short market order at the bid could have taken place 14.3 percent of the
time, and outright banned such sales only 2.5 percent of the time. However, the reader should
remember that these are averages, and that for an individual stock the uptick rule may block a
particular short sale indefinitely.
F. Short Sales and Price Declines
Short sales have often been blamed for causing drops in prices. To see whether short sales
are associated with price drops, I examine the frequency of short sales during periods when prices
declined more than two percent versus periods in which prices declined less or increased, as shown
in Table IX. As to be expected, an increase in the percentage of sell orders is associated with price
decreases. Sell orders were 57.9 percent of the orders during the half hour intervals when prices
declined more than two percent, but were only 29.8 percent during the half hour intervals when prices
increased more than two percent. Unlike the monotonic pattern of the regular sell orders, short
orders made up a smaller fraction of the order flow (3.4 percent) during the periods of greatest
decline than at other times. This is presumably a result of the uptick rule, since investors would find
it difficult to execute a short sale under those conditions and thus would be unlikely to place orders
14
that they did not expect to be filled. The highest percentage of short orders is during the period when
prices declined between zero and two percent. Thus, there is some evidence here that the uptick rule
Please insert Table IX approximately here.
deters investors from placing short sale orders during periods of rapid price decline.
G. Impact of Short Sales on Subsequent Quotes and Trades
The implications of short selling for future stock price movements has long been debated. On
the one hand, one may expect that short sellers, because of the added constraints and transactions
costs they face, would transact only when they had more information than the average trader. This
expectation implies that the information revealed by a short order should be more than the
information revealed by a regular sale order. On the other hand, it can be argued that a short sale is
either bullish or a neutral event, since the short investor must eventually purchase the stock to cover
the short.
To the extent that a short order reveals information, this information should be reflected in
subsequent quotes and trades. The price impact on both quotes and subsequent trades was calculated
by examining the difference between the best quotes before and after each order was placed, and
between the last trade price before with the first trade after. If no events occurred within ten minutes
after the order was placed, the changes were set to zero.
When a short SuperDot order is placed, the specialist who receives the order knows that the
order is for a short sale. Thus, the information that the trader is willing to short the security should
be incorporated in the specialist's quote-setting behavior immediately, even if the uptick rule prevents
15
the immediate filling of the order.
Table X displays the impact of orders on the next bid, offer, and trade after the order, in ticks
($.125). As would be expected from intuition, on average buy orders are followed by increases in
both the bid and offer quotes of about .02 ticks, and sell orders are followed by decreases of about
.02 ticks. The average price impact of a short order behaves asymmetrically: the bid declines by .004 ticks while the offer decreases -.03 ticks. Thus, the raw averages indicate that a short sale order
has less impact on the bid than a regular sale order but more impact on the offer. However, the
uptick rule makes it difficult to draw inferences from this raw statistic, since this may be a result of
the uptick rule preventing a short sale from knocking out the bid (if it was set by an outstanding
Please insert Table X approximately here.
customer limit order) and causing a quote revision.
To examine the impact of short sales on prices, it is necessary to control not only for whether
an order is short, but also for other characteristics which may affect the price impact. These include
whether the order is a limit or market order, the order size, the bid-ask spread in effect when the
order is placed, and the size of the firm.
To control for biases in the observed price impact that may be induced by the uptick rule, as
well as to control for other features that may affect the price impact, I estimate a probit regression
of the change in quotes on several control variables. A probit is chosen since most of the time the
quotes either move one tick or do not move at all. The results are shown in Table XI. The control
variables include whether the order was a limit or a market order, since Rock (1990) finds that the
informed investors are more likely to place market orders than limit orders. Thus, if a market order
16
contains more information, then it should have more impact on price. Furthermore, I also control for
whether the limit orders were pure limit orders that were away from the market, or a "marketable
limit" order that can be immediately executed given the current quotes, since such orders often behave
differently from regular limit and market orders.
Other control variables include a dummy
representing whether the order is larger than the quoted offer size, as well as dummies indicating the
types of investors who placed the orders. Dummy variables which indicate the current status of the
stock with respect to the uptick rule control for the impediments placed by the uptick rule.
The significantly negative coefficient on SHORT, the indicator of a short order, demonstrates
that short orders have less impact on subsequent bid quotes than regular sale orders. This does not
hold true for the offer quotations: Although the sign is still negative, the coefficient lacks statistical
significance, which is remarkable with over 275,000 observations. As to be expected, market orders
and marketable limit orders have more impact on the subsequent quotes, as do large orders and
orders placed when the uptick rule permits short sales at the bid price. Orders that were hand entered
on the floor have less impact; this is reasonable since one would expect that the information
contained in the order would already be impounded in stock prices. Short sale orders that were
identified as index arbitrage trades had slightly more impact. Sell orders for smaller capitalization
Please insert Table XI approximately here.
stocks had less impact.
One possible explanation for the smaller impact of short sales than regular sales could be the
information about account type that a short sale indicates. NYSE specialists do not ordinarily see the
account type indicators reported in the TORQ order file. However, they presumably know that index
17
arbitrageurs are responsible for a large fraction of the SuperDot short sales. Thus, when they see a
short sale, they know that there is a better than average chance that the order represents an index
arbitrage trade. Because the specialists observe the basis between the spot equity and futures market,
and because index arbitrage trades tend to arrive in waves, a particular index arbitrage sell order is
not likely to have any more information in it just because it is a short sale.
IV . Conclusions and Implications
Short selling forms about eight percent of sales volume on the NYSE, and over 13 percent
of sell order volume placed through the NYSE SuperDot system. Index arbitrage and program
trading are over a third of the short trades and volume executed through the SuperDot system. For
larger stocks, institutions place more short orders than do individuals, but individuals= fraction of
short orders increases dramatically in the smallest size deciles.
The pattern here, that individuals are a larger fraction of the order flow in the smallest stocks,
is consistent with market lore that institutional investors do not invest in small stocks. However, this
phenomenon is not well modeled and is worthy of more investigation.
The uptick rule impedes immediate execution of a short sale at the bid over 90 percent of the
time, although usually a short sale within the bid-ask spread or at the offer would be legal. Even on
days when stocks were rising more than five percent, the uptick rule would have impeded the
immediate execution of a short sale at the bid over 85 percent of the time. On days when stocks were
falling more than five percent, the uptick rule would have impeded immediate short sales at the bid
over 97 percent of the clock time. Fewer short orders are placed during times of rapid price decline,
indicating that the uptick rule may be dampening short-run volatility.
18
Short sales have less impact on subsequent bid quotations than do regular sales, even after
correcting for other factors that may affect quote setting along with the effect of the uptick rule. The
impact of short sales on the offer quote is also less than regular sale orders, but the result is not
significant. This result is counter to the intuition that short sale orders, because they come from more
sophisticated investors, should contain more information and thus move prices more than regular sale
orders do. This result is consistent, however, with the intuition that a short position eventually must
be covered, resulting in built-in future demand for the stock. It is also consistent with the notion that
the average short sale conveys less information to the NYSE specialist, perhaps because such as large
number of short sales are index arbitrage trades. It should be noted that short sale orders still result
in declines in subsequent quotes, but not to the extent that regular sale orders do.
19
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22
Notes:
23
24
Table I
Frequencies of NYSE SuperDot Orders
By Account Type
This table presents the number of electronic SuperDot orders by account type for 144 NYSE stocks from November 1, 1990 through January 31, 1991. Buy-minus orders are orders
to buy stock on a down tick and sell-plus orders are orders to sell on an uptick. Exempt short sales are short sales that are exempt from the uptick rule. The account types are as
explained in the text and Appendix 1. Percentages of the column totals are given below the numbers in each cell. The percentages in the bottom row are the percentages of the row
total.
Account Type
Code
Regular
Buy
Buy-minus
Regular Sell
Sell-plus
Short Sell
Exempt Short
Total
Agency
A
88,905
26.47
1,556
7.74
81,641
28.84
808
27.99
10,118
31.18
231
78.31
183,259
27.16
Proprietary
Program
C
5,249
1.56
2,448
12.18
6,532
2.31
944
32.70
623
1.92
0
0.00
15,796
2.34
Proprietary
Index Arbitrage
D
14,056
4.18
14,950
74.39
6,155
2.17
542
18.77
12,591
38.80
0
0.00
48,294
7.16
Individual
I
165,803
49.36
1
0.00
141,412
49.96
0
0.00
3,664
11.29
2
0.68
310,882
46.08
Missing
M
19,922
5.93
54
0.27
19,650
6.94
20
0.69
1,093
3.37
1
0.34
40,740
6.04
Proprietary
P
18,255
5.43
9
0.04
17,901
6.32
2
0.07
3,421
10.54
61
20.68
39,649
5.88
Agency Index
Arbitrage
U
16,160
4.81
305
1.52
6,503
2.30
140
4.85
539
1.66
0
0.00
23,647
3.50
Agency
Program
Trades
Y
7,583
2.26
774
3.85
3,245
1.15
431
14.93
405
1.25
0
0.00
12,438
1.84
335,933
49.79
20,097
2.98
283,039
41.95
2,887
0.43
32,454
4.81
295
0.04
674,705
100.00
Total
25
Table II
Frequencies of NYSE SuperDot Orders
By Order Volume (000)
This table presents the volume of electronic SuperDot orders by account type for 144 NYSE stocks from November 1, 1990 through January 31, 1991. Buy-minus orders are orders
to buy stock on a down tick and sell-plus orders are orders to sell on an uptick. Exempt short sales are short sales that are exempt from the uptick rule. The account types are as
explained in the text and Appendix 1. Percentages of the column totals are given below the numbers in each cell. The percentages in the bottom row are the percentages of the row
total.
Account Type
Account
Code
Regular
Buy
Buy-minus
Regular
Sell
Sell-plus
Short
Sell
Exempt
Short
Total
Agency
A
75,610
25.46
2,375
12.31
67,250
25.60
1,037
38.04
15,230
35.76
103
71.12
161,600
25.88
Proprietary
Program
C
4,011
1.35
2,032
10.54
6,023
2.29
636
23.34
783
1.84
0
0.00
13,490
2.16
Proprietary
Index Arbitrage
D
12,790
4.31
13,630
70.66
4,724
1.80
445
16.34
12,290
28.85
0
0.00
43,880
7.03
Individual
I
75,680
25.49
100
0.00
70,380
26.80
0
0.00
3,243
7.61
1
0.90
149,300
23.91
Missing
M
87,220
29.38
91
0.47
87,400
33.28
314
1.15
3,067
7.20
0
0.14
177,800
28.48
Proprietary
P
21,920
7.38
22
0.11
17,860
6.80
76
0.28
5,877
13.80
40
27.84
45,730
7.32
Agency Index
Arbitrage
U
10,520
3.54
293
1.52
4,967
1.89
138
5.06
857
2.01
0
0.00
16,770
2.69
Agency
Program Trades
Y
9,181
3.09
845
4.38
4,038
1.54
430
15.79
1,252
2.94
0
0.00
15,750
2.52
26
296,900
47.56
Total
19,290
3.09
262,600
42.07
2,725
0.44
42,600
6.82
145
0.02
624,300
100.00
Table III
Frequencies of Short NYSE SuperDot Orders
By Deciles of Market Capitalization
This table displays the short orders that were submitted for 144 stocks through the NYSE SuperDot system from November 1, 1990 through January 31, 1991 by account type and
deciles of market capitalization, with one being the largest decile. The definitions of the account types are given in the text and Appendix 1. Percentages of the column totals are given
below the numbers in each cell. The percentages in the bottom row are the percentages of the row total.
Account Type
Account
Code
Largest
1
Smallest
2
3
4
5
6
7
8
9
Total
10
Agency
Trades
A
5,227
32.52
1,974
34.75
923
24.49
952
29.92
442
23.59
402
47.13
111
20.15
69
25.27
16
11.85
2
3.12
10,118
31.18
Proprietary
Program
C
254
1.58
165
2.90
83
2.20
78
2.45
25
1.33
13
1.52
4
0.73
1
0.37
0
0.00
0
0.00
623
1.92
Proprietary
Index
Arbitrage
D
5,888
36.63
2,134
37.57
1,734
46.01
1,667
52.39
985
52.56
48
5.63
84
15.25
24
8.79
27
20.00
0
0.00
12,591
38.80
Individual
I
1,437
8.94
768
13.52
445
11.81
154
4.84
187
9.98
211
24.74
240
43.56
109
39.93
90
66.67
23
35.94
3,664
11.29
Missing
M
338
2.10
141
2.48
352
9.34
90
2.83
63
3.36
38
4.45
46
8.35
20
7.33
2
1.48
3
4.69
1,093
3.37
Proprietary
P
2,373
14.76
333
5.86
179
4.75
152
4.78
123
6.56
130
15.24
55
9.98
40
14.65
0
0.00
36
56.25
3,421
10.54
Agency Index
Arbitrage
U
363
2.26
73
1.29
12
0.32
49
1.54
42
2.24
0
0.00
0
0.00
0
0.00
0
0.00
0
0.00
539
1.66
Agency
Program
Trades
Y
193
1.20
92
1.62
41
1.09
40
1.26
7
0.37
11
1.29
11
2.00
10
3.66
0
0.00
0
0.00
405
1.25
16,073
5,680
3,769
3,182
1,874
853
551
273
135
64
32,454
Total
27
49.53
17.50
11.61
9.80
5.77
2.63
1.70
0.84
0.42
0.20
100.00
Table IV
NYSE SuperDot Orders
Use of Limit and Market Orders
This table displays the NYSE SuperDot orders for 144 stocks from November 1, 1990 through January 31, 1991 by the type of order and whether it was placed as a market or a limit
order. Marketable limit orders are orders that are marked as limit orders, but with limit prices such that they can be filled immediately at the current quotes. (e.g. If the bid is at $10.25,
a limit order to buy at $10.50 is classified as a marketable limit order, regardless of size or uptick rule status.) A buy-minus order is a buy order that can only be executed on a minus
or a zero-minus tick, while a sell-plus order is a sell order that can only be executed on a plus or zero-plus tick. An exempt short sale is one which is exempt from the uptick rule.
Percentages of the column totals are given below the numbers in each cell. The percentages in the bottom row are the percentages of the row total.
Order Type
Order Side
Marketable
Limit
(percentage of
total)
Regular Buy
Market
(percentage of
total)
Limit
(percentage of
total)
Total
(percentage of
total)
51,861
15.44
197,257
48.29
86,815
45.79
335,933
49.79
3
0.01
20,064
99.84
30
0.15
20,097
2.98
22,653
8.00
170,562
60.26
89,824
31.74
283,039
41.95
Sell-plus
3
0.10
2,879
99.72
5
0.17
2,887
0.43
Short Sell
2,039
6.28
17,521
53.99
12,894
39.73
32,454
4.81
26
8.81
240
81.36
29
9.83
295
0.04
76,585
11.35
408,523
60.55
189,597
28.10
674,705
100.00
Buy-Minus
Regular Sell
Exempt Short
Total
28
Table V
Sizes of Intraday SuperDot Orders
This table presents size statistics for all regular way NYSE SuperDot orders for 144 stocks that were placed while the market was open from November 1, 1990 through January 31,
1991. A buy-minus order is a buy order that can only be executed on a minus or a zero-minus tick, while a sell-plus order is a sell order that can only be executed on a plus or zero-plus
tick. An exempt short sale is one which is exempt from the uptick rule. Percentages of the column totals are given below the numbers in each cell. The percentages in the bottom
row are the percentages of the row total.
Order Side
Number of
observations
Mean size of
order
Standard
Deviation of
mean order
size
25th percentile
of order size
Median order
size
75th percentile
of order size
95th percentile
of order size
99th percentile
of order size
Regular Buy
293,595
807.75
2,115.63
100
300
800
3,000
10,000
Buy-Minus
19,246
968.60
1,415.32
200
400
1,200
3,584
6,700
Regular Sell
247,425
852.08
2,196.20
146
300
900
3,000
10,000
Sell-Plus
2,802
945.74
1,012.41
200
600
1,300
2,600
4,700
Short Sell
28,557
1,307.18
1,869.92
300
750
1,700
5,000
9,050
259
475.99
504.84
328
328
328
1,400
3,000
Exempt Short
29
Table VI
NYSE SuperDot Orders 11/1/90 - 1/31/91
Order size by account type
This table presents data on the sizes of intraday NYSE SuperDot orders from November 1, 1990 through January 31, 1991 for 144 stocks. The account types are as described in the text and
Appendix 1.
Number of
observations
Mean
size of
order
Standard
deviation of
mean order
size
25th
percentile of
order size
Median
order
size
75th
percentile of
order size
95th
percentile of
order size
99th
percentile of
order size
Regular Buy Orders
Agency
76,641
817.34
1,367.13
200.0
400
1,000
3,000
6,000
4,907
723.73
955.88
200.0
300
1,000
3,000
4,700
12,622
562.48
840.46
100.0
200
550
2,000
3,400
146,826
447.81
868.49
100.0
200
500
1,500
4,000
Missing
14,706
4,190.31
7,194.44
600.0
2,000
5,000
15,000
30,900
Proprietary
15,969
1,184.78
1,733.07
300.0
600
1,100
4,800
10,000
Agency Index Arbitrage
15,155
635.60
1,058.04
150.0
200
650
2,700
5,000
6,769
1,172.15
2,068.19
200.0
500
1,200
4,700
9,400
69,861
786.97
1,308.04
200.0
400
1,000
2,800
5,000
Proprietary Program
6,107
890.75
1,174.33
200.0
300
1,000
3,000
4,700
Proprietary Index Arbitrage
5,546
556.73
946.46
100.0
200
500
2,075
5,650
127,009
491.57
872.92
100.0
200
500
1,900
4,166
Missing
14,573
4,297.53
7,045.52
1,000.0
2,000
5,000
15,000
30,000
Proprietary
15,412
959.73
1,481.52
200.0
500
1,000
3,000
7,400
Agency Index Arbitrage
6,027
693.51
1,045.22
150.0
300
1,000
2,800
5,100
Agency Proprietary
2,890
1,137.35
1,773.52
200.0
500
1,200
3,900
10,000
Proprietary Program
Proprietary Index Arbitrage
Individual
Agency Proprietary
Regular Sell Orders
Agency
Individual
Short Sell Orders
30
Agency
8,608
1,539.98
1,846.08
500.0
1,000
2,000
5,000
8,500
469
1,186.35
1,793.10
100.0
375
1,300
5,000
9,000
11,493
994.46
1,372.76
200.0
500
1,500
3,500
6,250
3,259
887.30
1,129.79
200.0
500
1,000
3,100
5,000
878
2,705.18
4,188.30
500.0
1,000
3,000
10,000
24,000
3,048
1,698.56
2,110.35
500.0
1,000
2,000
5,000
10,000
Agency Index Arbitrage
477
1,597.78
2,103.99
300.0
500
2,000
7,070
8,739
Agency Program
325
2,710.46
4,680.99
400.0
1,300
3,000
15,000
20,000
Proprietary Program
Proprietary Index Arbitrage
Individual
Missing
Proprietary
31
Table VII
Time-of-day Patterns in NYSE SuperDot Orders 11/1/90 - 1/31/91
This table presents statistics on NYSE SuperDot order submission by time-of-day for 144 stocks from November 1, 1990 through January 31, 1991. A buy-minus order is a buy order that
can only be executed on a minus or a zero-minus tick, while a sell-plus order is a sell order that can only be executed on a plus or zero-plus tick. An exempt short sale is one which is exempt
from the uptick rule. Percentages of the column totals are given below the numbers in each cell. The percentages in the bottom row are the percentages of the row total.
Type of
order
Before
Open
9:3010
10-10:30
10:30-11
11-11:30
11:30-12
12-12:30
12:301
1-1:30
Regular
Buy
37,940
50.78
33,034
48.65
25,241
45.65
24,990
49.19
24,963
50.26
24,458
51.43
20,261
49.98
18,813
52.99
15,266
47.81
18,964
52.06
19,477
49.60
21568
48.61
23,460
51.25
27,332
50.09
763
1.02
3,444
5.07
2,873
5.20
1,968
3.87
1,784
3.59
1,437
3.02
1,399
3.45
947
2.67
786
2.46
1,044
2.87
873
2.22
1,069
2.41
868
1.90
842
1.54
32,196
43.09
26,465
38.98
23,108
41.80
21,144
41.62
20,219
40.71
19,553
41.11
17,133
42.26
14,184
39.95
14,233
44.57
14,912
40.93
16,962
43.20
19,686
44.37
19,492
42.58
23,545
43.15
Sell-plus
75
0.10
341
0.50
274
0.50
352
0.69
296
0.60
227
0.48
210
0.52
125
0.35
162
0.51
109
0.30
190
0.48
150
0.34
172
0.38
204
0.37
Short Sell
3,710
4.97
4,579
6.74
3,764
6.81
2,340
4.61
2,382
4.80
1,869
3.93
1,522
3.75
1,417
3.99
1,466
4.59
1,389
3.81
1,750
4.46
1,875
4.23
1,776
3.88
2,603
4.77
30
0.04
39
0.06
27
0.05
13
0.03
25
0.05
14
0.03
16
0.04
14
0.04
18
0.06
11
0.03
15
0.04
24
0.05
12
0.03
36
0.07
74,714
11.08
67,902
10.07
55,287
8.20
50,807
7.53
49,669
7.37
47,558
7.05
40,541
6.01
35,500
5.26
31,931
4.74
36,429
5.40
39,267
5.82
44,372
6.58
45,780
6.79
54,562
8.09
Buy-Minus
Regular
Sell
Exempt
Short
Total
32
1:30-2
2-2:30
2:30-3
3-3:30
3:30-4
Table VIII
NYSE SuperDot Orders 11/1/90 - 1/31/91
Fraction of Time That Uptick Rule Impedes Short Sales
By Price Change Categories
This table determines the fraction of time that uptick rule would have permitted short sales at various prices relative to the best bid and offers from November 1, 1990 through January 31, 1991.
Stocks were classified each day by their price movement relative to the prior day. For example, a stock whose closing price is more than five percent below the prior day's close is classified as
"Decline > -5%." The uptick rule permits short sales at prices which are an uptick or a zero plus tick. Unknown tick status results from the beginning of the data set when the previous trade was
unknown, and from times when the quotes unusable, such as a locked market in which one market is quoting a bid price higher than another market's offer.
Daily Price Change
Percent of
Time Short
Sales
Permitted at
Bid Price
Percent of Time
Short Sales
Permitted
Between Bid
and Offer but
not at Bid
Percent of Time
Short Sales
Permitted at
Offer
Percent of
Time Short
Sales Not
Permitted at
Offer Price or
Below
Percent Time
Uptick Status
Unknown
Number of
Observations
Total Seconds
Accounted For
Stock fell
(return < -5
percent)
2.39
23.63
63.68
9.98
0.32
413
9,664,200
-5 < return < 0
3.52
45.96
41.42
8.95
0.14
2,691
62,404,321
Unchanged
6.29
33.43
55.21
4.83
0.24
1,999
46,683,000
0 < return < 5
percent
9.40
44.95
41.94
3.57
0.14
2,964
68,913,000
Stock rose
( > 5) percent
14.28
29.83
52.92
2.52
0.45
520
12,144,600
Overall
6.76
40.44
46.49
5.82
0.49
8,989
209,208,039
33
Table IX
NYSE SuperDot Orders 11/1/90 - 1/31/91
Order Submissions and Price Movement
This table presents data on intraday NYSE SuperDot orders for 144 stocks from November 2, 1990 through January 31, 1991, classified by the movement of the midpoint of the NYSE bid and offer
quotations relative to the prior half hour period. For example, a stock whose quotes declined more than two percent in a 30 minute interval is classified as "Decline > -2%."
Decline > -2%
Buy
Decline 0 to -2%
Unchanged
Increase 0 to 2%
Increase > 2%
Total
2,349
36.41
75,939
42.98
101,716
50.81
107,296
54.02
5,994
64.60
293,294
49.61
138
2.14
5,884
3.33
6,296
3.14
6,696
3.37
221
2.38
19,235
3.25
3,733
57.87
83,881
47.48
83,085
41.50
73,658
37.08
2,764
29.79
247,121
41.80
Sell-plus
9
0.14
933
0.53
800
0.40
1,046
0.53
14
0.15
2,802
0.47
Sell Short
221
3.43
9,927
5.62
8,230
4.11
9,871
4.97
284
3.06
28,533
4.83
Exempt Short
1
0.02
103
0.06
81
0.04
73
0.04
1
0.01
259
0.04
6,451
1.09
176,667
29.88
200,208
33.86
198,640
33.60
9,278
1.57
591,244
100.00
Buy-minus
Sell
Total
34
Table X
Price Impact of NYSE SuperDot Orders 11/1/90 - 1/31/91
This table displays the effect of NYSE intraday SuperDot orders on subsequent quotes and trades for 144 stocks from November 1, 1990 through January 31, 1991. The change reflects the change
in the bid and offer quotes reflects the change in the best bid or offer before the order was received to the best bid or offer after the order was received. If no new quote occurred within ten minutes
of receipt of the order, the change was defined to be zero. All changes are measured in ticks ($.125).
der Side
Number of
observations
Change in Bid
Quote Subsequent
to Order (in ticks)
Change in Offer
Quote Subsequent
to Order (in ticks)
Change in Price of
Next Trade
Subsequent to Order
(in ticks)
Standard Error of
Change in Bid
Quote Subsequent
to Order
Standard Error of
Change in Offer
Quote to Subsequent
to Order
Standard Error of
Change in Price of
Next Trade
Subsequent to Order
gular Buy
293,595
0.0184
0.0187
0.0835
0.0007
0.0007
0.0011
y-Minus
19,246
0.0289
0.0026
0.0246
0.0031
0.0027
0.0044
gular Sell
247,425
-0.0192
-0.0174
-0.0812
0.0007
0.0007
0.0013
-Plus
2,802
-0.0126
-0.0309
-0.0120
0.0080
0.0078
0.0122
rt Sell
28,557
-0.0042
-0.0303
-0.0202
0.0022
0.0024
0.0037
259
-0.0279
-0.0177
-0.0198
0.0214
0.0202
0.0378
mpt
rt
35
Table XI
NYSE SuperDot Sell Orders 11/1/90 - 1/31/91
Market Impact of Short Sales on Quotes
Probit Model of Quote Decrease
This table displays the results of two probit models on quote revisions based on intraday NYSE SuperDot sell and short sell orders for 144 stocks from
November 1, 1990 through January 31, 1991. The dependent variable is an indicator of a quote decrease. A positive coefficient indicates that the
variable is more likely to cause a quote decrease. The intercept reflects a limit sell order for a stock in the largest decile of market capitalization when
the bid-ask spread is one-eighth and the uptick rule would prohibit a short sale at the bid price. ** indicates significance at the one percent level.
Dependent
Variable:
Independent
Variable
Change in Bid Quote
Parameter
Estimate
Change in Offer Quote
Standard
Error
Parameter
Estimate
Standard
Error
INTERCEPT
-2.02**
0.0183
-2.96**
0.0332
Intercept
SHORT
-0.15**
0.0156
-0.02
0.0162
Indicates regular short order
MARKET
0.44**
0.0121
0.30**
0.0121
Market order
MARKLIM
0.59**
0.0164
0.30**
0.0224
Marketable limit order
LARGE
0.35**
0.0164
0.26**
0.0192
Indicates order size > quote
SHORTYES
0.37**
0.0197
0.36**
0.0397
Short OK at bid
0.03
0.0210
0.52**
0.0322
Short not OK at bid, but higher
0.08**
0.0158
0.22**
0.0314
Short OK at offer, not below
FLOOR
-0.19**
0.0287
-0.29**
0.0302
Indicates entered on floor
TICK2
-0.06**
0.0118
1.51**
0.0152
Bid-ask spread=2 ticks ($.25)
TICK3
0.13**
0.0213
1.91**
0.0202
Bid-ask spread=3 ticks ($.375)
TICK4
-0.23**
0.0461
1.68**
0.0309
Bid-ask spread=4 ticks ($.50)
INDEXARB
0.11**
0.0152
0.08**
0.0173
Index arbitrage trade
DEC2
0.19**
0.0116
-0.13**
0.0132
2nd largest cap decile
DEC3
0.13**
0.0142
-0.36**
0.0161
3rd largest cap decile
DEC4
-0.12**
0.0190
-0.71**
0.0201
4th largest cap decile
DEC5
-0.50**
0.0243
-0.91**
0.0280
5th largest cap decile
DEC6
-0.85**
0.0373
-1.21**
0.0403
6th largest cap decile
SMALLCAP
-0.98**
0.0338
-1.30**
0.0360
Indicates 4 smallest deciles
Number of
observations
275,982
SHORTMAY
SHORTOFF
275,982
Percent correctly
36
classified
94.6%
94.5%
37
Appendix 1
Account type codes
Code
Account Type
A
Agency trades performed on behalf of another institution, which may
be another brokerage firm or an institutional investor
C
Program trades other than index arbitrage made for the brokerage
firm's own account
D
Index arbitrage trades made for a brokerage firms' own account
I
Orders for natural persons
M
Missing account information
P
Proprietary trades made for the brokerage firm's own account that are
not program trades or index arbitrage trades
U
Index arbitrage trades performed on an agency basis by the
brokerage firm for another entity
Y
Program trades other than index arbitrage that are performed by the
brokerage firm for another entity.
1. The "box" referred to here is presumably a safe deposit box in which the securities are already stored.
U.S. tax laws treat a short sale against the box differently than selling the securities in the box, resulting in
potential tax advantages. For example, an investor with a capital gain on the stock may wish to sell the
stock but defer paying the capital gains taxes until the future. By shorting against the box, the investor
locks in the price of the sale and removes the price risk of his position, but has not taken the capital gain on
the shares that have appreciated.
2. See Foster (1932) for an example of the classic attack on short selling.
3. See Meeker (1932) for details on this and other attempts to ban short selling over the years.
4. For a thorough discussion of the regulation of short selling in the United States, see Worley (1990).
5. Selling a put option produces similar payoffs to selling short. Incidentally, options market makers are
exempt from the uptick rule.
6. Federal Reserve Regulation T (12 CFR 220) governs margin requirements for short selling as well as
for margin purchases. Generally, the initial margin requirement is 50%. NYSE Rule 431 sets the
maintenance margin requirement for short sales at the greater of 30% or $5 per share for stocks priced
over $5.
7. These prices are based on discussions with market professionals involved in stock lending. Stock
38
lending has not yet progressed to a screen based system in which good price information is readily
available. Since the security lender holds the collateral which is invested in Treasury bills, the lender passes
on the interest to the short, less the fee, which is usually quoted in basis points. For more on the
institutional details of securities lending, see Fabozzi (1997).
8. Stocks listed on the NYSE, AMEX, and Nasdaq National Market are automatically eligible for margin
under Fed rules. Other OTC stocks are eligible if they meet certain requirements. The Fed regularly
publishes a list of eligible OTC stocks.
9. See Freeman (1991) for a description of the institutional details of stock lending in the United Kingdom.
10. See Lintner (1971), Ross (1977), Brito (1978), Jarrow (1980), Litzenberger and Ramaswamy (1980),
Dybvig (1984), Allen and Gale (1991), Sharpe (1991), and Alexander (1993) for work that investigates the
effect of constraints on short selling in asset pricing models.
11. See Jacobs and Levy (1993) for a good practitioners view of short selling.
12. The NYSE "Blue Books" contained daily for September 1931 to September 1932 and weekly at other
times. For a fascinating study of this data see Macaulay and Durand (1951).
13. The NYSE also publishes data on the monthly aggregate short interest in its annual fact book.
14. For more information on the database and on the mechanisms used for the handling of orders on the
NYSE, see Hasbrouck (1992) and Hasbrouck, Sofianos and Sosebee (1993).
15. A sell-plus order is a long sell order that is to be executed similar to a short sale in accordance with the
uptick rule. It can only be executed on an uptick or a zero-plus tick. Similarly, a buy-minus order is an
order that is only to be executed on a downtick or a zero-minus tick.
16. Under the uptick rule, an exchange may adopt a rule to exempt the specialist. However, the NYSE
decided not to exempt the specialist in NYSE rule 440B(b). Some arbitrage trades are exempt, but most
index arbitrage activity is not. For more details, see Worley (1990).
39