Centre for Risk Research Working Papers
School of Management



Short Selling: Discussion of Short Sales Constraints and Momentum in Stock Returns
Stephen H. Thomas
University of Southampton
March 2006
Number CRR-06-01
ISSN 1356-3548
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SHORT SELLING
1. Introduction
Data on the cost of short selling stocks has been noticeable by its almost entire
absence until recently, and the research implications of such ignorance for both
developments in asset pricing theory and the empirical implementation of
investment strategies is only recently coming to be better understood. Finance
theory makes very strong assumptions about the ability of arbitrageurs to borrow
and sell short large amounts of stock at no cost, (see Fama (1965, 1970), Ross
(1976)). Yet while short selling is central to the theoretical foundations of the
Efficient Markets Hypothesis and asset pricing theory, there has been relatively little
discussion regarding the mechanics, costs, feasibility and extent of short sales, let
alone its market impact. That constraints on short selling, whether formal and
legalistic, or informal and cultural, can lead to overpricing of securities is the single
most important theme of the literature: these securities may well have low future
returns until the overpricing is fully corrected. Further, while direct trading costs
such as bid-ask spreads and commission are incurred when buying or selling a
position, short sale costs is a holding cost and hence related to the length of time a
short position is maintained: this may well be for several months or even years for
certain strategies such as momentum or value versus growth, and hence they will
be greater than direct transaction costs.
In this discussion we concentrate on short sales of equities1: we begin with a
discussion of the perceived restrictions on short selling, together with the
implications of these restrictions and the information content of changes in short
interest. We then turn to the mechanics of short selling, the key facts that have
emerged from proprietary data in recent years, and the extent of short selling
restrictions in a global context. We then examine how data issues have influenced
research before reviewing the empirical evidence on short interest and market
returns behaviour, including the link to earnings’ announcements. We conclude
with a brief discussion of UK experience and how recent research such as Nagel
1 Of course, there are other well established alternatives to betting on downward movements in stock
prices, including options and single stock futures; while we do not pursue them here, we note that
some international comparisons of short selling rules do include such derivatives in their coverage
(see Charoenrook and Daouk (2005) for put option regulations).
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(2006) and Ali-Trombley (2006) are opening up new ways to think about mispricing
and associated investment strategies.
2. Background
There can be little doubt that the term ‘short sale’ would be considered by many to
be the most offensive term in the linguistics of finance and financial markets, being
met with opprobrium by certain market commentators, regulators and politicians
alike, usually as markets swing downwards after unsustainable excesses, whether it
is 1987 or 2001, or even with the suggestions that certain informed agents may
have short sold insurance and airline stocks prior to the 9/11 events in the US.
Chancellor (2001) provides an interesting account of such events since 1600,
emphasising that similar events and reactions have occurred throughout history,
whether it was the East India Company in 1609, the Mississippi and South Sea
bubbles of the early 18th century, the Great Wall Street Crash of 1929, or the
events of 2001, short sellers have been blamed for driving prices down, regulators
have imposed, or considered restrictions, on short selling, and where governments
have acquiesced to this pressure, such rules have had little market impact. Further,
he suggests that there is little or no evidence of short sellers being instrumental in
forcing prices lower in many of the occasions in which they have attracted blame
(i.e. the Asian currency crisis of 1997).
Although textbook accounts of asset pricing rely on unlimited arbitrage (and hence
short-selling), another school of thought sees definite limits to these processes (e.g.
Schleifer, (2000), Savor and Gamba-Cavazos (2005)). At its simplest, if short
selling is costly and hence constrained, the marginal investor will be an optimist
when a divergence of opinion exists (Miller (1977), see also Jarrow (1981)). The
key recent contribution of D’Avolio (2002), Nagel (2006), Ali-Trombley (2006) and
others is to calibrate and explain this cost of short selling in the real market context,
often in a relative rather than absolute metric, and apply such findings to reexamine
investment “anomalies” that are inconsistent with perfect arbitrage. As
they show very clearly, some major sources of predictable returns such as
momentum investing, and value versus growth, may appear unprofitable when real
world short selling costs are appropriately calibrated and hence this helps us
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discriminate between the mispricing and risk explanations for these “anomalies”,
(e.g. Ali, Hwang, and Trombley (2003)).
The growing popularity of hedge funds has led to more detailed analysis of the role
of short selling investment strategies. The use of accounting data, technical
analysis and tax strategies by market short sell professionals is described by Taulli
(2003), while the benefits of adding a short selling fund to a portfolio of other hedge
fund strategies in terms of risk-return improvements is explained in Jaeger (2003).
Basically short selling as a strategy is often the only one which has a negative
correlation with both other strategies and wider market indices, including equities
and bonds, and hence is important in determining the shape of the mean-variance
efficient frontier.
In the UK for FTSE 100 companies the average percentage of firms’ shares on loan
in the market has increased from 3½% in late 2003 to over 5% by late 2005
(Makinson Cowell (2005)); for FTSE 250 companies the average has risen from 2%
to 3% over the same period. Detailed figures for the US (e.g. D’Avolio (2002), show
similar average levels. These low figures are taken by many analysts as evidence
that restrictions must exist that thwart short sellers; since short selling is not done in
a centralised market, finding shares can sometimes be difficult or impossible, and
hence price may only partially equilibrate supply and demand. We can identify two
general types of restriction:
(i) Market structures are not set up to make short selling easy. Less than half
the world’s exchanges actually allow short-selling (Charoenrook and Daouk
(2005); there are regulations and procedures administered by the SEC and
Federal Reserve, stock exchanges, underwriters and brokerage firms that
can impede the mechanics of short selling, while legal and institutional
restrictions can seriously inhibit investors from selling short (see Savor and
Gamboa-Cavazos (2005)). The so-called “uptick rule” states that NYSE and
AMEX stocks can only be sold short at a price above the immediately
preceding reported price (the “plus-tick) or at the last sale price if it is higher
than the last reported price (“zero-plus” tick). NASDAQ prohibits its
members from short selling stocks at or below the current bid price.
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(ii) Deliberate action by firms’ management or advisers can be used to hurt
short-sellers, e.g. through subterfuge, private investigators, harassment via
civil suits, false accusations or appeals to regulators to intimidate short
sellers. Technical actions such as stock splits or distributions can disrupt
short selling, and management can work closely with shareholders to
withdraw shares from the stock lending market. Using a sample of 266 US
firms from 1977 to 2002 which had threatened, taken action against, or
accused short sellers of illegal activity or false statements, Lamont (2004)
finds abnormal returns of around -2% per month in the following year, and
returns continue negative for some years to follow, suggesting that short-sale
constraints can allow very substantial overpricing which will take some
considerable time to correct. The public policy aspects of these restrictions
are discussed in Lamont (2003)
There are two extreme views on whether a higher level of short interest conveys
positive or negative information on a stock: Diamond and Verrechia (1987) argue
that high short interest conveys negative information, with the constraints on short
selling raising costs and reducing its incidence by liquidity traders; hence short
selling is more likely to involve informed traders, and hence higher levels of short
interest reflect (genuine) negative information. On the other hand, what might be
called the ‘Wall Street’ view, is that high short interest is a bullish signal since it
represents a ‘latent demand’ for a stock, which will transform into actual purchases
at some point to cover this short position. A so-called third way would have short
interest as being essentially neutral for a stock: Senchak and Starks (1993)
emphasise how short selling may be driven by hedging strategies, arbitrage
transactions and tax related reasons. Indeed Barron’s magazine of May 1st, 1995,
cites a survey finding that 75% of short interest positions are either hedged or part
of some other trading strategy (see also Brent et al (1990)). This latter view would
suggest that short interest levels cannot help us predict market price reactions, (see
also Chen et al (2002)): this empirical issue has been a prime focus of applied work
in this area.
A number of general themes related to short selling have emerged of interest to
policymakers and academics:
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(i) From the theoretical perspective, do short-sale constraints, including costly
transactions, impede the speed of price adjustment to new information? Can
they help us understand market “anomalies” and distinguish between
mispricing and sources of risk? (e.g. Ali, Hwang and Trombley (2003))
(ii) Do changes in the level of short interest (i.e. lending) for a stock convey
positive or negative information about that security?
(iii) From a regulator’s point of view, can short sale restrictions reduce the
severity of price declines, and hence market stability? Recent studies
reviewing global short sale practices have allowed insight into this question
(Charoenrook and Daouk (2005)), Bris et al (2003)).
3. Short Selling: Institutional Structure
Despite its importance in the theory of finance, many academic and professional
finance practitioners have little precise knowledge of the nature and extent of short
selling. While this was perhaps largely due to the lack of publicly available data in
this area, this is changing with research based on proprietary information providing
new insights. D’Avolio (2002) is such a paper, utilising 18 months of daily loan
positions and transaction information for every US equity security on the books of
one of the largest (but unnamed) security lenders in the world. Ali and Trombley
(2006) describe the short selling process and some of D’Avolio’s (2002) key
statistics; at the risk of repetition we explain the process in a little more detail as it is
generally not well understood.
To short sell a share in company XYZ the seller, Agent A, must find an existing
owner of XYZ shares, Agent B, who is both able and willing to lend the shares.
Having negotiated the loan of the shares, ‘A’ may then short sell the borrowed
share to any willing purchaser, ‘C’.
The short seller (or borrower of the share) ‘A’ must deposit collateral with the
lender, ‘B’ equal, to 102% of the market value, marked to market daily: according to
industry sources, a tiny proportion, around 2%, is collateralised with Treasury
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securities, and the rest as cash. If the lender is a US broker-dealer then an
additional 50% margin is required, though this is not the case for trades between
broker dealers. In the UK and Europe transactions collateralised with cash are less
common but they are increasing: collateral may include both government,
corporate, and convertible bonds, as well as equities, and is typically 105% of the
value of the lent securities (Makinson Cowell, 2005).
So how does ‘B’ get rewarded for lending the stock? Clearly ‘B’ has use of the cash
collateral for as long as the stock is lent to ‘A’; so, the fee ‘A’ pays ‘B’ is actually a
reverse cashflow (usually!), ‘B’ paying ‘A’ a rebate for use of the cash collateral; this
rebate rate is analogous to ‘repo’ rate for bond lending, and comprises the market
rate for cash funds less the stock loan fee (which in extreme cases, as we shall see,
can be negative). Hence if the cash rate is 4% and the stock loan fee is 1.5%, then
the rebate from B to A would be 2.5% (4%-1.5%). If A and B agree to a rebate of -
35%, then A in effect pays B 39%, i.e. 35% plus 4% foregone interest. Note that
interest is calculated each business day and settled monthly.
One important piece of terminology in the literature distinguishes special stocks
from general collateral (or GC): the former refer to stocks with high fees (i.e. low
rebates) and the latter to those with the basic fee of around 15 basis points in the
US. This came about from another view of the whole process: if we view it as A
lending B cash with B offering stock as collateral; if B can replace the collateral with
any stock then it is called general collateral, wherein if a specific stock is involved A
will hold special collateral, and will charge a lower rate for the cash or Treasury
securities on loan at B. ‘A’ has to replicate and pay any dividends/distributions on
the borrowed stock, while B no longer has shareholder rights, such as voting.
Lenders rarely recall shares simply to exercise voting rights: there is a consensus,
certainly in the UK, that securities “should not be borrowed solely for the purpose of
exercising the voting rights” (Securities Borrowing and Lending Code of Guidance,
Bank of England Securities Lending and Repo Committee, December, 2004). At
the AGM of British Land in 2002 an activist investment fund, Laxey Partners, tabled
a motion to unseat the chairman and voted their 9% holding, of which 8% had been
borrowed for the purpose of voting (Makinson Cowell (2005)). Disclosure and
ownership of such holdings is under review by the Takeover Panel in the UK as of
mid-2005.
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A key feature of this stock lending procedure is that most lenders, especially
institutions, maintain the right to recall the loan at any time, and this may be driven
by legal or tax requirements: in the US for pension funds this is an explicit ERISA
requirement, while for mutual funds it is required under the Investment Company
Act of 1940. Similarly the IRS requires the recall rule for manufactured dividend
payments to stay as non-taxable income for certain exempt funds, and for the loan
not to be treated as a sale. Hence the loans are effectively rolled over each night
until the shares are returned voluntarily or recalled, at which point the borrower ‘A’
has 3 days to return the share, borrow from another investor, or cover the short sale
by buying the share; if after 5 days the shares are not returned to B, the latter has a
legal right to use the collateral to buy in the borrowed share on the open market.
Who provides the shares for short selling? The actual transaction is usually
effected by large custody banks (e.g. State Street) on behalf of institutional owners,
such as pension funds, mutual funds and endowments, with, unsurprisingly, passive
indexers the most actively involved in their custodian’s lending since their need for
specific stocks at any moment in time will be much less than that of an active
manager. The natural advantage of custodians as intermediaries here is that they
can replace recalled loans from a client by shares held on behalf of other
customers, offering a big reduction in disruption and search costs for borrowers.
Broker-dealers can also lend from their own market makers and trading desks, or
their own institutional customer accounts. Custody banks are the largest and most
reliable source of stock for lending.
Who actually gets involved in borrowing the stock? Clearly market makers will have
inventory management requirements, while derivatives traders will need to sell short
to hedge positions: hedge fund ‘long-short’ strategies have an obvious need, as do
merger and convertible arbitrage strategies.
In the US most stocks can be borrowed. D’Avolio (2002) offers detailed descriptive
statistics for the Center for Research in Security Prices (CRSP) universe from his
proprietary database for the period April 2000, through September 2001: at most
16% of the 8000 or so stocks on CRSP cannot be shorted, and these account for
under 1% of the total market capitalisation; over half of these are under $5 per
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share; and around 10% of the stocks are never shorted. The cost of shorting is for
the institution’s value-weighted lending portfolio, 25 basis points per annum, and
only 7% by value is actually borrowed; over 90% of the stocks lent out cost less
than 1% p.a. to borrow, and these so-called ‘general collateral’ stocks have a valueweighted
mean fee of 17 basis points; the remaining 9% of loaned stocks are
‘specials’, having fees above 1% and a mean fee of 4.3% p.a., with less than 1% of
stocks becoming ‘extremely special’, with negative rebate fees, i.e. loan fees in
excess of the risk-free rate. Celebrated cases of the latter include GM at 63% and
Unilever N.V. at 46% (see Table 4, p.287, D’Avolio (2002)).
In the UK the average (from proprietary data) is considered to be around 14 bp p.a.,
but is somewhat higher in other European markets at around 40 bp p.a. (Makinson
Cowell (2005)). Fees can go as low as 5 bp for large FTSE 100 stocks, or up to
400 bp (and beyond) for smallcap stocks.
Perhaps unsurprising given the sophistication of the intermediation process is that
recall is extremely rare, with only 2% of the stocks on loan being recalled in any
month in the US, though having been recalled the mean time before the short can
be re-established with the lender is 23 trading days. Forced covering of recalled
shorts tends to occur when trading volume is at least the daily average. Since the
largest suppliers of stock for lending are the large institutions, and these tend to
have a higher proportion of large cap, liquid stocks, then passive index funds have
a disproportionate presence in the loan market, and constituents of indices such as
the S&P 500 are provided in excess supply, and hence are nearly always ‘cheap’ to
borrow, i.e. are ‘general collateral’. Finally, what makes a stock ‘special’ (i.e.
expensive to borrow)? D’Avolio (2002) provides an empirical analysis suggesting
an inverse relation with market cap and institutional ownership (‘supply’), and a role
for heterogeneity of investor opinion, ‘demand’ (e.g. disparate analysts’ forecasts,
high turnover) (see also Nagel (2006), Chen et al (2002)). This approach is used
and extended by Ali and Trombley (2006) to calibrate the relative expense of short
selling a stock.
4. Short Selling: Data Issues and Research Implications
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However interesting the theoretical and practical issues alluded to earlier, without
high quality data there is little opportunity for the financial economist to shed much
light on an area. The literature on short selling has exploded over the last few years
precisely because new data is finally becoming available, albeit in a selective,
proprietary fashion. Whereas CRSP and NASDAQ have offered high frequency
data over various time periods for stock prices and related characteristics, short
interest data has only been available at monthly intervals, inhibiting event studies
and similar methods. Further, the cost of short selling has been almost entirely
unavailable until proprietary data has been obtained for studies such as D’Avolio
(2002) and Cohen et al (2005). More recently (2005, Q1) NASDAQ has made
available intraday data. Only Australia has had a substantial run of real time data
identifying short sales (Aitken et al (1998)), and hence such a study is unique
whereas in other markets there is an exhaustive array of such research (e.g. LIFFE
derivatives’ markets, see Buckle, et al (1998a)).
The absence of short sales costs has also proved a thorny issue, since trading
strategies/market anomalies based on arbitrage portfolios can be completely
misleading, (Ali-Trombley (2006), Nagel (2006)). One exception is the data used by
Jones and Lamont (2002) for 90 actively traded stocks per month for the period
1926-1933 (at which point the data was discontinued); these stocks appeared in a
centralised stock loan market on the floor of the NYSE, hence indicating high
shorting demand. Indeed, some had short selling costs of over 50% per annum:
stocks with high costs were associated with low subsequent returns, around 12-
24% lower than similar stocks over the following year, again suggesting they were
overpriced. This return predictability suggests that short selling costs keep
arbitrageurs from forcing down the prices of overvalued stocks, consistent with the
‘overpricing’ hypothesis.
That D’Avolio (2002) is able to offer direct insights into the short selling costs of a
large number of CRSP stocks facilitates the Ali-Trombley (2006) methodology of
identifying the factors which make certain stocks expensive to short sell and they
use this information in the context of momentum portfolio strategies to see if such
predictable returns are actually profitable. Clearly, empirical studies which involve
arbitrage strategies should really contain appropriate transaction costs, including
potentially substantial short selling costs, before we can feel confident on the
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efficacy of any strategy: this has been neglected to date in the literature but surely
should become integrated into mainstream anomaly studies when such data
becomes available. Indeed, the creation of a reliable database to complement
D’Avolio (2002) on the costs of short selling, both across stocks and over time,
would seem to be a priority for progress in scientific studies of arbitrage strategies.
Cohen et al (2005) go an important stage further in the analysis with proprietary
panel data for 4 years on both quantity and cost of short sales, and hence claim to
identify separately supply and demand shifts. In other words, a low level of short
interest may not indicate low short sale demand but limited supply. They find that it
is not so much high loan fees or high quantities of short interest that convey
information, but rather shifts in demand for short selling that dominate reductions in
supply. Even in a highly sophisticated capital market such as the UK stock market
there was much debate prior to average stock lending data being made available
monthly on CREST in September 2003 (see Section 8 below).
Hence, research on short-selling has suffered from a dearth of high frequency,
appropriate quantity data, the well nigh impossibility of separating quantity data into
that associated with hedging and arbitrage from that involving pure bets on price
falls, and the almost complete absence of information on the costs of short selling.
Hence attempts to identify demand and supply influences must necessarily be
incomplete. However, the collation of proprietary data on loan fees by D’Avolio
(2002) in particular gave new insights into the cost of short selling which were
previously not available. It also allowed calibration of economic influences on these
costs, which Ali and Trombley (2006) then extend backwards to 1984 from the
D’Avolio (2002) period of 2000-2001, giving themselves a longer data period to
examine strategies such as momentum investing. Nagel (2006) investigates the
low book-to-market overpricing with references to institutional ownership of shares
as a proxy for the lack of short selling supply, though clearly the multi-factor criteria
of Ali and Trombley (2006), if robust with respect to individual control variables as
well as a summary statistic in the form of an econometric model, should be superior
and lends itself to use in similar contexts, where such anomalies/investment
strategies are well documented. Ali, Hwang and Trombley (2003) also investigate
the book-to-market effect and use institutional ownership as a proxy for short-selling
costs, though they also include idiosyncratic stock volatility to capture arbitrage risk
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and the number of analysts following a stock as a measure of investor
sophistication.
D’Avolio himself (p.274, 2002) acknowledges that the loan fees on his sample do
not seem high enough to explain return anomalies or short selling reluctance; after
all only around 2-3% of US market capitalisation is short sold at any time. Rather,
they are useful in helping understand the limits to arbitrage, and help justify the Ali
and Trombley (2006) method of using proxies for loan fees based on observable
stock characteristics that capture loan demand by short sellers and available supply
combined as one measure reflecting the probability that the loan fee is high. The
five factors identified, including firm size and cash flow, can be the basis for
separate in depth analysis in parallel fashion. The fact that they omit some of
D’Avolio’s (2002) unimportant variables is less significant than the assumption that
the calibration is robust over an 18-year period. After all, this is an empirical area
with a dearth of relevant data and hence it is impossible to conclusively believe in
the results. However, given that the momentum returns are found to be robust with
respect to both the components of, and aggregate measure of the key variable,
short sale constraints, then we should have some confidence in the findings.
Nevertheless, since D’Avolio’s (2002) loan fee data is only for institutional
transactions, and over a limited time-period, complete comfort in loan fee costs is
not possible.
5. Short Selling Restrictions around the World
There have recently been two studies seeking to document the extent of shortselling
restrictions throughout the world. Bris et al (2003) examine 47 equity
markets for the period 1990-2001, quizzing regulators, investment banks and
institutional investors on the legality and practice of short-selling, in particular the
tax effects of short positions, settlement cycles, and the registration requirements of
short-selling. Charoenrouk and Daouk (2005) look at the history of both shortselling
and put option trading regulations and practices for 111 countries based on a
questionnaire for regulators covering the legality and feasibility of short-selling, and
whether put options are available for trading. Since Charoenrouk and Daouk (2005)
focus on market wide index returns, their data period extends from 1969 through
2002.
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Beginning from Diamond and Verrechia’s (1987) insight that short-selling
constraints impede the market’s ability to rapidly impound value relevant
information, both studies exploit the cross-section/time-series nature of their data to
address a variety of important policy issues. Bris et al (2003) suggest that markets
where short-selling is both legal and practised, show more efficient price discovery,
manifesting itself in reduced synchronicity in individual stock returns: more efficient
markets have more idiosyncratic risk, and the ratio of firm specific to market
information is higher, as agents can act quickly and inexpensively. Using a market
efficiency measure developed by Morck et al (2000), they find a negative
association between short-sales restrictions and the diffusion of value relevant
information into prices. Their second line of enquiry involves the conjecture by
regulators that short-selling restrictions can reduce the relative severity of market
panics, and this can be tested via examining the skewness of stocks and market
indices. There is weak evidence that for individual securities at least, restrictions
are associated with less negative skewness, and indeed a lower probability of an
extreme negative value. However, this does not carry over to the aggregate market
level, where the presence of restrictions does not seem to prevent market crashes.
An alternative approach is to look at the case where restrictions were lifted during
the sample period: here idiosyncratic risk rose on average by 27%, emphasising
the link between restrictions and individual stock behaviour, Charoenrouk and
Daouk (2005) also find no evidence that short-sale restrictions affect the level of
skewness of aggregate market returns, or indeed the probability of a market crash
occurring, though the volatility of stock returns is lower and liquidity is higher.
These findings arise from a panel study where the dependent variable is skewness
or volatility, or a proxy for market crashes or liquidity, while a binary variable
reflecting the country’s ability to take short positions appears on the right-hand side,
along with various control variables.
6. Short Selling and Stock Returns
A key question for analysts and policymakers is whether short selling actually leads
to predictable changes in stock prices. As we saw earlier, one school of thought
associated with practitioners is that a build-up of short interest may lead to a rise in
stock prices as it represents ‘latent demand’ for the stock which at some point will
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have to be covered. A major problem with establishing a link between short interest
and returns is that the former data has only been available in the US as a monthly
snapshot and hence high frequency studies which can remove contaminating
events have been difficult.
It is no surprise, then, that early research proved far from conclusive, with no clear,
unambiguous indication of the relation between short selling and subsequent stock
prices: for example, see Seneca (1967), Major (1968), Smith (1968); McDonald
and Baron (1973), using a random sample of 100 NYSE stocks for the five years up
to 1966 found a direct relation between short interest and risk (i.e. beta), with, on
average, a negative return accruing to short-sellers. Figlewski and Webb (1993)
also find no strong relation between short interest and abnormal returns, whereas
Senchak and Starks (1993) find that stocks with unexpected increases in short
interest generate statistically significant but small, negative abnormal returns for a
short period around the announcement data.
More recently Woolridge and Dickinson (1994) examined the relation for the NYSE,
Amex, and NASDAQ aggregate markets, and also for a random sample of 100
companies for the period 1986-91, the starting date being that at which shortinterest
data for NASDAQ first became available. Based upon simple regression of
returns on changes in short interest, together with control variables such as size
and market return, the results ‘provide strong refutation of the popular notion that
short sellers earn abnormal profits at the expense of less informed investors’ (p.20).
If anything, the finding of a positive relation between short-selling and returns
(adjusted both for risk and market movements) for companies suggests that on
average short sellers are actually selling as stock prices rise and reducing short
positions as they fall, in other words acting as a moderating, contrarian, force.
Overall, they find that a high level of short interest is not necessarily a bullish or a
bearish indicator for stock prices, and also that short-sellers on average do not
possess superior investment timing skills. Rather, they seem to act as stabilising
liquidity providers.
A much improved data offering is provided by the Australian Stock Exchange, ASX,
which gathers trade data, including short sales information, and sells it on to
brokers and institutions online in real time; hence short selling related activity
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becomes transparent very soon after the time of trade execution. Such intraday
data lends itself to a high frequency event study, unlike the monthly discrete US
data. Using data on all orders placed, as well as trades executed on the electronic
trading system of ASX, from 1994-1996 inclusive, Aitken et al (1998) offers a rich
descriptive insight into short selling behaviour, and finds an average -0.20% fall in
stock value within 15 minutes or 20 trades (see Buckle et al (1998b) for evidence of
more rapid adjustment within other markets), offering some evidence in support of
the Diamond-Verrechia (1987) hypothesis that short trades are more informative
than sell trades due to restrictions on short selling.
Further analysis of US data still had to make do with short interest information at
monthly intervals, so the focus turned to more extensive coverage of stocks and to
subsets with particular features of interest, such as intensive short selling. Desai et
al (2000) examined all NASDAQ listed stocks with any short interest for the period
1988-1994, taking the view that since listing requirements are easier on NASDAQ
than NYSE, then informational asymmetry is likely to be greater and hence short
interest may well be more informative for NASDAQ stocks. Indeed, they find that
‘high’ short interest stocks (i.e. those with over 2½% of shares outstanding sold
short), have significantly negative abnormal returns -0.76% per month, falling to -
1.13% per month for those with short interest over 10%, and in contrast to Aitken et
al (1998), such information is gradually absorbed into prices. This suggests strong
support for the ‘academic’ view that short interest is a bearish signal for a stock
(Diamond-Verrechia (1987)), and indeed the strength of the signal rises both with
the level of short interest and the length of time it is heavily shorted. An interesting
adjunct finding is that high short interest is associated with a high rate of delisting
and/or liquidation; indeed nearly 13% of firms with a short interest of over 2.5% of
shares outstanding are so affected within 36 months.
Lamont and Stein (2003) examine aggregate short interest for both the NYSE and
NASDAQ and find that it varies counter cyclically, and that the ratio of put-to-call
option volumes displays a similar pattern. Whereas in cross-section data it is
generally considered that the most ‘overvalued’ stocks attract the most short selling
demand (see Dechow et al (2001), over time total short interest in NASDAQ
stocks during the recent dot-com bubble actually decline as the index approaches
its peak; this is consistent with Schleifer and Vishny (1997) who argue that the
16
open-ended nature of most professional arbitrage firms makes it difficult for these
firms to resist aggregate mispricings. This also suggests that short-selling does not
act as a stabilising force for overall stock market movements.
The need for improved data for US markets to give a more robust understanding of
the nature and implications of short selling is met to some degree by the study of
Diether et al (2005). They use newly SEC-mandated tick-by-tick NASDAQ data for
Q1, 2005, to look at the link between short-selling activity and future returns. The
data allows identification of trade size and the separation of short sales by investors
who are subject to rules from market makers who are exempt. A major finding from
this new data is that short sales represent on average around 25% of NASDAQ
reported shares volume, whereas monthly short interest data reveals a short
interest of only 3.3%, suggesting for the first time that a high fraction of short sales
in daily volume involves intraday or at least short-term trading strategies, and that
the monthly ‘snapshot’ may well represent window dressing. Of this 25%, twothirds
is short-sales by traders subjects to short-sale rules. The other key finding is
that short-sellers are, on average, contrarian, selling short after positive returns, a
result similar to Woolridge and Dickinson (1994). Higher short sales predict future
negative returns, in some cases up to 5 days ahead, but a trading strategy based
on daily short selling incurs costs large enough to remove any profits. It is basically
small trades that have predictive power. However, Savor and Gamboa-Cavazos
(2005) find that short sellers cover their positions after suffering losses and increase
them after gains.
7. Short Selling and Earnings’ Announcements
Do short sellers pay particular attention to the quality of earnings and the
announcement of earnings? Are they able to exploit earnings’ based anomalies?
The literature suggests that short sellers both anticipate earnings surprises and
trade after earnings’ announcements. Cao and Kolasinski (2005) examine whether
short sellers exploit two well documented anomalies, namely post-earnings
announcement drift and the accrual anomaly; in particular, is the intensity of shortselling
related to the severity of the market under/overreactions to earnings and
accruals? Indeed, short sellers attempt to exploit both anomalies, though
surprisingly perhaps, there is no evidence that prices converge more quickly to
17
fundamental levels in the presence of short selling. Using (monthly) data from
NASDAQ for the period 1995-2003, and looking at short interest for the newest
month-long period that begins after the earnings announcement, the study
examines returns for 182 days after an earnings’ announcement/surprise, it finds
that short sellers can earn high returns by short selling stocks that have negative
earnings’ shocks and high income increasing accruals (the latter being in contrast to
Richardson (2003), who looks at accruals in isolation). In contrast Cristophe et al
(2004) look at short sales in the 5 days before earnings announcement for a sample
of over 900 NASDAQ firms; they find a significant negative relationship between
unusual short selling activity before the announcement and the subsequent postannouncement
change in stock pricing, suggesting that a significant proportion of
short sellers are informed traders. Further analysis suggests that while the
transactions are in part influenced by the fundamental characteristics of firms, the
selling is more likely to be related to information specific to the forthcoming
announcement. Clearly, making short selling information more quickly and readily
available could improve market efficiency in this context.
8. UK Experience: Stock Lending, Dividend Arbitrage and Crest
As we noted earlier, data limitations in the US and elsewhere have hindered
empirical analysis of short-selling, though this is being gradually reversed. In
September 2003, Crest, the UK’s stock clearing house began to make available
data on what has been described even by practitioners as ‘a little known and
opaque area of the UK stock market’ (see Chambers (2004)), namely stock lending.
Crest offers monthly average stock lending positions for FTSE 350 companies
(together with some large Irish companies) on its website, www.crestco.co.uk and,
more frequently, with a one-week delay, by subscription. However, we should note
that not all shares of a stock will be ‘in Crest’, since this refers to electronic, noncertified
holdings of shares. Yet preliminary analysis by Chambers (2004) for FTSE
350 companies finds a close correlation between shares in issue and shares in
Crest, and also between the percentage of shares on loan and the proportion held
inside and outside of Crest: hence the proportion of stock lending on a particular
stock is generally independent of how it is held, and thus Crest data should give a
good indication of the extent of stock lending, both by stock and over time. Table 1
below shows the equally weighted average of the stock on loan within the CREST
18
system to be between 3% and 4½% since the inception in September 2003.
However, for individual stocks this can rise to over 40% at various times. Figure 1
shows a simple plot of the stock loan percentage for 3 large UK firms: EGG did not
pay a dividend over this period but still had levels above 10% at times, British
Aerospace had a clear peak at 25% or more, possibly associated with cash
dividend arbitrage (see Makinson Cowell (2005)), while Prudential had notable
spikes but at a lower level of around 5% which may reflect scrip dividend arbitrage
(again see Makinson Cowell (2005)): daily data for the latter would have revealed
much greater percentage spikes.
Of course, not all borrowed stock is for short selling: for example, ‘fails
management’ required stock lending if a clearing transaction fails, say due to a
computer failure, and it takes place simply for technical purposes rather than a
portfolio trade: hence it is essentially market neutral. Dividend arbitrage is another
reason to borrow stocks common to the UK. This may refer to cash dividends,
whereby the differential tax rules faced by different investors may be exploited: the
Makinson Cowell (2005) review points to French tax rules providing French
investors with a 10% tax credit on dividend income which is not available to UK
investors. An institution, often a French bank, agrees to borrow UK equities ahead
of the dividend record data in order to receive the dividend payment. Clearly this
borrower can derive a greater net dividend return from the stock than the lender,
and hence can compensate the lender and still profit. Such stock lending activity
can be very significant, raising to above 10% of stock in Crest around dividend
dates for FTSE 100 companies, compared to a year round average of 5% or less.
A related source of borrowing stocks is scrip dividend arbitrage, whereby an issuer
offers shareholders the choice of receiving a cash dividend or a scrip dividend at a
discount to market price, but certain funds, such as index traders, cannot take the
scrip alternative as their holdings would become larger than allowed under their
portfolio guidelines. In this case, stock can be lent out with the borrower choosing
the script alternative and selling in the market and using the proceeds to pay the
lender the cash dividend, with the borrower making a profit equal to the difference
between the market value of the shares and the cash dividend, less the stock
lending fee. The lending period for this activity is much shorter than for cash
dividend arbitrage and the percentage of Crest stocks lent out can jump above 20%
from an average of 2% in certain instances.
19
9. Concluding Comments
If overpricing of costly-to-short sell, low book-to-market stocks generates a big part
of the book-to-market effect (Nagel (2006)), Ali, Hwang and Trombley (2003)), and
similar conclusions apply to the overpriced losers in Ali and Trombley (2006), then a
new insight is emerging that puts short sales constraints at the centre of our
understanding of certain investment strategies/market anomalies which rely on
some categories of stocks becoming overpriced. Nagel (2006) sees much of the
value premium arising from market segments where its existence appears to be
most consistently explained by mispricing and short sale constraints, rather than by
covariance with some underlying risk factor. Hence just as book-to-market has
entered textbook asset pricing as part of a ‘three-factor’ model, so short selling
constraints appear to challenge this approach with an alternative interpretation: if
arbitrage costs exceed arbitrage benefits than systematic mispricing may persist
(Schleifer and Vishny (1997)). Similarly, momentum, while not given quite the same
exposure as a factor as ‘value’, may also be considered to be at least partly
explicable by short sales constraints. Ali and Trombley (2006) do much more than
construct ‘a reliable index of short sales constraints using easily observable stock
characteristics’; their results suggest that other predictable return regularities should
be investigated to assess the importance of short sales constraints in these
processes. Ofek et al (2002) establish the importance of such costs for options
strategies.
Most investors never short sell, yet for most large capitalisation stocks it is not
difficult to short sell; we still do not know why so little short selling takes place.
Constraints which are difficult to calibrate, such as information shortfall, cultural, risk
perceptions, and institutional behaviour may be behind this. Yet the more
persuasive evidence presented here suggests that short sales are a stabilising
(contrarian) force and their introduction into a wide variety of countries has not been
associated with an increased likelihood of a financial crash. However, more
conclusive analysis of the role of short sales on investment regularities requires
data on both the quantity and price of short selling at a higher frequency than is
currently available.
20
References
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Buckle, M., ap Gwilym, O., Thomas, S.H. and Woodhams, M., (1998b), ‘Intraday Empirical
Regularities in Interest Rate and Equity Index Futures Markets and the Effect of
Macroeconomic Announcements’, Journal of Business Finance and Accounting, Vol. 25
(September/October), pp. 921-944.
Cao, B. and Kolasinski, A.C., (2005), ‘Bears and Numbers: Investigating How Short
Sellers Exploit and Affect Earnings Based Pricing Anomalies’, MIT Working Paper.
Chambers, C., (2004), ‘Stock Lending Data Offers Key Insights’, Traders, (May/June), pp.
64-67.
Chancellor, E., (2001), A Short History of the Bear, David Tice & Co., London.
21
Chen, J., Hong, H. and Stain, J.C., (2002), ‘Breadth of Ownership and Stock Returns’,
Journal of Financial Economics, Vol. 66 (November/December), pp. 171-205.
Charoenrook, A. and Daoak, H., (2005), ‘A Study of Market-Wide Short Selling
Restrictions’, Vanderbilt University Working Paper.
Cohen, L., Diether, K., and Malloy, C.J., (2005), ‘Supply and Demand Shifts in the Shorting
Market’, University of Chicago Working Paper.
Cristophe, S.E., Ferri, M.G. and Angel, J.A., (2004), ‘Short-Selling Prior to Earnings
Announcements’, Journal of Finance, Vol. 59 (August) pp. 1845-1875.
D’Avolio, G., (2002), ‘The Market for Borrowing Stock’, Journal of Financial Economics,
Vol. 66 (November/December), pp. 271-306.
Dechow, P., Hutton, A.P., Muelbrook, L. and Sloan, R.G., (2001), ‘Short Sellers,
Fundamental Analysis and Stock Returns’, Journal of Financial Economics, Vol. 61 (July),
pp. 77-106.
Desai, H., Ramesh, K., Rama Thiagarajan, S. and Balachandran, B.V., (2002), ‘An
Investigation of the Informational Role of Short Interest in the NASDAQ Market’, Journal of
Finance, Vol. 57 (October), pp. 2263-2287.
Desai, H., Krishnamurthy, S. and Venkataraman, K., (2005), ‘Do Short Sellers Target
Firms with Poor Earnings’ Quality? Evidence from Earnings’ Restatements’, Southern
Methodist University Working Paper.
Diamond, D.W. and Verrechia, R.E., (1987), ‘Constraints on Short Selling and Asset Price
Adjustments to Private Information’, Journal of Financial Economics, Vol. 18 (June), pp.
277-311.
Diether, K.B., Malloy, C. and Scherbina, A., (2002), ‘Differences of Opinion and the Cross-
Section of Stock Returns’, Journal of Finance, Vol. 57 (October), pp. 2113-2141.
Fama, E.F. (1965), ‘The Behaviour of Stock Market Prices’, Journal of Business, Vol. 38
(January), pp. 34-106.
22
Fama, E.F., (1970), ‘Efficient Capital Markets: A Review of Theory and Empirical Work’,
Journal of Finance, Vol. 25 (May), pp. 383-417.
Figlewski, S., (1981), ‘The Informational Effects of Restrictions on Short Sales: Some
Empirical Evidence’, Journal of Financial and Quantitative Analysis, Vol. 16 (November),
pp. 463-476.
Figlewski, S. and Webb, G.P., (1993), ‘Options, Short Sales, and Market Completeness’,
Journal of Finance, Vol. 48 (June), pp.761-777.
Geczy, C.C., Musto, D.K. and Reed, A.V., (2002), ‘Stocks are Special Too: An Analysis of
the Equity Lending Market’, Journal of Financial Economics, Vol. 66
(November/December), pp. 241-269.
Jaeger, R.A., (2003), All About Hedge Funds, McGraw-Hill.
Jarrow, R., (1980), ‘Heterogeneous Expectations, Restrictions on Short Sales, and
Equilibrium Asset Prices’, Journal of Finance, Vol. 35 (December), pp. 1105-1113.
Jones, C.M. and Lamont, O.A., (2002), ‘Short Sales Constraints and Stock Returns’,
Journal of Financial Economics, Vol. 66 (November), pp. 207-239.
Lakonishak, J., Schlaifer, A. and Vishny, R.W., (1994), ‘Contrarian Investment,
Extrapolation and Risk’, Journal of Finance, Vol. 49 (December), pp. 1541-1578.
Lamont, O.A. and Thaler, R.H., (2003), ‘Can the Market Add and Subtract? Mispricing in
Tech Stock Carve-Outs’, Journal of Political Economy, Vol. 111 (April), pp.227-268.
Lamont, O.A. and Stein, J.C., (2004), ‘Aggregate Short Interest and Market Valuations’,
American Economic Review, Vol. 94 (May), pp. 29-32.
Lamont, O.A., (2003), The Long and Short of Hedge Funds: Effects of Strategies for
Managing Market Risk, Testimony of the US House of Representatives, May 22nd.
23
Lamont, O.A., (2004), ‘Go Down Fighting: Short Sellers vs. Firms’, NBER Working Paper
No. 10659.
MacDonald, J. and Baron, D., (1973), ‘Risk and Return on Short Positions in Common
Stocks’, Journal of Finance, Vol. 28 (March), pp. 97-107.
Mackinson Cowell, (2005), Stock Lending – A Perspective.
Mayor, T., (1968), ‘Short Trading Activity and the Price of Equities’, Journal of Financial
and Quantitative Analysis, Vol. 3 (September), pp. 283-298.
Miller, E.M., (1997), ‘Risk, Uncertainty and Divergence of Opinion’, Journal of Finance,
Vol. 32 (September), pp. 1151-68.
Morck, R., Yeung, B. and Yu, W., (2000), ‘The Information Content of Stock Markets: Why
do Emerging markets Have Synchromous Stock Price Movement?’, Journal of Financial
Economics, Vol. 58, No. 1&2, pp. 215-260.
Ofek, E., Richardson, M. and Whitelaw, R.F., (2002), ‘Limited Arbitrage and Short Sales
Restrictions: Evidence from the Options’ Markets’, Stern School of Business Working
Paper.
Nagel, S., (2006), ‘Short Sales, Institutional Investors, and the Book-to-Market Effect’,
Journal of Financial Economics, Forthcoming.
Richardson, S., (2003), ‘Earnings Quality and Short Sellers’, Accounting Horizons, Vol. 17
(January), Supplement, pp. 49-61.
Ross, S.A., (1976), ‘The Arbitrage Theory of Captial Asset Pricing’, Journal of Economic
Theory, Vol. 13 (December), pp. 341-360.
Savor, P. and Gamboa-Cavazos, M., (2005) ‘Holding on to Your Shorts: When Do Short
Sellers Retreat?’, Havard University Working Paper.
24
Senchack, A.J. and Starks, L.T., (1993), ‘Short-Sale Restrictions and Market Reactions to
Short-Interest Announcements’, Journal of Financial and Quantitative Analysis, Vol. 28
(June), pp. 177-194.
Seneca, J., (1967), ‘Short Interest: Bearish or Bullish?’, Journal of Finance, Vol. 22
(March), pp. 67-70.
Schleifer, A. and Vishny, R.W., (1997), ‘The Limits of Arbitrage’, Journal of Finance, Vol.
52 (March), pp. 35-55.
Schleifer, A., (2000), Inefficient Markets, O.U.P..
Smith, R., (1968), ‘Short Interest and Stock Market Prices’, Financial Analysts Journal, Vol.
24 (November/December), pp. 151-154.
Taulli, T., (2003), Streetsmart Guide to Short Selling, McGraw-Hill.
Woolridge, J.R. and Dickinson, A., (1994), ‘Short Selling and Common Stock Prices’,
Financial Analysts Journal, Vol. 50 (January/February), pp. 20-28.
25
Figure 1
Stock Loan Percentage of BAE Systems,
Prudential and Egg
0
5
10
15
20
25
30
Sep-03 Feb-04 Aug-04 Jan-05 Jun-05 Nov-05
Month
Stock on Loan (%)
BAE PRU EGG
Table 1
Summary Statistics for the Average Monthly Stock on Loan in the CREST
System Sep 2003 – Nov 2005
Month Average Stock on
Loan per
Company (%)
Maximum Stock
on Loan for
Individual
Company (%)
Minimum Stock
on Loan for
Individual Share
(%)
Sep-03 3.09 38.66 0.00
Oct-03 3.22 42.01 0.20
Nov-03 3.16 43.52 0.11
Dec-03 3.09 45.09 0.19
Jan-04 2.99 43.39 0.11
Feb-04 3.15 39.85 0.11
Mar-04 3.44 44.58 0.15
Apr-04 3.47 41.01 0.09
May-04 3.69 42.90 0.16
Jun-04 3.72 42.80 0.00
Jul-04 3.98 42.22 0.00
Aug-04 4.24 43.08 0.00
Sep-04 4.29 44.87 0.16
Oct-04 4.14 25.84 0.13
Nov-04 4.05 29.97 0.14
Dec-04 3.66 27.55 0.12
Jan-05 3.35 23.85 0.19
Feb-05 3.55 25.81 0.11
Mar-05 3.88 23.00 0.04
Apr-05 4.20 25.85 0.05
May-05 4.16 26.13 0.02
Jun-05 4.02 28.55 0.15
Jul-05 4.06 21.79 0.02
Aug-05 4.09 24.49 0.27
Sep-05 4.15 24.02 0.14
27
27
Oct-05 4.29 23.75 0.13
Nov-05 4.50 29.38 0.12

Berthelsen: Data Shows Heavy Airline-stock Short Selling
Source: San Francisco Chronicle

PDF, 168K (http://physics911.ca/pdf/2001/berthelsen_short_selling.pdf)
From http://www.sfgate.com/cgi-bin/article.cgi?file=/chronicle/archive/2001/09/22/BU27558.DTL :

[edit]Data shows heavy airline-stock short selling
[edit]Christian Berthelsen
San Francisco Chronicle Staff Writer
September 22nd 2001

——————————————————————————–

In another sign that some investors speculated against the stocks of airlines whose jets were used in terrorist attacks on New York and the Pentagon, there was a sharp increase in short selling of the stocks of American and United airlines during the month before Sept. 11.

The trading activity far outpaced the rise in short selling for all stocks on the New York Stock Exchange — or other major airline stocks as a group on the Big Board — according to a computer analysis by The Chronicle of data released yesterday by the New York Stock Exchange.

A short sale is essentially a financial market bet that the value of a particular stock will drop. In a successful short sale, an investor borrows the stock from a broker, sells it and then repurchases it at a lower price, returning the shares to their owner and turning a profit on the difference.

Federal securities and law enforcement investigators have been looking at unusual trading activities in the stocks of AMR Corp. and UAL Corp., the parent companies of American and United, as well as a number of other securities in the days leading up to the terrorist attacks. Specifically, the investigators want to determine whether someone with advanced knowledge of what would happen was trying to profit on the ensuing financial downturn.

The data released yesterday is part of the NYSE’s regular monthly report on short-selling. It shows that investors shorted nearly 4.39 million shares of UAL in portions of August and September. That represented an increase of 1.25 million shares, or 40 percent over the previous month’s level.

Meanwhile, investors shorted more than 2.98 million shares of AMR, a jump of nearly 497,000 shares, or 20 percent above what it was in August.

Those increases were far larger than the average shorting of stocks for the two companies’ major competitors on the exchange, including Delta, Continental,

US Airways and Southwest. As a group, the competitors saw an increase in shorting of only 11 percent. And shorting on the exchange overall totaled only a one percent increase.

As reported previously, some of the suspicious trading under investigation by market monitors, the FBI and the Securities and Exchange Commission include an unusual spike in the purchase of “put” options on the stocks of AMR and UAL.

A put is essentially a bet that the stock will decline, giving the buyer the right to sell the stock at a set price at a set time and delivering profits when the share price drops lower than the agreed sale price.

To be sure, there are a number of legitimate reasons to account for the increase in short selling that have nothing to do with terrorism.

For instance, the airline industry was in serious finance trouble even prior to the attacks, as business and consumer travel demand slacked off in a weakening economy. And both AMR and UAL posted huge second-quarter losses in July and said they could be in the red for the rest of the year.

What’s more, short-selling on the exchange has become increasingly prevalent. Each month has seen a record high, with a new peak of 5.98 billion shares shorted this month.

Still, anyone shorting shares of AMR and UAL would have turned a strong profit. UAL closed yesterday at $17.13 per share, off 44 percent from its close of $30.82 the day before the attack. AMR is down 40 percent, closing at $17.90 yesterday from $29.70 on Sept. 10.

Only one carrier, US Airways, saw a higher jump in short sales, with an increase of 41 percent. But there were obvious reasons to short that company: US Airways is laden with debt and was the target of a takeover bid from United that failed in July.

As with put options, it is difficult to tell how much money was made in the short selling of UAL and AMR stocks without more specific information about sale and repurchase prices and dates of execution.

Retrieved from “http://www.physics911.ca/Berthelsen:_Data_Shows_Heavy_Airline-stock_Short_Selling”
Categories: Author: Berthelsen, Christian | Topic: Insider Trading

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Short Selling: Introduction

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Have you ever been absolutely sure that a stock was going to decline and wanted to profit from its regrettable demise? Wouldn’t it be nice to see your portfolio increase in value during a bear market? Both scenarios are possible. Many investors make money on a decline in an individual stock or during a bear market, thanks to an advanced investing technique called short selling.

Short selling is neither terribly complex nor entirely simple. In other words, it’s a concept that many investors have trouble understanding. In general, people think of investing as buying an asset, holding it while it appreciates in value, and then eventually selling to make a profit. Shorting is the opposite: an investor makes money only when a shorted security falls in value.

Short selling involves many unique risks and pitfalls to be wary of. The mechanics of a short sale are relatively complicated compared to a normal transaction. And, as always, the investor faces high risks for potentially high returns. It’s essential that you understand how the whole process works before you get involved.

Next: Short Selling: What Is Short Selling?

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John D. Finnerty

Professor of Finance, Fordham University

March 2005

John D. Finnerty

Fordham University Graduate School of Business

113 West 60th Street

New York, NY 10023

Tel: 212-599-1640

Fax: 212-599-1242

e-mail: finnerty@finnecon.com

The SEC recently adopted Regulation SHO to tighten restrictions on short selling and curb

abusive short sales, including naked shorting masquerading as routine fails to deliver. This paper

models market equilibrium when short selling is permitted and contrasts the equilibrium with

and without manipulators among the short sellers. I explain how naked short selling can

routinely occur within the securities clearing system in the United States and characterize its

potentially severe market impact. I show how a recent securities innovation called floating-price

convertible securities can resolve the unraveling problem and enable manipulative short selling

to intensify.

1. Introduction

Manipulative short selling has a long and colorful history that dates back to the origins of

organized stock markets (Allen and Gale, 1992). Bernheim and Schneider (1935) describe how

bear pools operated on the Amsterdam Stock Exchange during the late seventeenth century.

Stock manipulators carefully timed their aggressive ‘bear raids’ to exert maximum selling

pressure. The price declines attracted free riders, and the combined pressure on the prices of the

targeted stocks produced virtually assured profits. The manipulators found that they could defeat

any opposition by employing “tricks that only sly and astute speculators invent and introduce,”

such as planting false rumors about the target firm’s precarious condition in the press (Bernstein

and Schneider, 1935). When similar manipulation occurred on the London Stock Exchange in

the early eighteenth century, the British parliament passed a law prohibiting short selling in

1734. The law was not repealed until 1860, and short selling was not specifically authorized

under English law until 1893 (Bernstein and Schneider, 1935). Numerous histories document

how these and other manipulative short selling techniques have been woven into the fabric of the

stock market.1

2

The SEC defines a short sale as the “sale of a security that the seller does not own or that

the seller owns but does not deliver. In order to deliver the security to the purchaser, the short

seller will borrow the security, typically from a broker-dealer or an institutional investor.”2 The

potential for abuse in short selling is a concern to market participants, regulators, and academics

alike.3 The SEC adopted Regulation SHO on July 28, 2004 to tighten the restrictions on short

selling and curb abusive short sales, such as naked short selling (SEC, 2003b, 2004).4 The SEC

proposed new Regulation SHO in October 2003 because of growing concern that naked short

selling masquerading as routine fails to deliver had impaired market efficiency:

Many issuers and investors have complained about alleged “naked short selling,”

especially in thinly-capitalized securities trading over-the-counter. Naked short selling is

selling short without borrowing the necessary securities to make delivery, thus potentially

resulting in a “fail to deliver” securities to the buyer. Naked short selling can have a

number of negative effects on the market, particularly when the fails to deliver persist for

an extended period of time and result in a significantly large unfulfilled delivery

obligation at the clearing agency where trades are settled. At times, the amount of fails to

deliver may be greater than the total public float. In effect the naked short seller

unilaterally converts a securities contract (which should settle in three days after the trade

date) into an undated futures-type contract, which the buyer might not have agreed to or

that would have been priced differently. The seller’s failure to deliver securities may also

adversely affect certain rights of the buyer, such as the right to vote. More significantly,

naked short sellers enjoy greater leverage than if they were required to borrow securities

and deliver within a reasonable time period, and they may use this additional leverage to

engage in trading activities that deliberately depress the price of a security. (SEC, 2003b,

pages 6-7.)

Used appropriately, short selling promotes market efficiency by eliminating overpricing

(Diamond and Verrecchia, 1987, D’Avolio, 2002, Duffie, Garleanu, and Pedersen, 2002, and

3

Jones and Lamont, 2002).5 However, when left unchecked, short selling can artificially depress

share prices and impair market efficiency (SEC, 2003b).6 Whether short selling has this

unintended effect depends on first, whether there are rules and regulations that prohibit

potentially abusive behavior and second, whether regulatory enforcement is adequate to ensure

that market participants obey these rules (SEC, 2003b).

Manipulation is the “intentional interference with the free forces of supply and

demand.”7 A manipulative trading strategy corrupts the market’s price formation process to

generate a riskless profit (Jarrow, 1992). Market manipulation can be profitable when there is a

difference between the price elasticities of purchases and sales that the manipulator can exploit.

Stock market manipulators use a variety of devices, such as releasing false information about a

company into the market,8 and employing trading strategies that impede the price formation

process, such as naked shorting, wash sales, matched trades, and painting the tape, all of which

inject misleading trading information into the market, to move market prices in the direction that

benefits the manipulator. Illegal short selling, such as naked shorting, can distort market prices

by creating artificial supply-demand imbalances (Thel, 1994). Consequently, the securities laws

in the United States proscribe various restrictions on short selling that are designed to constrain it

so that it can not be misused to manipulate stock prices below the true asset value (Thel, 1994,

SEC, 2003b, 2004).

4

Manipulation can occur when informed traders can take advantage of uninformed traders

who must trade to meet their liquidity needs (Glosten and Milgrom, 1985, Kyle, 1985, 1989,

Easley and O’Hara, 1987, Allen and Gale, 1992, Allen and Gorton, 1992). Allen and Gale (1992)

examine trade-based manipulation, in which a trader can manipulate a stock’s price upward

simply by buying shares and then sell them at a profit even when the purchases do not cause any

price momentum. Manipulation in their model does not require traders who take overt action to

alter the value of the firm, inject false information into the market to move the price higher, or

create a corner. Asymmetric information and the difference in the price elasticities of purchases

and sales are the key factors. Uninformed traders are uncertain whether the buyer knows that the

stock is undervalued or instead intends to manipulate the price upward. Purchases have a greater

price elasticity than sales due to the greater information content of purchases when the sellers

include liquidity traders. Uninformed liquidity traders have less freedom to time their sales, and

so informed traders, such as corporate insiders, are able to profit by exploiting both their

information advantage and the liquidity traders’ timing disadvantage. When liquidity sales are

more likely than liquidity purchases, a purchase conveys more information because it is more

likely that the trader is informed. The share price elasticity with respect to purchases exceeds the

price elasticity with respect to sales, and a pooling equilibrium can occur in which price

manipulation is profitable.

My model is in the spirit of Allen and Gale (1992) but focuses on short sales. I include

active traders (arbitrageurs), who turn out to be the critical enabling factor that facilitates

manipulative short sales in market equilibrium. I assume that active traders are uncertain whether

the seller knows that the stock is overvalued or instead intends to manipulate the stock price

downward. They are less knowledgeable than informed investors or manipulators but more

knowledgeable than uninformed traders. Active traders seek out information regarding the firm’s

5

prospects and look for signals in the trading behavior of informed investors, such as corporate

insiders. They sell in response to short sales by informed investors and manipulators, whom they

mistake for informed investors, which allows manipulative short selling to be profitable.

Active trader selling can resolve the unraveling problem and allow profitable

opportunities for manipulative short selling. The unraveling problem would rule out trade-based

short sale manipulation if the market consisted only of informed traders and liquidity traders. It is

more difficult to justify forced purchases than forced sales by liquidity traders, who presumably

do not have the same pressing need to buy as to sell (Allen and Gorton, 1992). The asymmetry in

price elasticities that creates an opportunity for manipulative purchases to be profitable rules out

profiting from manipulative short sales. A manipulator can repeatedly buy stocks and then sell

them to earn a profit because purchases having the greater price impact. But selling and then

buying would have the opposite effects and result in a loss.

Active traders interact with the informed investor to create downward price momentum.

Jarrow (1992) investigates how manipulation can occur when large trades create price

momentum that leads to a difference between the price elasticities of purchases and sales. Price

momentum occurs when trades are large enough to move the price and an increase in price at one

date causes an increase in price at a later date. A large trader’s purchases create upward price

momentum, and then she trades against the price trend to lock in her profit by selling to noise

traders who buy at the inflated price. Presumably this sort of manipulation could work in reverse

with the large trader selling short to stimulate downward price momentum and then covering his

short position by buying at depressed prices from noise traders. In my model active traders sell in

the next period when they observe that the informed investor has sold shares, which moves the

price downward. The informed investor can cover his short by buying from the active traders, or

he can wait until after the further drop in price to cover, depending on how costly it is to carry

6

the short position another period. However, I do not make any special assumptions regarding the

relative price elasticities of buys and sells. I also do not assume forced buying or selling by any

class of traders. I assume that uninformed traders are willing to buy more shares at lower prices

than those currently prevailing. Trade-based short sale manipulation is sustainable in a market

setting in which due to information asymmetries, it is unclear whether the seller has negative

information about the firm’s prospects or is simply trying to manipulate the firm’s stock price.

Naked short selling can increase the manipulator’s profit. A short seller, who profits by

buying the shares to cover her short position at lower prices than the selling prices, can drive the

price of a stock lower by selling short a larger number of shares. Without enforceable restrictions

requiring short sellers to borrow the shares before they can commit to sell, a short seller might

destabilize the market for a particular stock through naked shorting.9 While some naked shorting

may take place for benign reasons, for example because it lowers the cost of short selling (Evans,

Geczy, Musto, and Reed, 2003), Regulation SHO reflects the SEC’s concern that previous

restrictions on short selling had not been effective in preventing its use as a manipulative device

(SEC, 2003b, 2004).10 There is mounting evidence that manipulative short selling has seriously

disrupted the market for some over-the-counter stocks.11

7

The unraveling problem should impose a constraint on naked shorting. There are two

mechanisms for avoiding this constraint. Since a firm’s common stock claims are extinguished if

it liquidates, a manipulative short seller can effectively cover its short position at zero cost by

forcing the firm into liquidation (House Report, 1991). Second, a popular private equity

financing instrument, floating-price convertible securities (Hillion and Vermaelen, 2004), can

resolve the unraveling problem because the manipulator does not have to buy back shares in the

open market. He can obtain as many conversion shares as he needs by short selling the price

downward just prior to the conversion notice date. The flawed structure of the floating-price

convertible’s contract may actually give security holders an incentive to manipulate the issuer’s

share price downward.

The rest of the paper is organized as follows. Section 2 describes the model and

characterizes the market equilibrium when there are no manipulators. Section 3 describes the

market equilibrium when manipulators can enter the market. I assess the impact of short sale

manipulation by comparing the two equilibriums. Section 4 explains how naked short selling can

destabilize the market for a stock. Section 5 shows how floating-price convertibles resolve the

unraveling problem, so that even trade-based short sale manipulation is profitable. Section 6

concludes.

2. The Market Model

This section characterizes the market equilibrium when there are no manipulators.

2.1 Institutional Details on Short Selling

8

A short sale is the sale of stock that the seller does not own.12 The seller borrows the

shares from a broker-dealer or an institutional investor. She establishes the short position by

selling the borrowed shares and closes it out by buying the stock at a later date and returning the

shares to the stock lender to extinguish the loan. Short sales increase the number of shares that

are beneficially owned by investors and hence the stock’s float.13 As a result, the total number of

shares beneficially owned and eligible to vote exceeds the number of shares the firm has

issued.14

Short sales are heavily regulated in the United States both because of the riskiness of the

strategy and also because of its potential for abuse as a manipulative device.15 In the United

States, many institutional investors are either prohibited by policy or regulation from short

selling or tightly restricted as to the size of the short positions they can maintain. Many brokerdealers

severely restrict short selling by their retail customers. However, the SEC has expressed

concern that enforcement of the restrictions on short selling, and especially naked short selling,

appears lax due to broker-dealers’ tolerance of extended fails to deliver (SEC, 2003b, Boni,

2004).

The regulation of short selling in the United States has evolved from the recognition that

unrestricted short selling could impair market efficiency by causing the price of a stock to spiral

downward (Dechow et al., 2001). Regulation constrains short selling in several ways. SEC Rule

9

10a-1 permits investors to sell short stocks listed on a national securities exchange only on either

a “plus tick” or a “zero plus tick” (SEC, 2003)16 The NASD has a similar bid test under NASD

Rule 3350 but it only applies to Nasdaq National Market (NNM) securities when the trades are

executed on either SuperMontage or over the NASD’s Alternative Display Facility (ADF). The

bid test does not apply to Nasdaq SmallCap, OTC Bulletin Board, or other over-the-counter

stocks or to NNM securities traded away from SuperMontage or ADF unless the market in which

they are traded has adopted its own price test. The short seller must place the proceeds from the

short sale in an escrow account, which collateralizes the stock loan. The short seller can not use

the short sales proceeds to hedge the short position. The short seller receives interest from the

stock lender at a below-market interest rate, called the rebate rate, with the difference between

the market rate and the rebate rate, the rebate spread, compensating the lender.17 Federal

Reserve Regulation T requires short sellers to post additional collateral in a margin account when

the stock is shorted. The initial margin requirement is 50% of the market value of the shorted

shares. The maintenance margin requirement is 25%.18 Broker-dealers often set higher margin

requirements, and large broker-dealers typically require at least 30% equity. The short seller has

to top up the escrow account if the price of the stock rises but can reduce it if the price of the

stock falls.

Current regulations prohibit naked short sales except under limited circumstances. New

York Stock Exchange (NYSE) Rule 440c and NYSE Information Memorandum 91-41 (1991)

require a short seller to make an affirmative determination that it will be able to borrow shares

10

before it can make a short sale unless the short seller is a market maker, specialist, or odd-lot

broker who is selling short in connection with its normal market-making responsibilities.

National Association of Securities Dealers (NASD) Rule 3370, NASD Rules of Fair Practice,

Article III, Section 1, and SEC Release No. 34-35207 (1995) impose a similar affirmative

determination requirement for NASDAQ stocks, and SEC Release No. 34-37773 (1996) imposes

a similar requirement for American Stock Exchange-listed stocks.

The SEC recently adopted Regulation SHO to curb abusive short selling (SEC, 2003b,

2004). Rule 203 under Regulation SHO, which became effective January 3, 2005, prohibits a

broker-dealer from accepting a short sale order unless it has arranged to borrow the security or

has reasonable grounds to believe that it will be able to borrow it before the settlement date. It

also requires the broker-dealer to enter into a bona-fide borrowing arrangement before executing

an order to short sell any equity security that has been identified as a ‘threshold security’. The

threshold list includes any equity security that is either exchange-traded or is issued by a public

reporting company for which aggregate fails to deliver at a registered clearing house amount to

(a) at least 10,000 shares which represent (b) at least one-half of one percent of the issuer’s

outstanding shares.19 It also requires the clearing house member or the clearing house to take

action to cure all fails to deliver threshold stocks that persist for 10 days after the normal

settlement date. The SEC proposed Regulation SHO out of concern that the existing rules

restricting naked shorting had not been effective in preventing abuses (SEC, 2003b). However,

the existing affirmative determination rules and the new rules under Regulation SHO except

short sales executed by specialists and market-makers engaged in bona-fide market-making

11

activities (SEC, 2003b, 2004), which provides a potential loophole.20 Boni (2004) finds that

naked short sales are pervasive in the U.S. stock market, which supports the SEC’s concern that

broker-dealers have not been diligent in enforcing the existing short sale restrictions.21

Borrowing shares is costly. In addition to the cost implicit in receiving a below-market

rebate rate, stock loan agreements typically require the borrower to reimburse the lender in full

for any dividends or other distributions the issuer makes to its stockholders, which imposes a real

cost (Frank and Jagannathan, 1998). Third, the Internal Revenue Code taxes all profits from

short sales at the short-term capital gains rate, regardless of the length of time the position is

open. Fourth, stock borrowers are exposed to the risk of a squeeze.22

Stock loan agreements usually provide that the loan must be repaid on demand. A short

squeeze can occur when the lender demands the return of the shares but the borrower can not

find a substitute lender and must therefore repurchase the shares in the open market. If the stock

is thinly traded, or if there are a relatively large number of short sellers trying to cover their short

positions, the resulting demand for shares can force the price higher and impose an added cost on

short sellers. A short seller can mitigate this risk by borrowing on a term basis. However, term

stock loans are unusual, and they are expensive (Geczy et al., 2002). Instead, market participants

may use strategic fails to deliver (i.e., naked shorting) when stock borrowing is costly or

impossible (Evans et al., 2003, Boni, 2004).

2.2 The Model

12

The model is a simplified depiction of an actual stock market that still is able to capture

the essence of manipulative short selling in actual stock markets. The model also gains

considerable clarity without losing generality by assuming a non-dividend-paying stock and a

zero interest rate. I assume that the intrinsic value of the stock to be revealed in the future can

have either of two possible values, high (H) or low (L). I also assume that aside from the initial

shareholders, stock market investors are of four types.23

First, there is an informed investor (subscripted I) who possesses information about the

firm that enables him to know what the value of the stock will be when it is revealed to the

market in the future. The informed investor could be a hedge fund or some other sophisticated

investor. Insiders are also informed but are prohibited from short selling by corporate

restrictions and the Securities Exchange Act of 1934.24 One could also think of the informed

investor as a professional short seller who has reliable information about the firm’s future

business prospects, which he gained through research (Diamond and Verrecchia, 1987). To

simplify the model, I assume a single informed investor.

Because of the risks and the cost involved, short sellers are likely to be better informed

than holders of long positions about the prospects for a stock (Diamond and Verrecchia, 1987).

A short sale is the most direct way for an investor to bet that a stock’s price will fall.25 Short

sellers expect the share price to fall sufficiently to compensate them for their costs and risks.

Asquith and Meulbroek (1996) furnish empirical evidence that supports Diamond and

Verrecchia (1987). They find a strong negative relation between the amount of short interest and

subsequent stock returns, during both the period the stocks are shorted and the following two

13

years. They also find that those stocks that are heavily shorted for more than one month have the

most negative returns.

Second, at times there is a manipulator (subscripted M), who I assume can also determine

the stock’s intrinsic value either through research or by observing the trading behavior of the

informed investor. To simplify the model, I assume a single manipulator. The manipulator takes

actions that are designed to drive down a stock’s price, hoping to profit from the lower future

price. The manipulator is capable of mimicking the informed investor, for example, by

duplicating his volume of short sales, so as to conceal his manipulative intent from active traders

and uninformed traders.

Manipulative strategies are of two general types. My model focuses on trade-based

manipulation (Allen and Gale, 1992). The manipulator sells shares to drive down the price and

hopes to profit by buying them back at lower prices in the future. Second, the manipulator could

also engage in information-based manipulation by spreading rumors (Allen and Gale, 1992),

engage in wash sales, or employ other manipulative devices without actually selling any shares

to drive the price down. Such behavior violates Rule 10b-5 under the Securities Exchange Act of

1934 but it probably accounts for a significant portion of stock manipulation. The two strategies

are complementary. By spreading false negative information after establishing the short position,

a manipulator can further depress a stock’s price and increase her profit. Reducing the price

further gives the manipulator greater opportunity to cover her short position without driving the

price up so much that it eliminates her profit. These non-trading devices could also be used to

resolve the unraveling problem. In my model, the existence of active traders and the variable

price feature of floating-price convertibles can both resolve the unraveling problem.

The manipulator can behave like an informed investor and as a manipulator at different

times. He could act like an informed investor by selling short in anticipation of the stock’s price

14

falling to L. He can also act like a manipulator by selling short to drive down the price and

covering his short position before the share price is revealed to be H. In addition, in Section 4, I

allow for the possibility that the manipulator can switch modes of behavior, at times borrowing

shares to make routine short sales and at other times intentionally effecting naked short sales by

failing to make delivery. Alternating between these two modes of behavior to exploit his

information asymmetry disguises the manipulator’s behavior and makes it more difficult for the

regulators to detect his misbehavior and for the other market participants to interpret the signals

in his trading decisions.

Third, there are N active traders (subscripted An , n = 1,….,N). Active traders, who may

include market makers, search for information about whether the firm’s stock price will be high

or low in the future.26 As part of their information gathering, they monitor the behavior of other

traders to look for value signals. They observe market price and trading volume but they do not

know the identities of buyers and sellers, which makes them incapable of distinguishing perfectly

between sales by a manipulator and an informed investor.27 They do not have complete

information about the firm. Instead, they infer information from prices, trading volumes, and the

trading behavior they observe in the market to decide whether they should buy the stock or sell

it. They interpret sales by an informed investor (or by a manipulator they mistake for an

informed investor) as a negative signal and sell shares the following period in response to the

negative signal.

Fourth, there is a continuum of uninformed (or noise) traders (subscripted U). They

initially have negligible holdings of the stock and behave like price takers. They do not

15

condition their purchases on any specific information but instead, stand ready to buy more shares

at lower prices, which provides liquidity to sellers. The uninformed traders’ willingness to hold

Q shares at time t is summarized in the following demand curve:

P is the market price of the stock at time t, and A and B are constants. The demand curve for the

stock is downward-sloping (Shleifer, 1986, Kaul, Mehrotra, and Morck, 2000, and Liu, 2000).

At time 0, the firm’s shares are held by insiders and passive investors who view their

shareholdings as long-term investments. A portion of the firm’s shares are held in margin

accounts with broker-dealers where they are available for lending to short sellers.28 If no one

wishes to sell the stock, then its price is A. The total number of shares outstanding is (A – L)/B.

If the time zero shareholders wish to sell all the outstanding shares to uninformed traders, then

the price would fall to L.

Share transactions occur in the market in the following sequence. At time 1, either the

informed investor or the manipulator can initiate a short sale. Since neither the informed investor

nor the manipulator owns any shares, each must borrow them. I relax this assumption later when

I consider the possibility of naked short sales. The informed investor sells shares if and only if

the future stock price will be L. The probability that the future stock price will be L is p (and the

probability that it will be H is 1 – p). One can think of A, the current market price, as the

expected present value of the share price at time 3:

A = pL + (1− p)H (2)

16

The manipulator observes the informed investor’s trading. She will not sell the stock

short if the informed investor does, and she may decide not to enter the market even if the

informed investor is not selling.29 The manipulator sells shares with probability q < 1 – p.30 There

is a probability 1 – p – q that neither the informed investor nor the manipulator will engage in

short selling.

Active traders observe the stock price and trading volume at time 1. They sell shares at

time 2 based on what they learn at time 1 conditioning their decision to sell on whether they

observe an informed investor (or the manipulator whom she mistakes for the informed investor)

selling.31 The manipulator or the informed investor can buy or sell shares at time 2. The

uninformed traders stand ready to buy shares at time 1 and also at time 2. The stock’s value is

revealed to be H or L per share at time 3.

The informed investor or the manipulator can sustain a short position until time 3 but it is

less expensive to sustain it to time 2 (unless the manipulator naked shorts). One might think of

this assumption in any of three ways. First, the rebate spread represents a direct cost of carrying

the short position. This cost can exceed the market rate of interest when the stock is on special

and extremely hard to borrow (D’Avolio, 2002, Duffie, Garleanu, and Pedersen, 2002, Geczy,

Musto, and Reed, 2002). Second, time 3 represents the long run, and it may be very costly for the

informed investor or the manipulator to borrow the shares to maintain the short position, for

example, because she is unable to borrow the stock continuously over an extended period.32

17

Third, while there is no uncertainty in my model, I could motivate a cost to maintaining the short

position that risk-averse investors face by making the distribution of time 3 prices uncertain.

Instead, I model the cost of holding the short position until time 2 as a scalar C per share and to

time 3 as 2C per share. D’Avolio (2002) finds that the overall value-weighted cost to borrow

stocks is 25 bp per year; 91% of the stocks (“general collateral” stocks) cost less than 1% per

year to borrow with a mean-weighted fee of only 17 bp; but the other 9% (“special” stocks) have

a mean fee of 4.3% per year; and less than 1% (“extremely special” stocks) have negative rebate

rates as high as 50%. If the stock price at time 3 is L, then the informed investor’s cost of

shorting a share until time 3 is L + 2C. Unless A – L – 2C > 0, the informed investor would

never sell shares at a price less than or equal to the time 0 price and maintain the short position

until time 3. To simplify the model, I also assume that active traders incur at most a negligible

cost to holding a short position.33

2.3 Market Equilibrium

I investigate the impact of short sale manipulation on stock market equilibrium by

comparing two market settings. In the first, there is an informed investor and active traders but

no manipulator. Both can sell shares short. They sell short when they expect the equilibrium

price of the shares to drop to L at time 3. In the next section, I permit a manipulative short seller

to enter the market and examine how her trading alters the market equilibrium. Unlike legitimate

short sellers, the manipulators sell short in the hope that their selling drives the share price below

the shares’ intrinsic value and attracts other sellers from whom they can buy shares after the

price drop to cover their short positions.

18

The informed investor might sell (1) I Q shares short at time 1 that he plans to repurchase

at time 3, an additional (1)

further (2) I Q shares short at time 2, which he would repurchase at time 3.34 I show that when

shorting is expensive, the optimal strategy for the informed investor is to sell shares at time 1 but

neither to buy nor to sell shares at time 2. When shorting is inexpensive, the informed investor

will sell shares short in both periods. Initially, I assume that there are N symmetric active traders

but no manipulator. Each active trader sells ) 2 ( i

time 2 if she observes what she believes to be the informed investor selling at time 1.35 There are

no limits on the number of shares short sellers can borrow.36

The active traders believe that the informed investor has negative information about the

firm’s prospects when they have observed him selling at time 1. Each active trader realizes that

she is competing against N – 1 other active traders to sell her shares. The aggregate number of

shares the active traders offer for sale is:

Q (2) Q (2)

= (3)

(4)

subject to . 0 ) 2 ( ≥ i

subject to (1) ≥ 0 I Q and ˆ (1) ≥ 0. I Q Applying the Kuhn-Tucker conditions, equation (7) has the

following solutions. Either (1) = 0 I Q or

ˆ (1)

2 2

2 1

2

(1) 2 I I Q

Either ˆ (1) = 0 I Q or

(1)

2

(1) (2)

(1) ≥ 0 I Q provided C ≤ (3N + 3)(A − L) /(2N 2 + 5N + 5) , and (1) 0

The informed investor’s strategy at time 2 must be optimal given the N active traders’

demand for shares at that time. The informed investor solves the problem:

max ( [ (1) (2) (2)]) (2) ( ) (2) (2) (10)

20

subject to (2) ≥ 0. I Q The solution to equation (10) is (2) = 0 I Q or

( 2)

(2) (1) ( 1)

(2) ≥ 0 I Q provided C ≤ (A − L) /(2N).

2.4 Equilibrium When Selling Short Is Expensive

When the informed investor’s cost of shorting shares is high enough and the number of

active traders is large enough that C ≥ (A − L) /(2N), then (1) = 0 I Q , (2) = 0, I Q and (1) 0

The informed investor only sells shares short at time 1 and repurchases at time 2 all the shares he

shorted at time 1. Each active trader sells short

B(N 1)

Q* (2) A L

Table 1 shows how the market equilibrium depends on the cost of shorting and the number of

active traders.

As the number of active traders becomes large, the aggregate short position converges to

all the outstanding shares, and P*(2) converges to the shares’ intrinsic value:

21

lim P* (2) L

Competition among active traders promotes market efficiency. However, if there is only a small

number of active traders, competition is limited, and each will try to extract a per-share rent

equal to

The informed investor sells

2 ( 1)

( ) ( 1)

2

(1) (2)

shares at time 1 at a market price of

2

( )

2 2

2

1 2 2

The informed investor will not find it profitable to sell shares at time 2. If he were going

to sell additional shares, he would be better off selling them at time 1 because P* (1) > P* (2) .

The informed investor also will not buy any shares at time 2 beyond what would be required to

cover his short position because he would lose P* (2) − L on each net share he purchased at time

2 and held to time 3.38 He will not sell any shares at time 2 because he would lose L + C − P* (2)

on each share he sold short at time 2 and held to time 3. He will not hold his short position to

22

time 3 because the cost of holding it and closing it out at time 3 is L + 2C. Since

in that case his profit would only be:

(1) (1) ( 2 ) (1)

[ ( 1) ][ ( ) ( 1) ]

4 ( 1)

[ ( ) ( 1) ]

+

Finally, each active trader’s strategy is optimal given all the other active traders’ strategies and

the informed investor’s strategy. Thus, no active trader can deviate profitably.

2.5 Equilibrium When Selling Short Is Inexpensive

When the informed investor’s cost of maintaining the short position is low enough and

the number of active traders is small enough that C ≤ (3N + 3)(A − L) /(2N 2 + 5N + 5), then

(1) ≥ 0 I Q , (2) ≥ 0 I Q , and (1) 0.

2 2 1

(2) 4 * (24)

provided N > 1. But the total number of shares shorted at time 2 is greater, and as a result, P*(2)

is lower than in the high-shorting-cost case:

23

2( 2) 1

provided N > 1.

P*(1) is also lower, and therefore, closer to the shares’ intrinsic value, because

2 1 2 2

Thus, in both cases, competition among active traders promotes market efficiency.

2.6 Timing of Short Covering

The informed investor will hold the short position until time 3, rather than cover it at time

2, provided

2( 1)

which is satisfied when C < (A − L) /(2N) . So long as C is small or N is small, the informed

investor finds it more profitable to cover the short position at time 3. He also sells short more

shares at time 2 and covers those short sales at time 3. But as the number of active traders grows,

eventually the sign in equation (29) reverses. The informed investor stops selling shares short at

24

time 2, and he repurchases some at time 2 and the rest at time 3. When N grows large enough

that C > (A − L) /(2N), the informed investor only sells shares short at time 1 and covers the

entire short position at time 2.

Active traders have two opposing effects on the informed investor’s profit. First, they sell

shares at time 2, which reduces P*(2) and the informed investor’s information rent from short

selling, P*(2) – L. The lower P*(2) allows the informed investors to repurchase shares more

cheaply at time 2 in the expensive-shorting case (IV). As a result, they sell more shares ˆ * (1)

Increasing the number of active traders in the expensive-shorting case increases *

other hand, the active traders compete with the informed investor to sell shares short at time 2

when short selling is inexpensive enough (and the number of active traders is small enough) that

the informed investor wants to sell shares short at time 2 (case II). Greater competition reduces

the informed investor’s information rent. This reduces (2) I Q and the profitability of the

informed investor’s short selling in the low-shorting-cost case (II), since *

case depends on N:

If the number of active traders becomes large enough – and the competition becomes

sufficiently intense – the informed investor’s profit-maximizing strategy shifts from selling

shares to buying them back at time 2. Short selling at time 2 becomes less profitable as N

increases and P*(2) falls. Competition from more active traders eventually makes it unprofitable

to sell short at time 2. He buys rather than sells at time 2. Further increases in the number of

active traders raise ˆ (1) I Q and increase the informed investor’s profit. This equilibrium

25

corresponds to the high-shorting-cost case. The change in strategy in response to the increase in

the number of active traders makes the informed investor worse off because even though he only

incurs one period’s shorting cost, he must pay P*(2) > L to repurchase the shares. His profit is

greater in the low-shorting-cost case because *

2.7 Effect of Short Sale Restrictions

Suppose the number of shares available for borrowing is capped at H. Then

As a result, P*(2) in equation (6) includes a shadow price for short sales λ . The time 2 market

price in equations (17) and (28) converges to L + λ . The amount of short sales at time 2 in

equations (16) and (27) converges to H < (A – L)/B. The borrowing restriction reduces market

efficiency by preventing short sellers from arbitraging away the mispricing (Dechow, Hutton,

Meulbroek, and Sloan, 2001, D’Avolio, 2002, and Geczy, Musto, and Reed, 2002).

The market equilibrium in the simplified market structure exhibits the behavioral

properties one would expect in a market that is free of manipulation.42 Figure 1 illustrates the

sensitivity of market prices to the cost of shorting and to the number of active traders, and

Figure 2 illustrates the sensitivity of *

3. Market Equilibrium When Manipulators Are Present in the Market

Next, I consider how a manipulator entering the market affects the market equilibrium. If

the informed investor is shorting shares optimally and the manipulator has the same cost of

1

(1 )

1

(2) * β β

(35)

27

Consequently, the market price at time 2 is higher due to manipulation:

(2)

1 1

+

The adverse impact of the manipulation on the active traders’ profits increases with the relative

likelihood of manipulation (β ).

If either the informed investor or the manipulator sells shares short, then each sells

2 ( 1)

ˆ * (1) ˆ * (1) [ (1 ) ] ( 1)

(38)

shares at a price of

2( 1) 2

( 2)( ) ( )

2( 1)

(39)

and buys them all back at time 2 at price ) 2 ( *

(β ) that the market may be manipulated. The informed investor or the manipulator earns

expected profit equal to

The manipulator’s profit is inversely related to the likelihood β the active traders attach to the

possibility of manipulation, and thus, to how well the manipulators disguise their activity. But so

28

long as 0 > β , *

the manipulator) earns lower expected profit from short selling when the market can be

manipulated than the informed investor earns from short selling when the market is free of

manipulation.

For the pooling equilibrium to be sustainable, the informed investor must not have an

incentive to deviate from this strategy to separate himself from the manipulator. Selling a

different number of shares at time 1 but still buying them back at time 2 will not disrupt the

pooling equilibrium because it is costless for the manipulator to mimic this strategy. In addition,

there is no credible way for the informed investor to commit to staying short through time 3

because the active traders only observe the quantity sold and the price at time 1.45 Thus, the

pooling equilibrium will be sustained so long as the informed investor finds it more profitable to

buy back shares at time 2 rather than at time 3.

The cost to the informed investor of staying short until time 3 is L + 2C. So the incentive

compatibility condition is satisfied when it is cheaper to buy back the shares at time 2:

1

( )

(42)

or

( )

( 1)

The incentive compatibility condition is satisfied when the number of active traders is

sufficiently large, the cost of shorting the stock is sufficiently high, and the relative likelihood of

manipulation β is sufficiently small.

29

The greater the cost of staying short until time 3, the greater the likelihood the informed

investor will cover his short position at time 2, and the easier it is for the manipulator to pool

with the informed investor. Second, the greater the likelihood that the seller of shares at time 1 is

a manipulator, the more severe is the adverse selection problem facing the active traders. They

respond by selling fewer shares at time 2, which causes the price to be higher than it otherwise

would and makes it less likely that the manipulator will be able to pool with the informed

investor. Since β is inversely related to the probability the seller is an informed investor, it is

easier for the manipulator to sustain the pooling equilibrium when the active traders believe it is

more likely that the seller is an informed investor. Third, the right-hand side of inequality (43) is

decreasing in H – L. The greater the dispersion of future share prices, the lower the likelihood of

a pooling equilibrium. The greater the price dispersion, the more profitable it is for the informed

investor to wait until time 3 to cover his short position.

Fourth, an increase in the number of active traders raises the likelihood of a pooling

equilibrium because the right-hand side of inequality (43) is increasing in N. Increasing the

number of active traders reduces the cost of covering the short positon at time 2 and makes it

more likely that the incentive compatibility condition for a pooling equilibrium is satisfied.

However, market efficiency suffers because less information concerning the market

manipulation is revealed. This effect suggests an important role for government regulation. In the

absence of manipulation, an increase in the number of active traders would improve market

efficiency by driving P*(2) closer to the stock’s true value. This effect is less pronounced when

manipulators are present in the market. Inequality (43) suggests that decreasing the conditional

probability β that a manipulator is present increases the likelihood that the manipulation will be

concealed by a pooling equilibrium. However, equation (35) shows that reducing β improves

market efficiency by driving ) 2 ( *

30

regulatory enforcement of the rules barring manipulation can improve market efficiency by

reducing the likelihood that manipulators are present in the market. But it may also increase the

likelihood that if manipulation occurs, it will be concealed by a pooling equilibrium.

3.2 Separating Equilibrium Free of Manipulation

A separating equilibrium can occur in cases I, II or III in Table 1. The manipulator would

still want to cover his short position at time 2. First I consider case II. The informed investor sells

shares short at time 1 and again at time 2 but waits until time 3 to cover. The manipulator will

not find it profitable to sell short.

The active traders would sell

4

2 2

4 ( ) 4

2

+

(45)

The manipulator would suffer a loss if he mimicked the informed investor by selling shares short

at ) 1 ( * P and ) 2 ( *

cover his time 1 short position at time 2 (buying rather than selling), the active traders would be

alerted to the manipulation, the market price would adjust upward, and the manipulator would be

precluded from earning a profit. The manipulator can not profitably mimic the informed

investor’s strategy if he only enters the market when the informed investor does not. But if he

enters and so does the informed investor, then his (incremental to the market) short sales are

unprofitable. Thus, a separating equilibrium occurs when the cost of shorting is sufficiently small

and the number of active traders is sufficiently small.

31

A separating equilibrium can also occur in case III. The manipulator would have to sell

(1) ˆ (1) I I Q +Q shares at time 1 to mimic the informed investor, and he would have to repurchase

ˆ (1) I Q shares at time 2 and the rest at time 3 to avoid detection. However, while he would make a

profit on the shares he repurchases at time 2, he would suffer an even greater loss on those he

repurchases at time 3. A sustainable equilibrium occurs only if the informed investor is the sole

short seller in case III.46

Manipulative short selling can not occur in a separating equilibrium. Two conditions

must be satisfied. First, the informed investor must be willing to wait until time 3 to cover her

short position. If she is patient enough, then a potential manipulator will not be able to mimic her

strategy profitably. This condition requires a relatively small cost of shorting. Second, if the

number of active traders is small, then the informed investor’s best strategy is to hold the short

position until time 3.

3.3 Role of Active Traders

Active traders affect the market in opposite ways. If the number of active traders is

small, increasing their number provides the usual benefit of arbitrage by incorporating the

information embodied in the informed investor’s sell signal into the market price to improve

market efficiency. However, as the number of active traders becomes large, their presence

eventually has the opposite effect. A pooling equilibrium can occur. Increasing the number of

active traders depresses P*(2) to such an extent that the informed investor prefers to repurchase

shares at time 2, rather than wait until time 3 to buy them. The manipulator is able to mimic the

informed investor’s strategy. As a result, P* (2) deviates farther from the shares’ intrinsic value

32

than in the manipulation-free case because the active traders do not know whether the short seller

at time 1 is an informed investor or a manipulator. Interestingly, increasing the number of active

traders actually increases the likelihood of manipulation and impairs market efficiency because

the informed investor is less willing to wait until time 3 to cover her short position. As a result,

the manipulator can more easily camouflage his true intent.

An important implication of the separating equilibrium is that manipulation is less likely

to affect stocks for which there is a large pool of shares available for lending because the cost of

shorting is lower and a separating equilibrium is more likely.47 Manipulation is more likely when

the informed investor has a high cost of shorting (for example, when the stock is on brokerdealers’

‘hard-to-borrow’ lists) but the manipulator has a much lower cost, for example, zero cost

through strategic fails to deliver.

The manipulator’s inability to sell short profitably when borrowing shares is expensive

would seem to suggest that if naked shorting were not permitted, then manipulative short selling

would be less likely to affect stocks that are difficult (or impossible) to borrow, for example,

because there is only a small public float or a large portion of the public float is in the hands of

institutions or individuals who hold their shares in cash accounts and refuse to lend. Naked

shorting avoids this constraint because it enables the manipulator to short even hard-to-borrow

stocks.

4. Naked Short Selling and Strategic Fails to Deliver

The SEC recently adopted Regulation SHO “to address the problem of ‘naked’ short

selling” (SEC, 2003, p. 1; 2004). Naked short selling involves entering into a transaction to sell

33

shares that the seller does not own and has not arranged to borrow to deliver to the buyer. A

naked short sale may initially appear to the clearing house as a routine fail to deliver (on the

settlement date). The naked short sale becomes apparent when the seller fails to deliver for an

extended period.48 Miller (1977) shows that the marginal investor is an optimist when short

selling is constrained and investors’ opinions on the stock diverge. Naked short selling removes

the constraint on short selling and results in a pessimist/manipulator becoming the marginal

investor. Naked short selling can be especially destabilizing to a company’s share price when

unrestrained because ignoring the regulatory requirement to borrow the shares eliminates the

main quantitative constraint on the amount of short selling and intensifies the resulting

downward pressure on price. There have been instances where the short position in a stock has

exceeded the firm’s entire supply of outstanding shares.49

Evans, Geczy, Musto, and Reed (2003) introduce the concept of strategic failures to

deliver (or more simply, strategic fails), which occur when short sellers decide not to borrow

shares and deliver them because borrowing the shares is too expensive or too difficult. They

show that options market-makers use strategic fails to get around short selling constraints

affecting stocks with listed options. Boni (2004) documents the prevalence of strategic fails –

naked short sales — across the entire spectrum of U.S. stocks, including stocks that do not have

options listed, and provides evidence that market-makers strategically fail to deliver shares

whose borrowing costs are high. Manipulative short sellers have an incentive to use strategic

34

fails because they avoid having to pay the rebate spread. Evans et al. (2003) also provide

evidence that broker-dealers seldom request buy-ins, which reduces the risk that a stock loan

might be called prematurely and leave the borrower unable to arrange a replacement loan.50

Naked short selling and manipulating the price downward provide cash returns to the

manipulator, who can withdraw cash from his clearing firm account as the shorted shares are

marked to market at progressively lower prices.51 Through naked shorting, the manipulator

realizes these returns without investing any cash (provided the market price never rises above the

sale price).

4.1 The Role of the Clearing House

Naked short selling could not occur, or at least not persist, if the stock purchaser or the

clearing house insisted on taking delivery of the shares. Most common stock transactions in the

United States clear through the National Securities Clearing Corporation (NSCC). The NSCC is

a subsidiary of the Depository Trust and Clearing Corporation (DTCC). Another subsidiary of

DTCC, the Depository Trust Company (DTC), is the world’s largest securities depository and

serves as the clearing house for most trades of registered shares in the United States.52 DTC was

formed about 30 years ago to eliminate the need for physical delivery of securities to settle

trades. DTC retains physical custody of stock certificates on behalf of its members, which

include all the major broker-dealers. Stock certificates for registered securities are deposited with

the DTC and are held in the name of Cede & Co., DTC’s nominee name. DTC records the

35

transfer of securities by book entry; electronically it debits the seller’s DTC account and credits

the buyer’s DTC account. No physical transfer ever occurs.

The NSCC was created in 1976 through the merger of three major clearing corporations

(NYSE, AMEX, and NASD). NSCC works in conjunction with the DTC to provide centralized

clearance and settlement for broker-to-broker stock trades in the United States. The NSCC clears

and settles transactions through the Continuous Net Settlement (CNS) system. It guarantees

completion of the transactions by assuming (a) the obligation of the buyers to pay for the shares

upon delivery and (b) the obligation of the sellers to deliver the shares. During the trading day,

the CNS continually nets all trades by its members in each security. The member’s previous

trading day’s closing net long or short position is continually updated with the day’s purchases

and sales. At the end of the trading day, the member’s updated net long or short position in each

stock is communicated to the DTC for overnight processing.

Each short position is compared to the member’s DTC account to determine if the

member has enough shares on deposit to settle the short position. If so, then the DTC transfers

the required number of shares from the member’s DTC account to the NSCC’s DTC account.

Based on instructions from the NSCC, the DTC transfers shares received from members with

short positions to the accounts of members with long positions. If the member with a short

position does not have enough shares in its account to cover the short position, then the NSCC

has five choices. It can wait another day to see whether the seller cures the fail by delivering the

shares. Second, if it determines that the open short position is a high-priority obligation, it can

attempt to arrange to borrow enough shares through its stock borrowing program to satisfy the

open position (NSCC, 2003). If it is unable to borrow the shares, then the DTC has the three

remaining choices: (a) it can demand a dealer buy-in (forcing the selling broker-dealer to buy the

shares in the open market and deliver them to the DTC), (b) buy the shares itself in the open

36

market and charge the cost of the buy-in to the account of the seller, or (c) as a last resort,

demand that the seller break the trade and compensate the buyer for the associated cost.

The NSCC’s stock borrow program permits it to borrow shares from participating

members to cover end-of-day open short positions that it deems to be of high priority. Addendum

C-1 of the Rules and Procedures of the NSCC (2003) governs the operation of the stock borrow

program. Members who wish to participate in the program inform the NSCC each day of the

number of shares of each stock in their general unpledged account at the DTC which they are

willing to lend. After the NSCC determines the number of shares it would like to borrow to

satisfy all high-priority open positions, it applies a formula to determine from whom it will

borrow the shares. The formula favors members who have the lowest stock loans from the NSCC

and who pay the most clearing fees to the NSCC. When it borrows shares, the NSCC debits the

lending member’s DTC account but also credits that member with a long position in a special

CNS sub-account set up specifically for the stock borrow program. The sub-account holds what

is tantamount to an undated stock futures contract with the NSCC as the obligor. The NSCC also

credits the lending member’s regular CNS account with funds equal to the market value of the

borrowed shares, which the lending member may invest overnight in an interest-bearing account.

The DTC credits the borrowed shares to the NSCC’s DTC account, which eliminates its short

position, and transfers them to the buyer’s DTC account. The buyer acquires all right, title, and

interest in the borrowed shares – just as it would in any cash transaction that settles the regular

way – including the right to vote the shares, receive dividends, resell them, or lend them (e.g.,

back to the NSCC through the stock borrow program). The NSCC charges a fee to each member

with a short position that triggered the NSCC’s need to use the stock borrow program. The

NSCC returns the borrowed shares when it receives deliveries against outstanding short positions

that exceed the amount of shares it needs to satisfy high-priority open short positions.

37

The stock borrow program can facilitate naked shorting in two ways. First, sellers can

continue to fail to deliver because the NSCC can borrow the shares it needs to meet its clearing

obligations through the stock borrow program. It does not have to force the seller who fails to

deliver to buy in shares, nor does it have to go into the market to buy in the shares. It simply

borrows them from another member firm to effect the buy-in. Since the NSCC covers the short

position, the buyer of the stock also never has to buy them in.53 Second, the stock borrow

program allows the shares to be recycled. Each stock loan gives rise to another stock futures

contract. Any single share could actually be relent multiple times, giving rise to multiple futures

contracts. Each futures contract credited to a broker-dealer’s sub-account at the DTC continues

to be reported on the broker-dealer’s books as a share held either in its proprietary account or in a

customer account. In either case, the account holder believes he owns a real share with all the

rights attached to it. Consequently, the stock borrow program effectively creates additional

unauthorized shares of the issuer’s stock. These undated stock futures contracts, which the

financial press has referred to as phantom shares, inflate the amount of stock that is available for

trading and also increase the amount of stock that is available for lending to short sellers (SEC,

2003b).54

4.2 Effect of Strategic Fails to Deliver

Naked shorting allows the manipulator to sell short profitably when borrowing shares

would be expensive, for example, because of a small public float. It also enables the manipulator

to conceal his true intent because he can mimic a market maker and need not borrow any shares.

38

The manipulator can achieve a pooling equilibrium in all four cases in Table 1. The

manipulator sells shares short but she (or her clearing broker) does not arrange to borrow them.

Her broker fails to deliver them to its clearing firm, who fails to deliver shares to the NSCC on

the trade settlement date. Her side of the trade never settles with the NSCC, which records a fail

to deliver in the clearing firm’s account.55 The NSCC can mitigate the effect of this delivery

failure through its stock borrow program, which credits the buyer’s clearing broker with the

number of shares its customer purchased. The manipulator does not have to post collateral at the

below-market rebate rate as he would if he had borrowed the shares, and he avoids the cost of

searching for shares to borrow. However, the clearing house holds the cash proceeds from the

sale of the shares. The manipulator’s direct cost of shorting is zero. However, in order to effect

the naked short sale, the manipulator needs the clearing broker’s cooperation to maintain the

naked short position for any significant length of time, for which the clearing broker will

undoubtedly require some form of compensation. To simplify the problem, I ignore these

indirect costs and assume C = 0 for the manipulator.56

First I consider the high-shorting-cost case (IV in Table 1). With a zero cost of shorting

through strategic fails, the manipulator can profitably sell short at time 1 if P*(3) will be L even

if the informed investor does not reduce his short sales.57 But the manipulator must conceal his

39

short sales so that the active traders are not alerted. If β ≥ 1 − p , then the manipulator will not be

able to cover his short sales at time 2 because the active traders will exit the market. Naked

shorting abets this concealment enabling the manipulator to sell short

3 ( 1)

( )[1 ] ( 1)

3 ( 1)

ˆ * (1) [ (1 ) ] ( 1)

(47)

shares at time 1, which is fewer shares than the manipulator sells short. The manipulator can

profitably sell ˆ * (1) ˆ * (1)

does not sell short in that case, which achieves a pooling equilibrium. Naked shorting conceals

the increase in the volume of shorting because fewer shares are borrowed. The active traders

would still sell * (2)

manipulated price. P*(1) is lower as a result of the greater volume of short sales when there is

naked shorting, and the lower cost of naked shorting and greater volume of shorting increase the

manipulator’s profit. Naked shorting drives the market price further below the stock’s intrinsic

value, and the difference is greater the lower is the perceived risk of manipulation.

) 1 ( ˆ*

naked shorting sufficiently so as not to drive the active traders from the market (1− p > β ) .58 An

increase in the number of active traders reduces ) 2 ( *

manipulative naked short selling. But if the active traders’ perception of the risk of manipulation

40

exceeds 1 − p , for example, because they detect the naked short selling, then the active traders

exit the market. Their departure removes the source of share sales that enables the informed

investor and the manipulator to cover their short sales at time 2. As a result, the informed

investor also exits the market. The manipulator could bid for shares from the uninformed

investors, but that would presumably raise the share price above A and make manipulation

unprofitable. The manipulator must disguise its trading, for example, by mimicking a market

maker, to prevent the scheme from unraveling.

) 1 ( ˆ*

related to H – L when 1 − p > β . The manipulator’s short sales increase (decrease) with the

potential profit from manipulation (proxied by H – L) when the likelihood that the future stock

price will be H is greater (less) than the likelihood that the manipulator will short the stock (the

risk of manipulation). The stocks most likely to be affected by naked shorting are the riskier,

small cap stocks that trade in the over-the-counter market. They have the greatest uncertainty

about their true value (greater H – L), and the NASD’s bid test restriction on short sales does not

apply to Nasdaq SmallCap, OTCBB (over-the-counter bulletin board), and Pink Sheet stocks

(SEC, 2003b, page 17), thus making it easier for a manipulator to enter the market (permitting

greater q).

Is it possible for the manipulator to drive the informed investor out of the market? The

greater volume of short sales could alert active traders to the greater risk that the market is

manipulated. This greater perceived risk results in β ‘ > β . The manipulator drives the informed

investor from the market when the numerator in equation (46) is positive and the numerator in

equation (47) is negative, that is, when

( ) ( )

2 2 ‘

41

If β ‘ is so much greater than β that the numerator in equation (46) becomes negative, neither

the manipulator nor the informed investor will be able to sell shares short profitably. The active

traders are so concerned about the risk of manipulation in that case that they will not accept a

price P* (2) that would make short sales profitable at time 1. If they do not sell short at time 2

spread negative news in both cases. As a result, the manipulator at times acts like an informed

investor and at other times like a manipulator. It is difficult to discern his true motivation, for

example, when investigating the possibility of market manipulation, without knowing the true

intrinsic value of the shares. However, the manipulator will be more likely to engage in naked

shorting when the future price will be L and the cost of shorting is high because incremental

short sales of borrowed shares are unprofitable in that case. Naked shorting will be more

prevalent as a fraction of total shorting the weaker the financial condition of the target firm.

Market makers can legally sell short more cheaply than other market participants,

including naked shorting, provided it is in connection with bona-fide market-making (SEC,

42

2003b, 2004). They can conceal the true intent of their trading more easily than non-marketmakers

because of the market-maker exceptions to the short sale restrictions and because short

selling by market makers is naturally greater for declining stocks. However, market makers

usually like to end each day flat to avoid the risk of carrying overnight positions (Schwartz,

1991). Thus, unusually large or unusually lengthy fails to deliver in a stock are more consistent

with manipulation than normal market-making.60 Controlling naked shorting requires the

regulators to enforce the short sale rules to ensure that manipulators do not register as market

makers to exploit these exceptions.61

In the lower-shorting-cost cases (I – III), the manipulator can profitably short incremental

shares at time 1 and time 2 when P*(3) will be L because the cost of naked shorting is zero. A

pooling equilibrium can occur in which the behavior of the manipulator is indistinguishable from

the informed investor’s. The greater combined short sales by the informed investor and the

manipulator at time 2 reduce P*(2), which causes the active traders to reduce their short sales. If

the active traders perceive a greater likelihood of manipulation, they reduce their short sales.

P*(2) is higher, and as a result, the informed investor and the manipulator increase their short

sales at time 2.

4.3 Aggressive Naked Short Selling and Extended Fails to Deliver

Aggressive short selling is a bearish signal. Desai et al. (2002) find that a high level of

short interest sends a strong negative signal because heavily shorted stocks experience significant

negative abnormal returns during the period they are heavily shorted and have a higher

43

probability of delisting relative to the size and industry-matched control firms. Naked shorting

intensifies these effects.

The manipulator will not sell short at time 2 in cases I-III if P*(3) will be H unless he can

also manipulate the time 3 price. Recall that in the absence of manipulation, only a separating

equilibrium is possible in case II. Naked shorting alters this situation. A manipulator can enter

the market when the informed investor does not, mimic the informed investor at time 1 and time

2, and increase his profit by continuing to naked short the stock until its price is close to zero at

time 3 when the price would otherwise be H. A similar result applies in case III. With such

aggressive naked shorting, the manipulator no longer needs to rely on active traders because he

does not have to cover his short position. In fact, he can earn greater profit by driving them from

the market to eliminate their competition for short sales at time 2.

The informed investor will not sell short when the intrinsic value is H. The manipulator

can achieve a pooling equilibrium in case II by short selling Q (1) Q (1) M I = shares at time 1 and

Q (2) Q (2) M I = shares at time 2 when the intrinsic value is H to mimic the informed investor.

The manipulator can conceal his manipulation in a pooling equilibrium.

The active traders sell short * (2)

will be ) 2 ( *

drive down the price. Due to the concealment that naked shorting affords, the other market

participants might misinterpret a sharp drop in share price, even to pennies a share, as the result

of informed investors selling the shares of a firm whose profitability and business prospects have

deteriorated, rather than manipulation. When information is revealed that suggests that the

intrinsic value is H, the uninformed traders’ demand curve at that time is H − BQ since A = H

44

when p = 0.62 If the manipulator covers his short position, the price rises to H, and he suffers a

loss. To avoid the unraveling problem, the manipulator can depress P*(3) by extending existing

fails to deliver and naked shorting an additional / ( (1) (2)) I I H B − Q + Q shares at time 3.63 The

manipulator’s profit is

P*(1)Q (1) P*(2)Q (2) P*(3)[Q (1) Q (2)] M M M M M π = + − +

)

2B(N 2)

(L C)(A L 2N (H L) 2NC

4B(N 2)

(A L 2N (H L) 2NC)

4B

A (L 2C)

(49)

when P*(3) = 0. The manipulator’s incentive is to drive the firm’s share price as close to zero as

possible. If he only does so when the future price will be H, his trading never interferes with the

informed investor’s. He can maintain this short position beyond time 3 either by extending the

fail to deliver or by rolling over the naked short position (by repurchasing the naked shorted

shares and simultaneously naked shorting the same number of shares to a different dealer). In

that case, the Equity Trade Journal for the stock will report daily trading volume but the NSCC

Continuous Net Settlement Report will reveal large open short positions and significant

persistent net fails to deliver but the DTC Weekly Position Report may indicate little, if any,

daily changes in the net positions of the shorting dealer(s) at the DTC.64

45

Building a short position of H/B to drive P*(3) to zero would involve naked shorting

more shares than the firm has outstanding because H/B > (A – L)/B.65 The manipulator can not

drive the share price close to zero unless he can naked short an extraordinary number of shares.66

This form of manipulation would result in a precipitous drop in the firm’s share price to well

below its intrinsic value, unusually heavy trading volume, and unusually large and persistent

fails to deliver at the NSCC. Preventing this activity requires the clearing house to enforce its

buy-in rules for fails to deliver and to impose penalties on short positions that are rolled over for

an extended period, which is the purpose behind new Regulation SHO (SEC, 2004).

A different pooling equilibrium is also possible with more aggressive naked shorting that

takes place when the intrinsic value of the stock at time 3 would be L. In this case, the

manipulator will compete with the informed investor by selling short (1) M Q shares at time 1 and

(2) M Q shares at time 2. The informed investor reduces his short sales, but the overall volume of

short sales is greater because of their combined shorting. The manipulator sells short

(1) (1) I M Q + Q shares at time 1 and (2) (2) I M Q + Q shares at time 2 if the time 3 intrinsic value

is H. He can drive P*(3) close to zero by increasing his naked short position to L/B.67 The

manipulator’s profit depends on his ability to manipulate the firm’s stock price and to keep it

depressed. The stronger the financial condition of the firm at time 3 (the higher is L), the greater

the number of shares the manipulator has to sell short at time 3 to drive the price close to zero.

46

The manipulator earns greater total profit in this alternate pooling equilibrium because he

can profitably manipulate the market even when the future price will be L and also because he

can substitute his own short sales when the informed investor cuts back. The firm’s share price is

close to zero at time 3 regardless of its intrinsic value. The volume of manipulative short selling

is greater due to the manipulator’s heavier short sales. The manipulator’s potential profit is

greater, but so is the risk of detection because of the greater naked short sales volume, the larger

fails to deliver at the clearing house, and the adverse reaction of the informed investor when the

manipulator interferes with his trading.

If the manipulator has driven the price close to zero to avoid the unraveling problem,

will the informed investor or active traders reenter the market and buy the underpriced shares?

They will not unless they are confident they can overcome the impact of the manipulation.

However, if they offer to buy shares, the manipulator can increase the naked short position to

prevent the share price from rising. If he can keep the price close to zero, then prospective

financiers are likely to conclude that the firm’s prospects have worsened and refuse to lend or

invest in its equity. Customers may cease doing business with it as well because its warranties

will appear worthless. Eventually, the firm will exhaust its liquidity and have to file for

bankruptcy. The manipulator will be relieved of its obligation to cover its short position if the

firm’s shares are cancelled in bankruptcy.68 This scenario leads to a zero cost of covering the

short positions. This form of manipulation may involve a single manipulator or a group of

manipulators who act in concert and make an unusually high percentage of apparently unlucky

equity investments that become worthless in bankruptcy, all of which have unusually high

trading volume, large and persistent fails to deliver, and a precipitous drop in share price below

the stock’s intrinsic value (often to just pennies a share).

47

Finally, the manipulator might be even more aggressive if he is not satisfied with the

profit he can earn in a pooling equilibrium. But the more aggressive naked shorting increases the

risk of detection. If the active traders detect the manipulation, two reactions are possible. They

might exit the market (N = 0), which leads to case II regardless of the informed investor’s cost of

short selling. The manipulator benefits because there is no competition from active traders to sell

short at time 2, which results in higher P*(2). He sells short to uninformed traders at time 1 and

time 2.

Alternatively, the informed investor might free ride on the manipulation. He benefits if

the manipulator drives P*(3) below L. However, he risks being branded a manipulator. The

informed investor will not free ride if the intrinsic value is H because he would then become a

manipulator.

Suppose the informed investor and the active traders decide to free ride on the

manipulation. Their short sales reduce P*(2) and thus the manipulator’s profit. For large N, the

informed investor sells short approximately (A – 2C)/(3B) and the manipulator sells short

approximately (A + C)/(3B) shares at time 1, neither sells short any shares at time 2, and the

active traders collectively sell short approximately (A + 4C)/(3B) shares at time 2. P*(2) is

approximately zero. Competition among the active traders drives P*(2) toward zero and results in

none of them earning a nontrivial profit. The manipulator’s profit if the informed investor and a

large number of active traders free ride is

(A C)2 /(9B) M π = + (50)

The informed investor earns a smaller profit because he sells short fewer shares. The combined

profit of the manipulator and the informed investor is

(2A C)(A C) /(9B) M I π +π = − + (51)

48

The manipulator maximizes his profit by driving competing short sellers from the

market. The manipulator aggressively sells short enough shares at time 1 to drive the price down

sharply. The heavy volume of sell orders and resulting sharp decline in price are likely to scare

off legitimate traders if they signal that the shares are about to be delisted to the OTC Bulletin

Board market, which is much less liquid than the Nasdaq National Market and the exchanges.

This likelihood increases if the manipulator is recognized by the informed investor and the active

traders as an aggressive ‘bear raider’. In this case, the manipulator not only does not want to

conceal his identity from legitimate active traders, he wants to make them aware of it to drive

them out of the market. He will try to maintain his naked short position until the shares are

ultimately cancelled in liquidation. He maximizes his short sale proceeds by naked shorting

A/3B shares at time 1, A/3B more at time 2, and either L/B – 2A/(3B) or H/B – 2A/(3B) more at

time 3. The market prices are P*(1) = 2A/3, P*(2) = A/3, and P*(3) is close to zero, all regardless

of whether P*(3) should be H or L. The manipulator’s profit is

A2 /(3B)

which is greater than M π in equations (50) and (51) for reasonable values of C.

4.4 Complementary Manipulative Trading Strategies

The manipulator can depress the price to reduce the market value of the firm’s float and

discourage the informed investor and active traders from trading the stock. It also increases the

probability of delisting (Desai et al., 2002). The firm will fail to meet both the NYSE’s and the

Nasdaq National Market’s listing standards if its share price falls below one dollar for 30

consecutive trading days.69 Pushing the stock to the Nasdaq SmallCap market or the OTC

Bulletin Board market will discourage institutional investors from trading the stock because of

the lower liquidity in those markets. But it will remove the constraint on short selling that the

49

tick test and the bid test impose and allow the short seller greater latitude in depressing the share

price further. Selecting the stocks of riskier, small cap firms to manipulate makes it easier to

cause this failure because the drop in share price is less likely to arouse suspicion and attract

arbitrageurs who might bid up the price and cause the scheme to unravel. Pushing the stock onto

the Nasdaq SmallCap or the OTC Bulletin Board (OTCBB) also reduces the risk of regulatory

detection if the securities regulators focus their attention on the exchanges and the Nasdaq

National Market.70

Which alternative the manipulator pursues depends on whether he wants to conceal his

behavior and his aversion to detection risk. He can reduce this risk by achieving a pooling

equilibrium but must sacrifice some of the potential profit from more aggressive manipulation.

Departures from a pooling equilibrium (e.g., more aggressive naked shorting) are more likely

when the manipulator registers as a market-maker to avail himself of the short sale rule

exceptions and also when he succeeds in driving the share price below one dollar to push the

stock into a less regulatory intensive market, such as the OTC Bulletin Board. Driving the price

down enough to trigger delisting provides a natural cover for the manipulation because it signals

a deterioration in the firm’s financial condition and its prospects to those market participants who

are unaware of the fraud.71

The type of behavior modeled in this section is more likely to occur in the OTC Bulletin

Board market than on the exchanges or in the Nasdaq National Market. It might take the form of

trading by investment ‘pools’ (informal investor networks) that have enlisted the cooperation of

one or more market-makers, who reduce the risk of detection because of the market-maker

exceptions to the short sale rules. These pools could reduce the risk of detection by spreading the

50

short selling across a large number of sophisticated investors, and the large number of sellers

would increase the credibility of the sell signal. These pools could include investors, such as

hedge funds who profess to follow short-sale strategies, who regularly sell stocks short because

interspersing manipulative trades with regular short selling reduces the risk of detection.72

4.5 Regulation SHO

Regulation SHO imposes a mandatory buy-in for stocks that remain on the NSCC’s

threshold list for 13 consecutive trading days (SEC, 2004). There is no market-maker exception.

If all stock trades cleared through the NSCC, the buy-in requirement would prohibit fails to

deliver in excess of 0.5 percent of a stock’s outstanding shares for more than 18 trading days (5

days to make the list plus 13 on it). Since trades also clear outside the NSCC (referred to as exclearing

in the securities industry), greater and more extended fails are still possible. Research

concerning whether Regulation SHO has curbed excessive fails to deliver seems warranted. Is

there evidence of buy-ins of stocks that have remained on the threshold list for 13 days, or has

Regulation SHO raised the proportion of stock trades that settle ex-clearing?

5. Floating-Price Convertibles and Resolving the Unraveling Problem

Floating-price convertibles (FPCs) became a popular form of PIPE (private investment in

public equity) financing in the 1990s. Hillion and Vermaelen (2004) identify 467 issues of FPCs

that firms issued between January 1995 and July 1998. FPCs allow the manipulator to resolve the

unraveling problem by covering his short position with FPC conversion shares. This can increase

the profitability of manipulative short selling. Because he faces less risk of a short squeeze, the

manipulator can sell short more shares. The greater selling further reduces the firm’s share price,

which increases the manipulator’s profit. It also increases the number of conversion shares at no

51

additional cost. Finally, the manipulator obtains a valuable delivery option. If he naked shorts, he

does not have to drive the firm into bankruptcy to avoid covering the short position; he can

deliver the conversion shares.

5.1 Equilibrium When Short Selling Is Expensive

The firm needs to raise F to finance a new project. It sells F = P*(1) x Z face amount of

FPCs at time 1, which is convertible into Z new shares at a discount to the market price at the

time of conversion. The discount D is usually in the range from 15% to 25% (Hillion and

Vermaelen, 2004). The initial conversion ratio is Z/(1 – D), and the intrinsic value of the

conversion option is initially F/(1 – D). Conversion can begin after a specified grace period

expires, which I assume is time 2.

I assume that the firm invests the proceeds of the new issue in a zero-net-present-value

project. The present value of the project’s free cash flow is F/(1 – D) to compensate for the

discount (and leave the wealth of the existing shareholders unaffected).73

The manipulator buys the FPCs and sells short at time 1. His short selling at time 1

reduces the firm’s share price and increases the initial conversion ratio for given new issue

proceeds F. Since the announcement of a zero-NPV project does not shift the active traders’

demand curve, the demand curves are * (1) ( ˆ (1) ˆ (1) (1))

time 2 and the rest at time 3.

52

The manipulator sells short ˆ (1) M Q shares at time 1. In a pooling equilibrium, the

manipulator sells short at time 1 and covers the short position at time 2 if the time 3 intrinsic

value is H. His profit on his FPC investment apart from any short sales is

which is the value of the discount specified in the FPC contract. It does not matter whether the

FPC investor converts at time 2 or time 3 so long as the conversion shares are priced and

delivered concurrently because the FPC pricing formula provides a perfect hedge. The FPC

investor receives F/((1 – D)P) shares, which are worth P each and F/(1 – D) in the aggregate.

Including short sales, his profit is

The manipulator earns the same profit (equation (40)) on his short sales as he would without the

FPC investment. The short sales do not affect the profitability of the FPC investment because the

FPC provides a perfect hedge when the conversion shares are priced and delivered concurrently.

The manipulator should not use the conversion shares to cover the short position because that

strategy would save him P*(2) at time 2 but cost him H > P*(2).

Recall that when the time 3 intrinsic value is L, the manipulator can not profit at the

margin unless he can achieve a lower cost of shorting than the informed investor or unless he can

pursue strategies that cause the informed investor to reduce his short sales. Incremental short

selling is unprofitable when the manipulator’s cost of shorting is C. The manipulator’s

opportunity cost of using the conversion shares to cover the short position is P*(2), and a profitmaximizing

informed investor will short sell that number of shares which reduces the marginal

53

shorting profit to zero when the cost of shorting and covering is P*(2) + C. The manipulator can

not increase his overall profit by substituting conversion shares for market share repurchases.74

Investing in the FPC gives the manipulator a valuable delivery option because he can use

conversion shares to cover the naked short position if the clearing house demands delivery of

shares and if it is more expensive to purchase shares in the market than to deliver conversion

shares. Merely submitting the conversion demand notice eliminates the naked short position.75

This option reduces the manipulator’s risk of detection because a short squeeze is impossible so

long as the number of conversion shares exceeds the naked short position. Investing in the FPC

also generates a virtually guaranteed profit because of the discount and the FPC’s built-in hedge.

This profit is available to offset potential losses on the short selling, if the price of the shares

should rise. The FPC provides insurance that reduces the manipulator’s financial risk.

5.2 Equilibrium When Short Selling Is Inexpensive

The manipulator can profitably sell short incremental shares at time 1 and time 2 in the

lower-shorting-cost cases (I – III) when the time 3 intrinsic value is L. A pooling equilibrium

results in which the manipulator behaves like the informed investor. If he buys FPCs, he obtains

the valuable delivery option and insurance against loss. The greater combined short sales by the

informed investor and the manipulator at time 2 reduce P*(2), which causes the active traders to

reduce their short sales. The greater the perceived risk of manipulation (β ) , the greater the

informed investor’s and the manipulator’s short sales at time 2 and the smaller are the active

traders’ short sales.

5.3 Aggressive Naked Shorting

54

The manipulator will not sell short in cases I-III if the intrinsic value is H unless he can

manipulate P*(3). The manipulator might engage in aggressive naked shorting and use the FPC

conversion shares for either of two purposes, depending on the anticipated time 3 price of the

stock. I assume that through his due diligence, the manipulator can accurately assess the firm’s

future prospects well enough to determine whether the manipulation-free time 3 price will be L

or H. This assumption is more plausible when the manipulator purchases FPCs because of the

due diligence that usually accompanies a private securities issue (Blackwell and Kidwell, 1988).

FPCs give the manipulator two valuable overlapping options, the option to expropriate

wealth from the other shareholders and the option to gain voting control of the firm. He can

aggressively short the stock to depress its price if the time 3 intrinsic value is L and then cover

the short position with the cheap conversion shares. He uses naked shorting to exploit an

overvalued stock, whose price would normally be expected to fall to L. He can permanently

manipulate the share price below L, perhaps to only pennies a share, and keep the price

artificially depressed by flooding the market with the cheap conversion shares to dilute the share

price and by extending his strategic fails.

The issuance of FPCs is perceived as a negative signal if active traders and the informed

investor associate it with manipulation. They can either stay out of the market to avoid becoming

victims of the manipulation resulting in a separating equilibrium or else free ride on the

manipulator’s behavior resulting in a pooling equilibrium.

If the manipulator is the only short seller, he enhances his profit by naked shorting. The

manipulator’s profit is

55

when the manipulator engages in naked shorting at time 1 and time 2, tenders the conversion

notice at time 3, and fully covers both short positions at time 3. P(t) is the conversion price,

which is determined at the date t the FPC investor submits the conversion notice. The

manipulator could increase his profit by (Qˆ (1) Qˆ (2))P * (3) M M + by extending the strategic fail

until the firm liquidates. Since the firm is overvalued at time 1, its share price would decline

from P*(1) to L in the absence of any manipulation. The manipulator maximizes his profit by

maximizing his short sale proceeds and naked shorting P*(3) close to zero.76 The manipulator

should sell short A/(3B) shares at time 1 resulting in P*(1) = 2A/3 and Z=3F/(2A). These short

sales occur at the time of the financing because the manipulator has an incentive to begin

shorting the stock immediately. He should sell short an additional A/(3B) shares at time 2. If L >

A/3, the manipulator will naked short more shares than the firm has outstanding. The share price

is P*(2) = A/3, which is half what it was at time 1. At time 3, the financial condition of the firm

is revealed, and the uninformed traders’ demand curve shifts to P = L – BQ. The manipulator

drives P*(3) close to zero by adjusting the short position to L/B shares. If L > 2A/3, the

manipulator will increase his short position; otherwise, he will decrease it.77

The manipulator’s profit is

the profit on its FPC investment plus its profit on the short sale. Aggressive short selling has

increased the manipulator’s profit. This has occurred with a huge volume of naked shorting –

possibly exceeding the firm’s outstanding shares – and a precipitous decrease in share price that

first cut the price in half and then reduced it close to zero.

56

Suppose instead the manipulator submits the conversion notice at time 2. By selling short

an additional 2A/(3B) shares for a total of A/B, he can depress P*(2) close to zero and obtain a

virtually infinite number of shares. He dilutes the equity ownership interest of the other

shareholders virtually to zero, covers the naked short at time 3 at virtually zero cost, and realizes

profit equal to

which equals the profit on the FPC plus the profit on the naked short sale at time 2 plus the

entire equity value of the firm at time 3. The profit in equation (57) is greater if

time 2 short sale when the manipulator waits to time 3 to submit the conversion notice. This

condition is satisfied if the likelihood that the time 3 intrinsic value of the firm will be H is high

enough.

The manipulator selects the conversion strategy that maximizes his profit. If the time 3

intrinsic value is (highly likely to be) L, the manipulator will sell short A/(3B) shares at time 2,

cover the short at time 3, and wait until time 3 to depress the share price close to zero. If the time

3 intrinsic value is (highly likely to be) H, he will sell short A/(2B) shares at time 2 to depress

the price close to zero at time 2.78

For example, suppose the manipulator realizes at time 2 that the firm’s share price the

next period will be H, rather than L as originally expected, say, due to favorable developments in

the firm’s business. Suppose further that the securities regulators or the clearing house require all

securities dealers to clear up all fails to deliver.79 The manipulator would face potentially large

57

losses on his short sales. By short selling an additional 2A/(3B) shares at time 2, he can drive the

share price close to zero. He would obtain sufficient shares to dilute the equity ownership interest

of the other shareholders virtually to zero. He realizes virtually the entire equity value of the firm

and achieves a profit equal to

Owning the FPCs gives the manipulator a valuable hedge against the regulatory risk that the

regulators might enforce, or require the clearing house to enforce, the restrictions on short sales

and fails to deliver. The FPCs give the manipulator a valuable manipulative tool he can use to

blunt the impact of any unexpected tightening of short sale restrictions.

The informed investor may decide to free ride on the manipulation when he realizes that

the stock is being manipulated by an aggressive short seller. He recognizes that sellers will be

able to use the decrease in the stock’s price ex post to justify their short selling. The justification

will appear plausible if as a result of the manipulation, the company is driven out of business. If

the informed investor and the manipulator sell short at time 1, the active traders will also at time

2, which will intensify the downward price pressure on the stock.

The manipulator maximizes his profit by naked shorting, which distinguishes his

behavior from the informed investor’s. The manipulator sells short

and

The informed investor sells short fewer shares unless its cost of shorting is zero, which occurs

58

when it joins in the naked shorting. The total short sales at time 1 are approximately 2A/(3B) –

5C/(9B) when the number of participating active traders is large and the market price is

which approaches A/3 + 5C/9, about one-third the initial price, as a limiting value. The total

short position at time 2 amounts to approximately A/B, which is more shares than the firm has

outstanding. The manipulator and the informed investor each accounts for about 4/9 of the total

(3/9 sold at time 1 and 1/9 at time 2), and the active traders collectively account for 1/9 (all

shorted at time 2). The time 2 market price is

which approaches C/3 as a limiting value as the number of active traders increases.

FPCs embody a valuable option to gain voting control, which the manipulator has an

incentive to exercise when the time 3 price will be H. The manipulator can gain control by

acquiring one more than 50 percent of the outstanding shares. The informed investor will not sell

any shares short because the time 3 price will be H. The manipulator naked shorts at time 1 and

time 2 to depress the share price before submitting conversion notices. He then demands

conversion shares based on the cheap price, and if the price is low enough, he obtains sufficient

shares to achieve voting control of the firm with the economic benefits that accompany control.

The manipulator’s profit-maximizing strategy is to submit the conversion notice at time 2

after driving down the price. The conversion price is P*(2)[1 – D]. His profit is

(1)[ * (1) 2 ] (2)[ * (2) ]

* (2)[1 ]

[ * (2)]

1

Profit is equal to the value of the discount plus the profit on the cheap conversion minus the

losses on the short sales at time 1 and time 2 (since H > P). The profit on the cheap conversion is

59

greater the lower is P*(2), but the loss on the short sales at time 2 is also greater. Naked shorting

reduces these losses. The manipulator will not sell short at time 1 to avoid the losses on time 1

short sales.80 In that case, the active traders would not sell short because they do not observe any

short sales at time 1.

Suppose the manipulator did not sell any shares short at time 2. His profit would be

(Q (2) 0) F[H A(1 D)] /[A(1 D)] M M π = = − − − (64)

The manipulator makes money on the FPC without short selling but short selling increases his

profit. The manipulator increases his profit by increasing his short sales to A/B.81 P*(2) falls

nearly to zero, and the manipulator gets enough shares to dilute the other shareholders’ collective

equity interest virtually to zero. The manipulator realizes virtually the entire economic value of

the firm even after using A/B shares to cover his short position. The firm’s share price will

remain near zero because of the dilutive effect of the conversions at a near-zero price. The

manipulator’s profit is approximately

The manipulator is able to expropriate wealth amounting to H(A – L)/B from the other

shareholders.

5.4 The Firm’s Failure to Honor Conversion Notices to Control Moral Hazard Risk

How can the firm deal with the moral hazard risk that the FPC investor turns out to be a

manipulator who aggressively short sells its stock? The firm can attempt to control this risk by

insisting on a provision in its FPC contract that prohibits the investor from short selling its stock.

The investor should not object because the floating-price feature of the FPC provides a natural

60

hedge against a falling share price. The firm can also refuse to honor the investor’s conversion

requests. However, that strategy is risky for the firm because it exposes the firm to the accusation

that it has breached the FPC contract.82

If the firm fails to honor any of the conversion requests, the investor is out of pocket F

but still has an investment that is in theory worth F/(1 – D). FPCs are usually unregistered, and

so there is no public market for them. The FPC investor can attempt to find another private

investor who is willing to purchase the FPCs. But if the FPC investor has manipulated the firm’s

share price downward and the firm has refused to honor the conversion requests, a prospective

sophisticated private purchaser would be alerted by the decline in share price. He would

presumably discover in the course of his due diligence, for example by calling the firm, that it

has refused to honor the conversion notices and would refuse to purchase the FPCs. The FPC

investor would be unable to exit his investment. This prospect should discourage manipulators

from purchasing FPCs with a short-sale prohibition in the contract. By insisting on such a

provision, a prospective FPC issuer can detect a potential manipulator.

5.5 FPCs and the Faulty Contract Design Hypothesis

Hillion and Vermaelen (2004) find that the stocks of FPC issuers realize an average

return of -43.78 percent after adjusting for market effects during the year following the offering

and that 85 percent of the post-announcement returns are negative. They test three hypotheses

that might explain this behavior and find support for the faulty contract design and last-resort

financing hypotheses but no support for the undervaluation hypothesis.

The sharp price declines Hillion and Vermaelen document are consistent with the model

of share price manipulation developed in this paper. My model suggests the following

61

explanation for their results. Manipulators offer potentially attractive long-term financing to

smaller, riskier firms who may be unable to raise such large amounts of equity by issuing

common stock or conventional fixed-conversion-price convertible securities and issue FPCs as a

last resort. The financiers, who can drive the harder bargain because of the firm’s need for funds

and lack of alternatives, insist that the firm issue FPCs. Optimistic managers and existing

shareholders, who may believe that their firm’s shares are more likely to rise than fall when the

funds are invested in the business (thereby reducing the number of shares the firm will have to

issue when the FPCs are converted), fail to appreciate the risks inherent in issuing FPCs and

agree to the choice of security, possibly even issuing it multiple times (Hillion and Vermaelen,

2004). Once the firm has issued the FPCs, the financiers/manipulators can exploit its flaws to

manipulate the stock to their advantage and to the firm’s detriment.

In light of the SEC’s concerns about the impact of naked shorting and the implications of

my model that FPCs are an effective instrument to complement naked shorting, it would seem

appropriate to reexamine the after-issue performance of FPC issuers to determine whether (and

to what extent) naked shorting (and other forms of manipulation) might have contributed to the

large negative returns. Such an investigation might reveal that the faulty contract design

hypothesis is an even better explanation for these returns than Hillion and Vermaelen suggest

because the flaws in the contract facilitate manipulative short selling.83

62

6. Conclusion

The SEC’s recent adoption of Regulation SHO has drawn attention to the potentially

disruptive impact of manipulative short selling, and in particular, naked short sales masquerading

as routine fails to deliver. An interesting empirical question concerns the impact of manipulative

short selling on the capital market in the United States. Some recent evidence suggests that

strategic fails to deliver are pervasive and are not confined to the over-the-counter market. The

impact of these fails to deliver has never been investigated, however. A related question concerns

the impact of Regulation SHO, which became effective January 3, 2005, and in particular,

whether this regulation has had the intended effect of curbing abusive short sales.

Analyzing both questions requires a model of stock market behavior. This paper models

market equilibrium and describes the market impact of manipulative short selling. Naked short

selling is shown to be a particularly effective and damaging manipulative device. It is difficult to

control because of the market-maker exceptions to the normal restrictions on short selling,

including permitting naked short selling in the course of bona-fide market-making activity. A

recent securities innovation called floating-price convertible securities removes an important

constraint on short selling by resolving the unraveling problem. I conclude that the current

capital market environment and regulatory regime, Regulation SHO notwithstanding, are

conducive to manipulative short selling. I will leave it to future research to test this conclusion

empirically and measure the impact of the manipulation.

A recent study of FPCs by Hillion and Vermaelen finds that FPC issuers experience large

negative returns following the issue, which the authors partly attribute to flaws in the FPC

contract. The SEC’s concerns about the impact of naked shorting, as reflected in its adoption of

Regulation SHO, coupled with the implications of my model that FPCs can intensify the adverse

impact of naked shorting suggest that further study of Hillion and Vermaelen’s faulty contract

63

design hypothesis is warranted. This research should investigate whether FPC investors short the

issuer’s stock, for example, in anticipation of submitting conversion notices. Such a strategy is

unnecessary because of the natural price hedge built into the floating-price structure. Evidence of

significant shorting would imply that the FPC’s faulty contract design may play a more

important role in the share price decreases Hillion and Vermaelen document.

64

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