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Interpretation key for short interest & equity finance
A well-known use for US equity finance data is the estimation of
the Short Interest published by US exchanges in between the
bi-monthly publications of that dataset. This can be done
effectively and result in a timeliness and level of insight
unavailable from the Exchange Short Interest (SI) data alone. There
are important considerations when applying these methods, which
we'll discuss here. These considerations are critical for market
participants, highlighted by the January short squeeze when a
demand for real-time insights faced the real-world challenge of
providing them. Estimating Exchange SI with a model has advantages
and drawbacks which are revealed by reviewing the model output in
the context of the inputs.
The bi-monthly Exchange SI publications show the gross short
positions across underlying accounts held with FINRA member
broker-dealers. The disclosures are aggregated and made available
after the close on the 7th trading following the settlement date
they were collected for. The January 29th short interest dataset
was published by US exchanges after the close on February 9th.
Since the dataset was collected for January 29th settlement, it
reflects settled open short positions held from trade date January
27th.
Equity finance data including the number of shares on loan, is
also published for a settlement date and reflects the trade date
two days prior. This brings in an essential consideration for
estimating the short interest: the number of Shares on Loan, as
published by IHS Markit Securities Finance, can be considered the
net borrow demand beyond broker-dealers' internal supply of
shares.
When a short sale is made, the broker settling the trade can
either borrow shares from an external counterparty (picked up in
the equity finance dataset) or they can use shares already in their
custody for delivery to the counterparty who made the purchase from
the short seller. For Prime Brokers (PB), who handle most short
sales, the key sources of internal supply are hedge fund longs
(which may be in margin or fully paid accounts) and Delta-1 long
positions. The gap between the short interest and shares on loan
can generally be interpreted as the internal supply the brokers
held in custody and delivered to settle short sales.
The management of dynamic internal supply means that brokers
will modify their borrowing both to reflect changes in client short
positions and to reflect changes in their own internal
availability. They may also modify their usage of internal supply
in anticipation of supply or demand changes, which is why shares on
loan may react to an event on trade date or T+1. This creates a
challenge for estimating the short interest in real-time based on
shares on loan, because it's possible that a decrease in borrowing
reflects an increase in internal availability as opposed to a
decrease in short positioning.
To deal with share borrowing changes potentially being driven by
variations in broker-dealer longs, a model which estimates the
short interest needs to qualify the changes in shares on loan by
estimating the probability that they reflect a change in short
interest. The SI Forecast from IHS Markit does this partly by
looking at the historical relationship between the short interest
and shares on loan. The goal is to correctly forecast changes with
a minimum of error introduced by forecasting large changes that
don't materialize. For that reason, the SI Forecast incorporates
the most recently published Exchange SI data and subsequently
adjusts based on model inputs including shares on loan. The
forecast is unlikely to fully reflect a change in shares on loan
unless the two series are very similar historically, which suggests
a minimal Prime Broker internal availability.
GameStop Example:
The January 15th NYSE Short Interest dataset showed 61m shares
short for GameStop, a 9.4m share decline since the December 31st
publish. The January 15th dataset was published after the close on
January 27th. The timeline is important to note because during the
trading sessions from January 22nd to 27th, when the share price
increased from $65 to $347, the most recently available NYSE SI
data was the December 31st observation, which showed 71m shares
short.
GameStop Shares on Loan was published by IHS Markit as 51m
shares for January 15th, 9.4m shares lower than the NYSE SI for Jan
15 settlement. The January 15th equity finance dataset was
published on Jan 18 (S+1, with a weekend). By January 27th, when
the January 15th short interest was published, the most recently
published equity finance dataset was Jan 26th, which showed 41.7m
shares on loan, a 9.3m share reduction since Jan 15th.
From the perspective of post-close January 27th, market
participants knew that the short interest for Jan 15 was 61.8m
shares, which declined by 9.4m shares since Dec 31st. The Jan 26th
shares on loan showed a decline of 9.3m shares as compared with Jan
15th; if that were fully reflected in a reduction in short
interest, that would mean 52.5m shares short on Jan 27th.
The first SI forecast published by IHS Markit which reflected
knowledge of Jan 15th SI was for the Jan 27th dataset. That was
published on Jan 28th and estimated the short interest at 56.4m
shares. The forecast was heading in the direction of assuming the
change in shares on loan was the change in short interest (52.5m
shares), however, the model gave a lower weighting to the equity
finance data and was nearly 4m shares higher for that reason.
Over the final days of January, the Shares on Loan continued to
decline. From the perspective of February 1st, when the Jan 29th
equity finance dataset had been published, there were only 17.4m
shares on loan, reflecting a 31.5m share reduction in shares on
loan between Jan 15th - 29th. The most recent short interest was
still Jan 15th at 61.7m shares, so if the change in shares on loan
were fully reflected, that would mean 30m shares short. The SI
forecast published on Feb 1st estimated 50m shares short.
On February 9th, the short interest dataset for Jan 29th
settlement was published, which showed that short interest had
declined by 40m shares to 21.4m shares. The gap between the shares
on loan and short interest declined from 10.7m shares on Jan 15th
to 1.9m shares on Jan 29. The declining gap indicated the
possibility that hedge fund longs who had previously lent their
shares (in so doing reducing the need for their brokers to borrow
shares externally for client shorts) had recalled their shares over
the last two weeks of January, forcing a larger portion of the
total short position to be settled with shares borrowed from the
equity finance channel. The Jan 29th settlement pertains to Jan
27th trade date, which means the vast majority of the short
position had been covered by trade date Jan 27th.
The question may then be asked: Why bother with the forecast?
The purpose of the forecast is to provide a daily estimate of the
Exchange Short Interest which will be as close as possible to the
as-yet unpublished Short Interest figure. The previous publication
of that figure will, in general, be reasonably close, so the
assumption of no-change will yield a result that appears accurate
in comparison to a specific date, but obviously does nothing to
track changes between publishes. There is a persistent correlation
between the shares on loan and short interest for many US equities,
so using the shares on loan in a model makes sense; however, there
are known causes for the series to diverge (changes in
broker-dealer internal availability). Any suggestion of change from
the prior short interest has the potential to introduce error, so a
substantial recognition of changes in shares on loan should only be
done when the two series are highly correlated, grading slowly
toward a very limited reliance on equity finance data where there
is a low expectation for forecasting success. In this view, the
forecast performed as expected with the inputs available. It would
have been possible for the Jan 29 short interest to print at 50m
shares, which would have been interpreted as a substantial uptick
in dealer inventory, likely the result of an increase in hedge fund
longs (possibly also some index related Delta-1 longs). Given the
events which unfolded over the last week of January, along with the
decline in shares on loan, that may have been deemed unlikely, but
is important not to discount as a possibility when considering the
model output.
Conclusion:
The Exchange Short Interest publish is a valuable source of data
which is widely used. When the phrase "Short Interest" is used
pertaining to US equities it is understood to mean the bi-monthly
figures. One important caveat is that Exchange Short Interest only
includes short positions cleared by FINRA member broker-dealer
entities, which means it is possible short positions not to be
included. While the knowledge that the short interest data is not
comprehensive is important, there narrative impact from the common
knowledge of short interest may be more significant than ever. The
reporting lag and the lag to trade date mean that the shortest time
between a short sale being traded and included in the SI dataset is
ten trading days. On the eve of an SI release, the prior publish is
more than three weeks old. Equity finance data can help identify
short flows between publishes, and the comparison reveals other
signals; however, it is no panacea. Using a model to estimate short
interest can be helpful but introduces a new source of error and
should therefore, when precision is required, be considered in the
context of model inputs.
Posted 12 February 2021 by Sam Pierson, Director of Securities Finance, S&P Global Market Intelligence
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