Algorithmic Finance Meetup: Starmine Short Interest Talk
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Finding Alpha in Short Interest Data New York, March 21, 2013 Jessica Stauth, Ph.D. Director, Quant Product Strategy – Thomson Reuters
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With the commoditization of such basic quant factors as value and momentum, in recent years systematic investors have turned more and more to sentiment based alpha signals. Aggregated open short interest level provides a profitable, low turnover signal rooted in buy-side sentiment, aka "the smart money." Dr. Stauth will cover the basics of short selling and data availability and will review the research and proprietary formulation of the StarMine short interest model as well as covering a range of sample trading strategies.
Transcript of Algorithmic Finance Meetup: Starmine Short Interest Talk
Finding Alpha in Short Interest DataNew York, March 21, 2013
Jessica Stauth, Ph.D.
Director, Quant Product Strategy – Thomson Reuters
Short Interest as Stock-ranking Signal• Introduction
• StarMine Signal overview, In/Out of Sample and Live Returns
• StarMine SI Model Formulation– Baseline ratio
– Institutional Ownership adjustment
– Merger arbitrage
– Dividend payments
– Short Squeeze Indicator
• Recap – universe selection, correlations and turnover
• Q&A
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Introduction
• What is a short sale? Why is a short sale?
• How can I find out how many shares are sold short for a given stock?
• Can short interest data be used as an input signal for quantitative investment strategies?
• What risks or known caveats are there to a strategy of following the shorts?
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What/Why is a short sale
• What is a short sale? The sale of a security that the seller does not own (or deliver).
• Why is a short sale?– Fundamental Shorts – aka Valuation shorts: when an investor has
conviction that an individual stock is overvalued.
– Hedge shorts – risk management technique to reduce exposure incurred through long investments. e.g. pairs trading
– Arbitrage shorts – exploit mispricing between two assets or asset classes. e.g. M&A arb (buy the acquiree, short the acquirer) or convert arb (buy the debt, short the equity)
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HLF – Ackman v Icahn, value short or prelude to the ‘mother of all short squeezes’ ?
Feb 6
Yesterday…
LINK
How can I find out how many shares are sold short for a given stock?
From the exchange e.g. NASDAQ , NYSE, AMEX
Data is available on a twice-monthly basis on an 8-day delay
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Can short interest data be used as a signal for quantitative investment?Yes. A simple ratio of shares sold short / shares outstanding (or shares
short/ADV) can be used as a buy-side sentiment signal.
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What risks or known caveats are there to a strategy of following the shorts?• Trying to short ‘hard to borrow stocks’ , which, even when you
can short them, incur high t-costs
• Emulating short positions or changes in shorting levels that are not reflective of “value” shorts, but rather are hedges or arbitrage shorts.
• Data shortcomings
– the free/cheap exchange provided data is “low frequency” and published at a delay (actually based on the nature of the signal neither of these is a deal-breaker).
– must be sourced from each exchange independently – can be a pain if you want to trade on many exchanges.
• Possibility of a ‘short squeeze’ or loan recall
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DISCLAIMERS!
Short Interest as Stock-ranking Signal• Introduction – what is a short sale, and why should quants care
• StarMine Signal overview, Out of Sample and Live Returns
• StarMine SI Model Formulation– Baseline ratio
– Institutional Ownership adjustment
– Merger arbitrage
– Dividend payments
– Short Squeeze Indicator
• Recap – universe selection, correlations and turnover
• Q&A
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StarMine Signal Overview
SharesSold Short
Shares Outstanding
Shares Held by
Institutions
Adjusted Baseline Short Interest Rank
Conditioning Factors:1. Dividend Payments
2. M&A Activity
StarMine Short Interest Final Rank
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The StarMine Short Interest Model combines short interest data from US exchanges with institutional holdings and accounts for dividends and M&A in an intelligent, robust way.
Comparable in and out of sample performance – a good sign we didn’t overfit.
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The StarMine SI model was built on in-sample data from 1/2004 – 1/2009 and tested on out-of sample data from 1/2009 – 1/2011
Long/Short returns continue to look good in the first 24 months of true out of sample (aka “live”) data
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Live Results
Cumulative returns to Top, Bottom and L/S SI Portfolios Jan 2004 - Jan 2013 vs. R3000
Live Performance slice only
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Notes: the long-only side of the book suffered ~22% draw down in mid-2011 in line with the R3K while the market-neutral strategy continued to accumulate profit.
The largest L/S draw down (~14%) hit later in 2011 at the market turnaround
Short Interest as Stock-ranking Signal• Introduction – what is a short sale, and why should quants care
• StarMine Signal overview, Out of Sample and Live Returns
• StarMine SI Model Formulation– Baseline ratio
– Institutional Ownership adjustment
– Merger arbitrage
– Dividend payments
– Short Squeeze Indicator
• Recap – universe selection, correlations and turnover
• Q&A
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Baseline ratio
– Low (high) short interest levels predict out (under)-performance in US Equities, with low correlation to commonly used quant factors (value, price momentum, etc)
– Academics have been writing about this anomaly for years (selected refs: Diamond 1987, Dechow 2001, Desai 2002, Arnold 2005, Asquith 2005, Engleberg 2010)
– We propose that the short interest “anomaly” is a combination of market (in)efficiency and biases: SEC requires disclosure of short positions (as a measure of transparency) semi-monthly and investors believe that short sellers are good stock pickers.This leads to herding as people follow the “smart money”
Naïve Baseline Ratio: Rank [ ], per company
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Decomposing short interest quintiles by institutional ownership reveals an interaction
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Shor
t Int
eres
t Qui
ntile
s
Pct held by Inst. Quintiles
least held by institutions 2 3 4
most held by institutions
Mean return by lvl of short
most heavily shorted 0.06% 0.12% 0.34% 0.24% 0.82% 0.31%2 0.49% 0.38% 0.38% 0.35% 0.83% 0.49%3 1.03% 0.37% 0.56% 0.39% 0.93% 0.65%4 1.38% 0.70% 0.66% 0.52% 1.19% 0.89%
least shorted 1.14% 1.26% 0.79% 0.71% 1.38% 1.05%
SI spread 1.08% 1.14% 0.45% 0.47% 0.56%outperformance underperformance
Mean one month return for all stocks in each bucket
As might be expected, high levels of short interest in stocks with low institutional ownership (which we use a proxy for ‘hard to borrow’) underperform heavily shorted stocks with high levels of institutional ownership.
We view these as ‘high conviction’ shorts, which will also clearly be more difficult to trade in practice.
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Event Study: M&A arbs artificially drive down the SI Rank of ‘acquiree’ companies
In the 30 days surrounding an acquisition announcement we see an increase in the short interest level of the acquiring company that is typically uncorrelated to any changes in fundamentas.
Large dividend payments drive short sellers (temporarily) out of stocks
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Event Study/Histogram: What is the distribution of large dividend payers across short interest deciles?
Too many lightly shorted companies implies artificial short covering on ex-date
StarMine provides a short squeeze indicator independent of the SI model rank to help users algorithmically identify potential short squeezes.
“Short Squeeze” means different things to different people. We look for a large forward 1-month “draw-up”.
What is F1M draw-up?The maximum % price increasefrom the first day of the period.
e.g., for HOV on 2007-7-31:F1M draw-up = (16.22 - 11.95)/11.95 = 35.7%
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Our goal is to predict the rank of F1M draw-up, rather than an absolute value.
StarMine short interest model rank informs price direction while the short squeeze indicator informs short term upside volatility.
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Short Squeeze Indicator : risk of one
month drawup
Short Interest model rank (1-100): relative to country, sector, or market cap quantile
Model scores update semi-monthly with short
interest data, monthly with ownership, and as reqd by
M&A and dividends
Recap: The StarMine Short Interest Model is a buy-side sentiment signal based on the hypothesis that short sellers are value-oriented investors making directional price bets.
US securities top 98.5% by marketcap
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L/S Turnover110% per year
Rank Correlations between SI and other StarMine models
Annual Spread Sharpe ValMo ARM PriceMo EQ RV IV
Short Interest
13% 1.17 0.216 0.022 0.060 0.101 0.240 0.172
QUESTIONS?
Appendix
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“borrows” stock (pays borrow rate)
What is a short sale?
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BD/II/Owner Short Seller Open Market Buyer
t=0
t=time to cover
Sells stock at t=0 day’s price
“returns” borrowed stock
Open Market Seller
Buys stock at t = time to cover’s price to “cover” the shares that need to be returned to the Owner
A stock “short sale” is a stock sale where the purchase price is not determined until AFTER the sale takes place.
*exceptions are hedges and arb strategies
Small cap performance exceeds large cap performance, but using the “cap neutralized” StarMine model rank does not hurt performance.
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• Leadership switched to Mid Cap in 1Q2009 after large drawdown• Large Cap performance has suffered since 1Q2009
We provide a market
cap neutral rank as part
of the model output
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We found that Days to Cover, a commonly used predictor of short squeezes, does not work better than a random indicator.• Days to cover = “Short Ratio” = # Shares Short / Avg Daily Volume (T1M)
• Our primary measure is hit rate (0-1, higher is better) - the number of stocks actually in the top decile of F1M draw-up / number of stocks predicted to be in the top decile. This is a measure of how good your highest-conviction predictions were.
•
We have developed an indicator that has a significantly better hit rate.
Hit Rate for Random Model = 0.1
