Short Selling

How well have long/short equity mutual funds done in recent years? In their April 2019 paper entitled “Hedge Funds Versus Hedged Mutual Funds: An Examination of Long/Short Funds; A Performance Update”, David McCarthy and Brian Wong present an out-of-sample update of a prior performance assessment of long/short equity mutual funds (see “Multialternative Mutual Fund Performance”). They track the same universe as the prior paper and therefore do not include funds launched after January 2013. They construct an equally weighted index of long/short equity mutual funds, rebalanced monthly. They compare performance of this index to those of the S&P 500 Total Return Index, HFRI Equity Hedge Fund Index (HFRI Index) and the Dow Jones Credit Suisse Long/Short Equity Hedge Fund Index (DJ-CS Index). Using monthly returns of 26 live, 14 dead and 4 changed (up to date of change) long/short equity mutual funds established as of January 2013 along with contemporaneous returns for benchmark indexes during July 2013 through December 2018, they find that:

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Do “bubble” stocks (those with high shorting demand and small borrowing supply) exhibit unconventional momentum behaviors? In their December 2018 paper entitled “Overconfidence, Information Diffusion, and Mispricing Persistence”, Kent Daniel, Alexander Klos and Simon Rottke examine how momentum effects for bubble stocks differ from conventional momentum effects. They each month sort stocks into groups independently as follows:

1. Momentum winners (losers) are the 30% of stocks with the highest (lowest) returns from one year ago to one month ago, incorporating a skip-month.
2. Stocks with high (low) shorting demand are those with the top (bottom) 30% of short interest ratios.
3. Stocks with small (large) borrowing supply are those with the top (bottom) 30% of institutional ownerships.

They then use intersections of these groups to reform 27 value-weighted portfolios. Bubble (constrained) stocks are those in the intersection of high shorting demand and low institutional ownership, including both momentum winners and losers. For purity, they further split bubble losers into those that were or were not also bubble winners within the past five years. Using monthly and daily returns, market capitalizations and trading volumes for a broad sample of U.S. common stocks, monthly short interest ratios and quarterly institutional ownership data from SEC Form 13F filings during July 1988 through June 2018, they find that: Keep Reading

In the June 2018 draft of their paper entitled “An Information Factor: Can Informed Traders Make Abnormal Profits?”, Matthew Ma, Xiumin Martin, Matthew Ringgenberg and Guofu Zhou construct and test a long-short information factor (INFO) based on observed trading of firm insiders, short sellers and option traders. Specifically, the INFO portfolio:

• Is each month long the 10% (decile) of stocks with the highest levels of net buying (purchases minus sales) by top managers scaled by the average number of shares held by all top managers over the calendar year.
• Is each month short stocks based on both short interest (number of shares short divided by shares outstanding) and associated option trading activity (volume of liquid put and call options divided by volume of associated stock). They sort stocks independently on short interest and option trading activity, add the two ranks for each stock and short the decile of stocks with the highest combined ranks.

They further examine whether INFO is a key driver of hedge fund returns. Using monthly data for specified variables, monthly returns for a broad sample of U.S. stocks priced over $5 and monthly returns for 13 hedge fund indexes and 5,565 individual U.S. equity hedge funds during February 1996 (limited by options data) through December 2015, they find that: Keep Reading

Is optimal stock anomaly exploitation long-only or long-short? If not long-short, does shorting the market rather than individual stocks work as well as shorting individual stocks? In his November 2017 paper entitled “How Do Short Selling Costs and Restrictions Affect the Profitability of Stock Anomalies?”, Filip Bekjarovski explores effects of short selling costs and constraints on the viability of exploiting seven U.S. stock anomalies: size, value, profitability, investment, momentum, accruals and net issuance. He constructs all anomaly portfolios via market capitalization weighting of stocks sorted into tenths (deciles). He measures portfolio alphas relative to the market excess return (1-factor). He considers long-only (long the top decile), conventional long-short (long the top and short the bottom deciles) and hybrid long-short (long the two highest alpha deciles, tilted toward the highest, while short the market). Anomaly portfolio rebalancing is annual for all except momentum (monthly). He analyzes effects of shorting costs based on an April 2017 proprietary snapshot of institutional stock borrowing fees. He specifically estimates a shorting cost threshold above which investors should switch between long-short and hybrid long-short exploitation methods. Using the stock borrowing fee snapshot and data required to construct seven anomalies from a broad sample of U.S. common stocks during July 1963 through December 2016, he finds that: Keep Reading

Do legal, policy and practical constraints on short selling substantially detract from factor investing performance? In their February 2017 paper entitled “Factor Investing: The Rocky Road from Long Only to Long Short”, Marie Briere and Ariane Szafarz examine how severely constraints on short selling affect the attractiveness of factor investing. They consider 11 assets consisting of the value-weighted market and the separate long and short sides of five widely studied factors (size, value, profitability, investment and momentum). Short sides consist of the stocks typically shorted when quantifying factor returns, but they are not short portfolios. They use these 11 assets to construct five gross-of-costs mean-variance efficient sets of portfolios, all with net long exposure 100%:

1. FF [Fama-French] Benchmark: 100% long the market, plus exposures to the 10 factor long and short sides, with respective long and short sides exactly offsetting (one positive and one negative).
2. Global long-only: positive exposures only to all 11 assets.
3. Long-short market + long-only factors: positive or negative market exposure, but positive exposures only to the 10 factor long and short sides.
4. 130/30: total negative exposure to all assets capped at 30% of portfolio value.
5. Global long-short: positive or negative exposures to all 11 assets.

Their principal analysis compares the efficient frontiers of these sets of portfolios. Using monthly market and factor long and short side returns as specified during July 1963 through December 2015, they find that: Keep Reading

“When to Sell Equity Index Put Options” summarizes research finding that the “insurance” premium from systematically selling equity index out-of-the-money (OTM) put options concentrates during the last few days before expiration. An ancillary finding is that a similar, though weaker and more volatile, pattern holds for selling at-the-month (ATM) put options. To test the general finding, we therefore look at the monthly return pattern for the CBOE S&P 500 PutWrite Index (PUT). PUT sells a sequence of one-month, fully collateralized (cash covered) ATM S&P 500 Index put options and holds these options to expiration (cash settlement). Per the referenced research, PUT gains should noticeably concentrate in the week before monthly option expiration. Using daily levels of PUT during mid-July 1986 through mid-February 2017, we find that: Keep Reading

Can speculators squeeze the “insurance” premium from shorting equity index put options in just the few days before expiration? In their January 2017 paper entitled “The Timing of Option Returns”, Adriano Tosi and Alexandre Ziegler investigate the timing of returns from shorting out-of-the-money (OTM) S&P 500 Index put options. Specifically, they compute daily excess returns (accruing return on cash for open short positions) for the two front contracts (“front-month” and “back-month”) up through expiration. They translate findings into strategies that open equally weighted short positions in the most liquid OTM puts a certain number of days before expiration and hold to the cash-settled expiration. They also consider delta-hedged positions via long S&P 500 Index futures. In most calculations, they account for market frictions by opening (closing) short positions at the bid (ask). Using daily data for S&P 500 Index levels, options and futures, and contemporaneous stock and option pricing model factors, as available during January 1996 through August 2015, they find that: Keep Reading

Do short sellers who publicly attack their targets affect stock prices? How do they choose their targets? In his October 2016 paper entitled “Activist Short-Selling”, Wuyang Zhao studies short sellers who publish adverse research on and/or publicly disparage the stocks they short. To assess unique effects of the negative publicity on targeted stock prices, he compares performances of targeted stocks on negative publicity days with those of the same stocks, and of industry peers with the closest or highest contemporaneous levels of short interest or increases in short interest, on short interest release days (five separate benchmarks). To identify characteristics of firms that attract activist short sellers, he examines 12 indicators of stock overvaluation and nine measures of uncertainty about firm prospects. Based on initial tests, he constructs aggregate metrics for overvaluation (averaging seven of the overvaluation indicators) and uncertainty (averaging six of the uncertainty measures) for subsequent tests. Using stock prices and firm characteristics related to 6,197 cases of activist short selling reported in Seeking Alpha or Activist Shorts Research during mid-February 2006 through December 2015, he finds that: Keep Reading

Can investors exploit the combination of unusual changes in hedge fund long positions and unusual changes in short interest for individual stocks? In the February 2015 version of their paper entitled “Arbitrage Trading: The Long and the Short of It”, Yong Chen, Zhi Da and Dayong Huang examine the power of three variables to predict stock returns:

1. Abnormal hedge fund holdings (AHF), the current quarter aggregate hedge fund long positions in a stock divided by the total shares outstanding minus the average of this ratio over the four prior quarters.
2. Abnormal short interest (ASR), the current quarter short interest in a stock divided by the total number of shares outstanding minus the average of this ratio over the four prior quarters.
3. The difference between AHF and ASR as a measure of imbalance in hedge fund trading.

They also examine how AHFSR interacts with ten widely used stock return predictors: book-to-market ratio; gross profitability; operating profit; momentum; market capitalization; asset growth; investment growth; net stock issuance; accruals; and, net operating assets. To measure the effectiveness of each predictor, they each quarter rank stocks into fifths (quintiles) based on the predictor and then calculate the difference in average gross excess (relative to the risk-free rate) returns of extreme quintiles. Using quarterly hedge fund SEC Form 13F filings and short interest data for a broad sample of U.S. stocks (excluding small and low-priced stocks), along with data required to compute stock return predictors and risk factors for these stocks, during 1990 through 2012, they find that: Keep Reading

Does accounting for the difficulty of covering short positions enhance the power of short interest to predict stock returns? In the February 2015 draft of their paper entitled “Days to Cover and Stock Returns”, Harrison Hong, Weikai Li, Sophie Ni and Jose Scheinkman examine days-to-cover short interest (DTC) of individual stocks as a return predictor. Their basic metric for DTC is monthly short interest divided by same-month average daily share turnover. They hypothesize that:

1. Short-sellers prefer positions they can close quickly without dominating trading volume.
2. A large DTC indicates that doing so would be difficult.
3. When DTC is high, short sellers must therefore believe strongly that the stock is overpriced.

The main approach of the study is to measure the performance of a hedge portfolio that is each month long (short) the equally weighted or value-weighted tenth or decile of stocks with the lowest (highest) DTC or short interest ratio (SR). Using monthly returns, short interest, shares outstanding, turnover, stock loan fees, stock/firm characteristics and institutional ownership and daily trading volumes for NYSE/AMEX/NASDAQ stocks as available during January 1988 through December 2012, they find that:

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