Short Selling Keeps Markets Efficient
High-profile episodes, such as that involving GameStop, have led some to advocate for banning short selling. But new research confirms that short sellers play a valuable role in keeping markets efficient and preventing prices from overshooting their intrinsic value.
To sell a stock short, betting that the price will fall and allowing the shorter to buy it back in the future at a lower price, the trader must borrow shares and pay a loan fee. The borrowing fee reflects the demand for shorting by traders (as well as the supply by lenders of stock, generally institutions). Thus, stocks with the highest loan fees represent the strongest conviction on the part of short sellers. Those shorting play a valuable role in keeping market prices efficient, allowing for the efficient allocation of capital. If short sellers were inhibited from expressing their views on valuations, securities prices could become overvalued and excess capital would be allocated to those firms.
Research into the information contained in short-selling activity, including the 2016 study, “The Shorting Premium and Asset Pricing Anomalies,” the 2017 study, “Stock Loan Fees, Private Information, and Smart Lending” and the January 2020 study, “Securities Lending and Trading by Active and Passive Funds,” has found that short sellers are informed investors who are skilled at processing information. Those studies found that stocks with high shorting fees earn abnormally low returns even after accounting for the shorting fees earned from securities lending. Thus, loan fees provide information in the cross-section of equity returns.
Joseph Engelberg, Richard Evans, Gregory Leonard, Adam Reed and Matthew Ringgenberg contribute to the literature with their September 2020 study, “The Loan Fee Anomaly: A Short Seller’s Best Ideas.” They compared the loan fee to 102 anomalies. Their sample period was 2006-2019. Following is a summary of their findings:
- Among the 102 anomalies, equity loan fees are the strongest predictor of cross-sectional returns.
- While the median loan fee was only 36 basis points (bps) per annum, the mean loan fee was 103 bps per annum, and the 99th percentile was 1,367 bps per annum.
- Stocks with a daily cost of borrowing score (DCBS) of 1 had a mean (median) loan fee of 36 bps (27 bps) while stocks with a DCBS of 10 had a mean (median) loan fee of 5,278 bps (4,451 bps).
- When compared to 102 other anomalies, the loan fee anomaly had the highest monthly long-short return (1.17%), the highest monthly Sharpe Ratio (0.40), and the highest percentage of months with a positive return (68.3%).
- “On special” stocks (stocks with very high loan fees) constituted just over 10% of the equity universe and underperformed general collateral (GC) stocks by 0.91% per month.
- The outperformance of the loan fee anomaly over time is driven largely by the short side of the portfolio.
- The information contained in loan fees exhibited strong persistence throughout the sample. This is in contrast to the performance of many anomalies, which deteriorates post-publication.
- Twenty-eight percent of the loan fee anomaly could be explained by its selective exposure to the best performing anomalies, while 72% was due to unique information possessed by short sellers.
- The other 102 anomalies are almost exclusively in high loan-fee stocks. Among general collateral (GC) stocks (i.e., those that have low loan fees) the long-short trading strategy return for an aggregate anomaly portfolio was 0.25% monthly. Among non-GC stocks, it was 1.82% monthly.
- Idiosyncratic return volatility was highly positively correlated (R-squared value of 0.97) with loan fees, as was the bid-ask spread (reflecting illiquidity), while return on assets (ROA) was negatively correlated with the loan fees.
Their findings led the authors to conclude that short sellers have unique information not contained in existing anomalies – their “best ideas” outperform other anomalies.
The research on short selling has led some “passive” (systematic) money management firms (such as AQR, Bridgeway and Dimensional) to suspend purchases of small stocks that are “on special” (securities lending fees are very high). Dimensional has done extensive research on securities lending. Using securities lending data for 14 developed and emerging markets from 2011 to 2018, it found that stocks with high borrowing fees tend to underperform their peers over the short term. Moreover, stocks that remain expensive to borrow continue to underperform, but persistence of high borrowing fees is not systematically predictable. While the information in borrowing fees is fast decaying, it can still be efficiently incorporated into real-world equity portfolios.
Dimensional also found that while high borrowing fees are related to lower subsequent performance, it is not clear this information can be used to make a profit by selling short stocks with high fees. Borrowing fees are just one cost associated with shorting; short sellers must also post collateral, typically at least 100 percent of the value of borrowing securities, and incur transaction costs. In addition, its research shows that there is relatively high turnover in the group of stocks that are on loan with high borrowing fees. For example, fewer than half of high-fee stocks are still high-fee one year after being identified as such. Therefore, excluding these stocks may lead to high costs if buy and sell decisions are triggered by stocks frequently crossing the high-fee threshold. After considering the tradeoffs between expected return, revenue from lending activities, diversification, turnover and trading costs, Dimensional believes that an efficient approach to incorporate these findings into a real-world investment process is to consistently exclude from additional purchase small-cap stocks with high borrowing fees.
Avantis takes a different approach in designing its fund construction rules. It tries to avoid holding securities that tend to have characteristics associated with high lending revenues and shorting. AQR also uses the information in some of its portfolios – a high shorting fee is used as a signal to sell short the hard-to-borrow names, assuming AQR forecasts a positive expected return (net of the fee). It does so based on the academic evidence showing that high short-fee names are predictive of lower returns even net of their higher fee.
Finally, investors may benefit from the research findings without shorting stocks. They can do so by avoiding purchasing high-sentiment stocks where borrowing fees are “on special.”
Larry Swedroe is the chief research officer for Buckingham Strategic Wealth and Buckingham Strategic Partners.
Important Disclosures: This article is for educational and informational purposes only and should not be construed as specific investment, accounting, legal or tax advice. The analysis contained in this article is based upon third party information and may become outdated or superseded at any time without notice. Third-party information is deemed to be reliable, but its accuracy and completeness cannot be guaranteed. By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of Buckingham Strategic Wealth®. When constructing client portfolios, my firm recommends AQR, Bridgeway and Dimensional funds to clients. R-20-1479