In the past, academic research has shown that stocks with high levels of short interest are connected with a high probability of experiencing negative abnormal returns subsequently. Therefore, the common sense implies that it should be possible to gain an advantage of the aforementioned stocks. The theory says that shorting stocks with all the constrain (connected with the shorting) is most often made by the informed investors whose activity ultimately helps prices incorporate more information. Moreover, the level of their holdings has predictive power about returns and fundamentals of the stocks. Knowing the short-interest can lead to a strategy that consists of simply joining informed short-sellers. The long-short variation (our screener also includes the long-only variant) of this strategy would be performed by the shorting stocks with high short interest and going long stocks with low short interest.
Overall, the academic world support this anomaly, for example, Asquith, Pathak, and Ritter in their work “Short Interest, Institutional Ownership, and Stock Returns“, say that “Stocks are short sale constrained when there is a strong demand to sell short and a limited supply of shares to borrow. Using data on both short interest, a proxy for demand, and institutional ownership, a proxy for supply, we find that constrained stocks underperform during 1988-2002 by a significant 215 basis points per month on an EW basis, although by only an insignificant 39 basis points per month on a VW basis. For the overwhelming majority of stocks, short interest and institutional ownership levels make short-selling constraints unlikely.” Additionally, the authors of this paper state that: “The cross-sectional relation between short interest and future stock returns vanishes when controlling for short-sellers’ information about future fundamental news. Thus, short-sellers contribute, in a significant manner, to price discovery about firm fundamentals.” Last but not least, this long-short strategy has a low correlation to the overall market, and therefore, the strategy can be used as a portfolio diversifier.
The literature offers two popular explanations for this predictability, namely the overvaluation hypothesis and the information hypothesis. The first possible explanation for the short interest effect – the overvaluation hypothesis stems from the work of Miller (1977). His theory says that stocks with high levels of short interest are overvalued because pessimistic investors are unable to establish short positions, leaving only the optimists to participate in the pricing process. In this model, market forces are unable to prevent overpricing in the amount of shorting costs when these costs are high. The greater the shorting costs, the greater the possible overpricing, and therefore, the lower the subsequent stock returns.
The second and probably more valid explanation is the information hypothesis. The information hypothesis builds on a broadening base of empirical research that demonstrates that short sellers are well-informed traders. Those mentioned above could be the reason for the functionality because if one follows the decisions of the short-sale practitioners, who tend to be investors with superior analytical skills (for example, according to the research of Gutfleish and Atzil, 2004). The main idea is simple; the research says, that these investors typically initiate short positions only if they can infer low fundamental valuation from public sources. For example, short-sellers may engage in forensic accounting, looking for high levels of accrual as evidence of hidden bad news. Still, there is a large number of other possibilities than just accruals.
Backtest period from source paper
Confidence in anomaly's validity
Notes to Confidence in Anomaly's Validity
OOS back-test shows slightly negative performance. It looks, that strategy’s alpha is deteriorating in the out-of-sample period.
Notes to Indicative Performance
per annum, annualized monthly return 1,51% (geometrically), data from table 3, around 22.70% pure alpha based on four factor model (market, size, book, momentum)
Period of Rebalancing
Notes to Period of Rebalancing
Notes to Estimated Volatility
estimated from t-statistics, data from table 3
Number of Traded Instruments
Notes to Number of Traded Instruments
it depends on investor’s need for diversification (usually 100-1000)
Notes to Maximum drawdown
Moderately complex strategy
Notes to Complexity Evaluation
Simple trading strategy
All stocks from NYSE, AMEX, and NASDAQ are part of the investment universe. Stocks are then sorted each month into short-interest deciles based on the ratio of short interest to shares outstanding. The investor then goes long on the decile with the lowest short ratio and short on the decile with the highest short ratio. The portfolio is rebalanced monthly, and stocks in the portfolio are weighted equally.
Hedge for stocks during bear markets
Not known - Source and related research papers don’t offer insight into the correlation structure of the proposed trading strategy to equity market risk; therefore, we do not know if this strategy can be used as a hedge/diversification during the time of market crisis. The strategy is built as a long-short, but it can be split into two parts. The long leg of the strategy is surely strongly correlated to the equity market; however, the short-only leg can be maybe used as a hedge during bad times. Rigorous backtest is, however, needed to determine return/risk characteristics and correlation.
Out-of-sample strategy's implementation/validation in QuantConnect's framework