Can Shorts Predict Returns? A Global Perspective, a paper co-authored by our school’s Assistant Prof. Zhang Xinran, Prof. Zhang Xiaoyan from Tsinghua University, Prof. Ekkehart Boehmer from Singapore Management University, Prof. Zsuzsa R. Huszár from the National University of Singapore, and Prof. Wang Yanchu from Shanghai University of Finance and Economics, was officially accepted by Review of Financial Studies, a world-class journal on finance, and pending publication.
Short sellers play an important role in preventing the formation of price bubbles, and promoting price discovery in stock markets. In the past twenty years, the share of short selling in the US stock market has risen substantially. Take the New York Stock Exchange for example, the share of short selling was less than 10% before 2000, but increased to 20% in 2003 and then reached around 40% in 2008. Research on the US stock market shows that high volume of short selling predicts future negative stock returns, and that short sellers can boost share price efficiency due to their information advantage. Existing studies have also analyzed in detail the US regulators’ adjustment to regulatory policies on short selling.
However, unlike the US market which has a mature mechanism for short selling, short sales are restricted in many markets across the world. For instance, it is difficult to borrow securities required for short selling; and short sellers may face high transaction costs. Therefore, are the US short selling mechanism and regulatory experience applicable to other markets? Can short sellers still predict price changes in other markets? What influence will the regulatory mechanism and development degree of different markets, and the shorting cost, liquidity and price efficiency of different stocks have on short sellers?
To address these questions, the authors construct a variety of shorting activity indicators to predict future changes in stock returns by collecting data about short sales trading volume, shorting costs, and loan supply (among others) in 38 stock markets worldwide (including the US market). The authors find that Days-to-Cover and Utilization have a robust ability to negatively predict future stock returns in global markets. Of which, Days-to-Cover means the number of trading days needed to cover all the shares short sold so far based on the average trading volume per day; Utilization means the share of stocks short sellers borrow and short in all stocks available for lending. The higher the two ratios, the higher degree of short selling.
Furthermore, this paper analyzes the predictive power of short sellers in terms of differences in regulatory policy and development degree at the market level, as well as in shorting cost, liquidity and price efficiency at the individual stock level: Firstly, at the market level, the 38 stock markets have developed to varying degrees, with visible differences in regulatory provisions for short selling. Regulators of most markets imposed adequate restrictions on short selling through the uptick rule and the naked short-sale ban. These policies have duly raised the shorting cost, and pushed up the negative predictive power of short selling and returns of short sellers. Secondly, at the individual stock level, lower shorting costs make large numbers of uninformed traders engage in short selling, hence reducing the returns of short sellers; meanwhile, if stock liquidity and price efficiency increase, information will be quickly reflected in share prices, resulting in lower returns of short sellers.
Finally, this paper investigates the effect of changes in the short selling environment on shorting activities by assuming that the MSCI ACWI index (MSCI All Country World Index) inclusions and exclusions are exogenous shocks. If a stock is included in the MSCI, its price efficiency rises; if it is excluded from the MSCI, the shorting fees rise and its price efficiency drops. As the shorting cost in developed countries is relatively low, a stock’s inclusion into or exclusion from the MSCI does not generate notable impact on activities shorting it. However, the shorting cost in emerging markets is very high. If a stock of a developing country is included into the MSCI, its shorting cost falls from very high to a medium level, the negative predictive power of short selling will rise notably with the returns of short sellers going up as well. Otherwise, if a stock of a developing country is excluded from the MSCI, its shorting cost increases from medium to a very high level, the negative predictive power of short selling will drop evidently with the returns of short sellers falling as well.
Overall, the findings of this paper suggest that there is no “one-size-fits-all” solution for shorting regulation; regulators in different markets should take into account factors such as market development degree, information environment and investor structure prior to decision making.