Which Shorts Are Informed

By Ekkehart Boehmer, Charles M. Jones, Xiaoyan Zhang. 2008

886 citations recorded by the source corpus.

We construct a long daily panel of short sales using proprietary NYSE order data. From 2000 to 2004, shorting accounts for more than 12.9% of NYSE volume, sug- gesting that shorting constraints are not widespread. As a group, these short sellers are well informed. Heavily shorted stocks underperform lightly shorted stocks by a risk-adjusted average of 1.16% over the following 20 trading days (15.6% annualized). Institutional nonprogram short sales are the most informative; stocks heavily shorted by institutions underperform by 1.43% the next month (19.6% annualized). The re- sults indicate that, on average, short sellers are important contributors to efficient stock prices. THROUGHOUT THE FINANCIAL ECONOMICS LITERATURE, short sellers occupy an exalted place in the pantheon of investors as rational, informed market participants who act to keep prices in line. Theoreticians often generate a divergence be- tween prices and fundamentals by building models that prohibit or constrain short sellers (e.g., Miller (1977), Harrison and Kreps (1978), Duffie, Garleanu, and Pedersen (2002), Hong, Scheinkman, and Xiong (2006)). Empirical evidence uniformly indicates that when short sale constraints are relaxed, overvalua- tions become less severe, suggesting that short sellers move prices toward fun- damentals (examples include Lamont and Thaler (2003), Danielsen and Sorescu (2001), Jones and Lamont (2002), Cohen, Diether, and Malloy (2007)). But there is surprisingly little direct evidence that short sellers know what they are doing. There is indirect evidence in the existing literature. For example, Aitken et al. (1998) show that in Australia, where some short sales were immediately disclosed to the public, the reporting of a short sale causes prices to decline immediately. Some authors (but not all) find that short interest predicts fu- ture returns. 1 Dechow et al. (2001) find that short sellers generate positive

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/251496cc19fb15d0e8ff85edb119371bcbd55c81

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

  1. Matthew C. Ringgenberg
  2. David A. Hirshleifer
  3. Siew Hong Teoh
  4. Kenneth R. Ahern
  5. Hai-fan Lu
  6. Ekkehart Boehmer
  7. Joseph E. Engelberg
  8. Pedro A. C. Saffi

In Finance

  1. Matthew C. Ringgenberg
  2. David A. Hirshleifer
  3. Siew Hong Teoh
  4. Joseph E. Engelberg
  5. Ekkehart Boehmer
  6. Kenneth R. Ahern
  7. Hai-fan Lu
  8. Adam V. Reed

Citations in the corpus