ACADEMIC
EMPLOYMENT
EDUCATION
PUBLICATIONS
We show that stock prices are more accurate when short sellers are more active. First, in a large panel of NYSE-listed stocks, intraday informational efficiency of prices improves with greater shorting flow. Second, at monthly and annual horizons, more shorting flow accelerates the incorporation of public information into prices. Third, greater shorting flow reduces post-earnings announcement drift for negative earnings surprises. Fourth, short sellers change their trading around extreme return events in a way that aids price discovery and reduces divergence from fundamental values. These results are robust to various econometric specifications and their magnitude is economically meaningful.
WORKING PAPERS
We
use a large sample from 2001-2009 that incorporates 39
exchanges and an average of 12,800 different common stocks to
assess the effect of algorithmic trading (AT) intensity on
liquidity in the equity market, short-term volatility, and the
informational efficiency of stock prices. We exploit the first
availability of co-location facilities to identify the
direction of causality. We find that, on average, greater AT
intensity improves liquidity and informational efficiency, but
increases volatility. The volatility increase is robust to a
range of different volatility measures and it is not due to
more "good" volatility that would arise from faster price
discovery. These patterns are widespread and are not limited
to a few markets, but they vary in the cross-section of
stocks. In contrast to the average effect, more AT reduces
liquidity in small stocks; has little effect on the liquidity
of low-priced or high-volatility stocks; and leads to greater
increases in volatility in these stocks. Finally, during days
when market making is difficult, AT provide less liquidity,
improve efficiency more, and increase volatility more than on
other days
Management frequently attributes earnings news to various economic events. Using textual analysis, we identify the economic factors underlying earnings news from press releases. We find that earnings news in management forecasts is attributed to a wide range of industry-wide shocks and firm-specific actions.
As expected, earnings attributions significantly affect peer firms' price reactions to the earnings news. Specifically, earnings news attributed to industry-wide trends or firm structural changes leads to positive information transfers but news attributed to firm competitive moves triggers negative information transfers. The strength of information transfers depends on firm-level rivalry within the industry, the nature of industry-level competition, and the credibility of earnings attributions.
In
the month preceding a credit rating downgrade, equity short
interest is 40% higher than one year prior and short selling
returns to normal levels following a downgrade. Short interest
is higher for downgrades with higher negative equity
announcement returns and for more severe downgrades (e.g., to
speculative grade). Short selling also facilitates price
discovery in equity markets around rating downgrades. Abnormal
returns following downgrades are smaller when short selling is
higher prior to the downgrade and when the costs of short
selling are smaller. Short selling also increases before bond
prices anticipate the downgrade.
We propose a risk-based explanation on why stocks of firms with high relative short interest (RSI) have lower future returns. We argue that these firms have negative alphas because they are a hedge against expected aggregate volatility. Consistent with this argument, we show that these firms have high firm-specific uncertainty and real options, and the ICAPM with the aggregate volatility risk factor can explain the high RSI effect. The key mechanism is that high RSI firms have abundant growth options and, all else equal, growth options become less sensitive to the underlying asset value and more valuable as idiosyncratic volatility goes up. Idiosyncratic volatility usually increases together with aggregate volatility, i.e., in recessions.
We
provide new evidence on the relation between order flow and
prices, an issue that is central to asset pricing and market
microstructure. We examine proprietary data on a broad panel
of NYSE-listed stocks that reveal daily order imbalances by
institutions, individuals, and market makers. We can further
differentiate regular institutional trades from institutional
program trades. Our results indicate that order imbalances
from different trader types play distinctly different roles in
price formation. Institutions and individuals are contrarians
with respect to previous-day returns, but differ in the effect
their order imbalances have on contemporaneous returns.
Institutional imbalances are positively related to
contemporaneous returns, and we provide cross-sectional
evidence that this relation is likely to be the result of
firm-specific information institutions have. Individuals,
specialists, and other market makers appear to provide
liquidity to these actively trading institutions. Our results
also suggest a special role for institutional program trades,
which tend to be uninformed and provide liquidity to more
aggressively trading institutions. Finally, institutional
non-program imbalances (information which is not available to
market participants) have predictive power for next-day
returns.
We examine how equity short sellers form trading strategies when faced with an increasing "crowded-trade" effect (Stein 2009) over time in the context of a broad range of well-known asset pricing anomalies. We find that short selling has increased over time, with more increase on the short side of each anomaly. Overpricing on the short side of these anomalies has disappeared in recent years in firms with less-binding constraint. Short sellers' trading on crowded signals based on these known anomalies largely explains the negative relation between short interest and returns in the early sample period of 1988-1999, but only explains part of this relation in more recent period of 2000-2011, suggesting that over time short sellers have become more sophisticated in trading on less-crowded signals independent of these known anomalies. Investors who trade on both anomaly and short interest signals are better off than only trading on the anomaly signal.
This paper extends Mitchell, Pulvino and Stafford (2004) by studying merger arbitrage short selling using daily shorting flow data in a more recent period. We show that short selling increases significantly at merger announcements for acquirers in stock-financed mergers, and over 60 percent of the negative returns can be attributed to merger arbitrage short selling. Merger arbitrageurs' daily short position in the acquirer stock is positively related to the estimated arbitrage spread. Heightened arbitrage shorting and price declines in acquirers are also observed near the end of the pricing period for floating-exchange-ratio stock mergers. After the deals are closed, short selling reverses to its pre-announcement level. These findings suggest that merger arbitrageurs play an increasingly critical role in capital markets and their trading behavior can have important implications for the estimates of wealth effects associated with mergers.
PAPER
PRESENTATIONS AT PROFESSIONAL MEETINGS
- 2013
- American Finance Association, San Diego
- "International Evidence on Algorithmic Trading"
- 2012
-
Bachelier conference, Paris
- "International evidence on algorithmic trading"
-
American Accounting Association, Washington D.C
- "Earnings Attribution and Information Transfers"
-
Financial Management Association, Atlanta
- "High short interest effect and aggregate volatility risk"
- World Finance Conference, Brazil
- "High
short interest effect and aggregate volatility
risk"
- Midwest Finance Association, New Orleans
- "High short interest effect and aggregate volatility risk" *
- 2011
- 3rd
RMA/UNC Academic
Forum for Securities Lending Research, New
York
- "Do equity
short sellers anticipate bond rating
downgrades?"
- Southern
Finance Association, Key
West
- "High
short interest effect and aggregate volatility
risk"
- Financial
Management Association, Denver
- "Cash flow
volatility and firm valuation" *
- "How are
shorts informed: evidence from market anomalies"
- 2010
- Singapore
Management University Accounting Symposium,
Singapore
- "Industry
news, firm news, and information transfer from
management earnings forecasts"
- 2009
- 1st
RMA/UNC Academic
Forum for Securities Lending Research, New
York
- "Short
selling and the informational efficiency of
prices"
- All Georgia
Finance Conference, Atlanta
- "Short
selling and the informational efficiency of
prices"
- 2007
- American Finance
Association, Chicago
- Financial
Management Association Doctoral Consortium,
Orlando
- "Short
selling and the informational efficiency of
prices"
- Q-Group
Fall meeting, Scottsdale
- 2006
- Workshop on the Microstructure of Foreign Exchange and Equity Markets, Ottawa
TEACHING
EXPERIENCE
- University of
Georgia
- 2011-2012, Research Topics in Finance (PhD)
- 2008-2012, Corporate Finance Theory (Undergrad)
- Texas A&M
University
- 2007, Boot
Camp for Incoming Finance PhD Students (PhD)
- 2004, 2006,
Managerial Finance I (Undergrad)
- Xian Foreign Language University
- 1997-1999,
English courses
PROFESSIONAL
ACTIVITIES
Journal
of Finance
Review
of Financial Studies
Management Science
Journal
of Empirical Finance
Journal
of Corporate Finance
Journal of Financial Intermediation
Financial
Management
Financial Review
Pacific-Basin
Finance Journal
Review of
Financial Economic
International Journal of
Managerial Finance
- Discussant,
National Bureau of Economic Research (NBER) Microstructure
meeting, May 2008
- Program
Committee (Investment Track), Midwest Finance Association,
2008
- External
grant proposal reviewer for the Research Grants Council of
Hong Kong, 2012
- Discussant, Financial Management Association, 2012
HONORS
AND AWARDS
- 2007,
Post-Doctoral Research Associate Fellowship, Mays Business
School, Texas A&M University
- 2007,
American Finance Association Travel Award
- 2007,
Dean's Award for Outstanding Research by a Doctoral Student,
Mays Business School, Texas A&M University
- 2005,
Dean's Award for Outstanding Teaching by a Doctoral Student,
Mays Business School, Texas A&M University
