THE JOURNAL OF FINANCE • VOL. LXV, NO. 2 • APRIL 2010
The Variability of IPO Initial Returns
MICHELLE LOWRY, MICAH S. OFFICER, and G. WILLIAM SCHWERT∗
ABSTRACT
The monthly volatility of IPO initial returns is substantial, fluctuates dramatically
over time, and is considerably larger during “hot” IPO markets. Consistent with IPO
theory, the volatility of initial returns is higher for firms that are more difficult to
value because of higher information asymmetry. Our findings highlight underwriters’
difficulty in valuing companies characterized by high uncertainty, and raise serious
questions about the efficacy of the traditional firm-commitment IPO process. One
implication of our results is that alternate mechanisms, such as auctions, could be
beneficial for firms that value price discovery over the auxiliary services provided by
underwriters.
INITIAL PUBLIC OFFERINGS (IPOS) are underpriced on average: The secondary
market trading price of a stock is on average much higher than its IPO price.
A number of academic papers note that the equity in private companies with
uncertain prospects is inherently difficult to value, and they posit that under-
pricing is an efficient response to the complexity of this valuation problem.1 In
contrast, others have questioned whether the IPO price-setting process results
in excess underpricing of IPO stocks.
This article proposes a new metric for evaluating the pricing of IPOs in tradi-
tional firm-commitment offerings: the volatility of initial returns to IPO stocks.
We find that there is considerable volatility in initial returns. To the extent that
the IPO price is a forecast of the secondary market price for the stock, these
forecasts are not only biased downward (underpricing), but the range of the
∗Michelle Lowry is from Penn State University. Micah S. Officer is from Loyola Marymount
University. G. William Schwert is from the University of Rochester and NBER. We are indebted
to Jay Ritter for the use of his data. We received valuable comments from Campbell Harvey
(Editor), Harry DeAngelo, Craig Dunbar, Robert Engle, Laura Field, Ravi Jagannathan, Jay Ritter,
Ann Sherman, Ivo Welch, Donghang Zhang, Jerry Zimmerman, and two anonymous referees. We
also received valuable comments from the participants in seminars at Boston College, Indiana
University, New York University, Penn State University, the University of Arizona, the University
of Rochester, the University of Southern California, the University of Toronto, and the University
of Western Ontario, and from participants at the Duke-UNC Corporate Finance Conference and
at the Harvard Business School Entrepreneurship, Venture Capital and Initial Public Offerings
Conference. Much of the work for this project was completed while Officer was on the faculty at
the Marshall School of Business at USC. The views expressed herein are those of the authors and
do not necessarily reflect the views of the National Bureau of Economic Research.
1See, for example, Rock (1986), Beatty and Ritter (1986), Welch (1992), and Benveniste and
Spindt (1989), among others.
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forecast (or pricing) errors is huge. While underpricing2 averages 22% between
1965 and 2005, a relatively small portion of offerings have underpricing that
is close to this average: Only about 5% of the initial returns are between 20%
and 25%. Moreover, nearly one-third of the initial returns are negative. The
standard deviation of these initial returns over the 1965 to 2005 period is
55%.
If one considers IPO initial return volatility to be a proxy for the difficulty
of pricing IPOs, then one could reasonably expect this volatility to change over
time with changes in the complexity of the pricing problem. Consistent with
this intuition, we find that the volatility of initial returns fluctuates greatly over
time. While prior literature shows the existence of hot IPO markets character-
ized by extremely high initial returns (see, for example, Ibbotson, Sindelar,
and Ritter (1988, 1994)), we find that these hot markets are also characterized
by extraordinarily high variability of initial returns. That is, there is a strong
positive correlation between the mean and the volatility of initial returns over
time.
These descriptive statistics suggest that the level of uncertainty surround-
ing IPO firms, and correspondingly, underwriters’ ability to value these firms,
varies over time. The pricing of an IPO is a complex process. Although the
issuer and its investment bank know considerably more about the firm’s own
prospects than any single market participant does, market participants as a
whole know more than the firm about one critical input in the IPO pricing pro-
cess: the aggregate demand for the firm’s shares (see, for example, Rock (1986)).
Aggregate demand uncertainty is one of the principal problems facing issuers
and their investment banks when attempting to price an IPO. By definition,
the initiation of trading resolves this information asymmetry between the issu-
ing firm and the market; that is, trading resolves the firm’s uncertainty about
the market’s aggregate demand. At this point, the information of all market
participants becomes incorporated into the price.
Uncertainty about aggregate demand for IPO stocks varies in both the time
series (it is higher at some points in time than others) and the cross section
(it is higher for some types of firms than others). To understand these effects,
we examine both variation in the types of firms going public and variation in
market-wide conditions.
To the extent that the complexity of the pricing problem is greater for cer-
tain types of firms than others, one would expect greater pricing errors when
the sample of firms going public contains a larger fraction of highly uncertain
firms. A number of theories support this intuition and predict that an invest-
ment bank’s pricing of an offering should be related to the level of information
asymmetry surrounding the company. For example, Beatty and Ritter’s (1986)
extension of Rock (1986) predicts that companies characterized by higher infor-
mation asymmetry will tend to be more underpriced on average, a prediction
2As discussed in more detail later, to avoid the effects of price support we measure initial returns
as the percent change from the offer price to the closing price on the 21st day of trading.