The Journal of Finance

Why Does Stock Market Volatility Change Over Time?

Published: 12/01/1989   |   DOI: 10.1111/j.1540-6261.1989.tb02647.x

G. WILLIAM SCHWERT

This paper analyzes the relation of stock volatility with real and nominal macroeconomic volatility, economic activity, financial leverage, and stock trading activity using monthly data from 1857 to 1987. An important fact, previously noted by Officer (1973), is that stock return variability was unusually high during the 1929–1939 Great Depression. While aggregate leverage is significantly correlated with volatility, it explains a relatively small part of the movements in stock volatility. The amplitude of the fluctuations in aggregate stock volatility is difficult to explain using simple models of stock valuation, especially during the Great Depression.

Hostility in Takeovers: In the Eyes of the Beholder?

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00301

G. William Schwert

This paper examines whether hostile takeovers can be distinguished from friendly takeovers, empirically, based on accounting and stock performance data. Much has been made of this distinction in both the popular and the academic literature, where gains from hostile takeovers result from replacing incumbent managers and gains from friendly takeovers result from strategic synergies. Alternatively, hostility could reflect strategic choices made by the bidder or the target. Empirical tests show that most deals described as hostile in the press are not distinguishable from friendly deals in economic terms, except that hostile transactions involve publicity as part of the bargaining process.

The Adjustment of Stock Prices to Information About Inflation

Published: 03/01/1981   |   DOI: 10.1111/j.1540-6261.1981.tb03531.x

G. WILLIAM SCHWERT

This paper analyzes the reaction of stock prices to the new information about inflation. Based on daily returns to the Standard and Poor's composite portfolio from 1953–78, it seems that the stock market reacts negatively to the announcement of unexpected inflation in the Consumer Price Index (C.P.I.), although the magnitude of the reaction is small. It is interesting to note that the stock market seems to react at the time of announcement of the C.P.I., approximately one month after the price data are collected by the Bureau of Labor Statistics.

Stock Returns and Real Activity: A Century of Evidence

Published: 09/01/1990   |   DOI: 10.1111/j.1540-6261.1990.tb02434.x

G. WILLIAM SCHWERT

This paper analyzes the relation between real stock returns and real activity from 1889–1988. It replicates Fama's (1990) results for the 1953–1987 period using an additional 65 years of data. It also compares two measures of industrial production in the tests: (1) the series produced by Babson for 1889–1918, spliced with the Federal Reserve Board index of industrial production for 1919–1988, and (2) the new Miron and Romer (1989) index spliced with the Federal Reserve Board index in 1941. Fama's findings are robust for a much longer period—future production growth rates explain a large fraction of the variation in stock returns. The new Miron‐Romer measure of industrial production is less closely related to stock price movements than the older Babson and Federal Reserve Board measures.

IPO Market Cycles: Bubbles or Sequential Learning?

Published: 12/17/2002   |   DOI: 10.1111/1540-6261.00458

Michelle Lowry, G. William Schwert

Both IPO volume and average initial returns are highly autocorrelated. Further, more companies tend to go public following periods of high initial returns. However, we find that the level of average initial returns at the time of filing contains no information about that company's eventual underpricing. Both the cycles in initial returns and the lead‐lag relation between initial returns and IPO volume are predominantly driven by information learned during the registration period. More positive information results in higher initial returns and more companies filing IPOs soon thereafter.

Heteroskedasticity in Stock Returns

Published: 09/01/1990   |   DOI: 10.1111/j.1540-6261.1990.tb02430.x

G. WILLIAM SCHWERT, PAUL J. SEGUIN

We use predictions of aggregate stock return variances from daily data to estimate time‐varying monthly variances for size‐ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time‐varying betas. Implications of heteroskedasticity and time‐varying betas for tests of the capital asset pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that risk‐adjusted returns are related to firm size. We also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicted by more complex multivariate generalized‐autoregressive‐conditional‐heteroskedasticity (GARCH) procedures.

The Variability of IPO Initial Returns

Published: 03/19/2010   |   DOI: 10.1111/j.1540-6261.2009.01540.x

MICHELLE LOWRY, MICAH S. OFFICER, G. WILLIAM SCHWERT

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.

Joint Editorial

Published: 12/17/2002   |   DOI: 10.1111/1540-6261.00451