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To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1540-6261.2009.01548.x Byline: MICHAEL J. COOPER, HUSEYIN GULEN, ALEXEI V. OVTCHINNIKOV (*) Abstract: ABSTRACT We develop a new and comprehensive database of firm-level contributions to U.S. political campaigns from 1979 to 2004. We construct variables that measure the extent of firm support for candidates. We find that these measures are positively and significantly correlated with the cross-section of future returns. The effect is strongest for firms that support a greater number of candidates that hold office in the same state that the firm is based. In addition, there are stronger effects for firms whose contributions are slanted toward House candidates and Democrats. Article note: (*) Cooper is with the David Eccles School of Business, The University of Utah. Gulen is with the Krannert School of Management, Purdue University. Ovtchinnikov is with the Owen Graduate School of Management, Vanderbilt University. Ovtchinnikov gratefully acknowledges financial support from the 2006 Pamplin Summer Research Grant and the Financial Markets Research Center. We thank Julian Atanassov, Hank Bessembinder, Al Carrion, John Chalmers, Mike Cliff, Don Cooper, Doug Eckel, Mara Faccio, Laura Frieder, Roberto Gutierrez, E. Han Kim, Madhuparna Kolay, Michael Lemmon, Uri Loewenstein, Jennifer McConnell, John McConnell, Wayne Mikkelson, Mike Munger, Raghu Rau, Jonathan Reuter, Scott Schaefer, Jim Snyder, Thomas Stratmann, two anonymous referees, the Editor (Cam Harvey), and seminar participants at Brigham Young University, Goldman Sachs, University of Oregon, The Q-Group fall seminar, and Vanderbilt University for their helpful comments. We thank Gokhan Sonaer for research assistant work.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1540-6261.2008.01370.x Byline: MICHAEL J. COOPER, HUSEYIN GULEN, MICHAEL J. SCHILL (*) Abstract: ABSTRACT We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. Asset growth rates are strong predictors of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm's annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns. Article note: (*) Cooper is with the David Eccles School of Business, The University of Utah. Gulen is with the Krannert Graduate School of Management, Purdue University. Schill is with the University of Virginia - Darden Graduate School of Business Administration. We thank Mike Cliff, Kent Daniel, Naveen Daniel, David Denis, John Easterwood, Wayne Ferson, John Griffin, Ro Gutierrez, Michael Lemmon, Laura Xiaolei Liu, Elena Loutskina, Bill Maxwell, John McConnell, Grant McQueen, Raghu Rau, Jacob Sagi, Paul Simko, Jeff Wurgler, an anonymous referee, the editor (Rob Stambaugh), and seminar participants at BYU, Indiana University, ISCTE, Michigan State University, Purdue University, University of Michigan, University of Porto, University of Virginia, Virginia Tech, and meetings of the American Finance Association, CRSP Forum, and the Financial Management Association for their helpful comments. We thank Dave Ikenberry for providing us with data used in Ikenberry, Lakonishok, and Vermaelen (1995). This paper was previously titled 'What best explains the cross-section of stock returns? Exploring the asset growth effect.'

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jfineco.2006.03.001 Byline: Michael J. Cooper (a)(b), John J. McConnell (c), Alexei V. Ovtchinnikov (d) Keywords: January barometer; Return seasonalities; Asset pricing; Market returns Abstract: Streetlore since at least 1973 has touted the market return in January as a predictor of market returns for the remainder of the year. We systematically examine the predictive power of January returns over the period 1940-2003 and find that January returns have predictive power for market returns over the next 11 months of the year. The effect persists after controlling for macroeconomic/business cycle variables that have been shown to predict stock returns, the Presidential Cycle in returns, and investor sentiment, and it persists among both large and small capitalization stocks and among both value and growth stocks. In addition, we find that January has predictive power for two of the three premiums in the Fama-French [1993. Journal of Financial Economics 33, 3-50] three-factor model of asset pricing. Author Affiliation: (a) David Eccles School of Business, University of Utah, 1645 E. Campus Center Dr., Salt Lake City, UT 84112, USA (b) Krannert Graduate School of Management, Purdue University (c) Krannert Graduate School of Management, Purdue University, 403 W. State St., West Lafayette, IN 47907-2056, USA (d) Department of Finance, Insurance, and Business Law, Virginia Polytechnic Institute & State University, Blacksburg, VA 24060 USA Article History: Received 13 June 2005; Revised 9 October 2005; Accepted 14 March 2006 Article Note: (footnote) [star] We thank Steve Buser, Mike Cliff, Kent Daniel, Dave Denis, Eugene Fama, Ken French, Russ Fuller, Toby Moskowitz, Raghu Rau, Bill Schwert (the editor), Hassan Tehranian, Jaime Zender, an anonymous referee, and seminar participants at Boston College, the University of Colorado, Penn State University, Deloitte & Touche, Goldman Sachs Asset Management, and the Wharton School of the University of Pennsylvania for their comments. We thank Mike Lemmon for providing us with the data used in and Jeff Wurgler for providing us with the data used in .

The effects of mutual fund name changes on its cash flows are analyzed.

A paper elucidating the positive effect of corporate name changes on the stocks of Internet-related firms is presented. Research results reveal a 74% spike in abnormal returns for the 10 days surrounding a dot.com name change.

Previous work shows large differences in fees for S&P 500 index funds and other funds and suggests that investors suffer wealth losses investing in high-fee funds when similar low-fee funds are available. In contrast, the neoclassical model of mutual funds (Berk and van Binsbergen, 2015 , J. Financ. Econ. 118, 1–20) argues that percentage fees are irrelevant, as fund size will adjust in equilibrium such that net alphas are equal to zero. We show that fees matter from an investor perspective. We document (i) a strong negative association between net-of-fee fund performance and fees in a sample of all US and international equity funds, (ii) economically large, robust, persistent, and pervasive fee dispersion in the mutual fund industry, and (iii) important economic effects for investors. During the sample period, the mutual fund industry has generated a total value lost (i.e. a negative net value added) of 125 billion USD, coming predominantly from high-fee funds. [ABSTRACT FROM AUTHOR]

Background Antibodies that inhibit hemagglutination have long been considered a correlate of protection against influenza, but these antibodies are only a subset of potentially protective antibodies. Neutralizing and neuraminidase antibodies may also contribute to protection, but data on their associations with protection are limited. Methods We measured preoutbreak hemagglutinin pseudovirus neutralization (PVN) and neuraminidase inhibition (NAI) antibody titers in unvaccinated military recruits who experienced an H3N2 influenza outbreak during training. We conducted a case-control study to investigate the association between titers and protection against influenza illness or H3N2-associated pneumonia using logistic regression. Results With every 2-fold increase in PVN titer, the odds of medically attended polymerase chain reaction–confirmed H3N2 infection (H3N2+) decreased by 41% (odds ratio [OR], 0.59; 95% confidence interval [CI],.45 to.77; P <.001). Among those who were H3N2+, the odds for pneumonia decreased by 52% (OR, 0.48; CI,.25 to.91; P =.0249). With every 2-fold increase in NAI titer, the odds of medically attended H3N2 infection decreased by 32% (OR, 0.68; 95% CI,.53 to.87; P =.0028), but there was no association between NAI titers and H3N2-associated pneumonia. There was also no synergistic effect of PVN and NAI antibodies. Conclusions PVN and NAI titers were independently associated with reduced risk of influenza illness. NAI titers associated with protection had greater breadth of reactivity to drifted strains than PVN titers. These findings show that PVN and NAI titers are valuable biomarkers for assessing the odds of influenza infection. [ABSTRACT FROM AUTHOR]

We test overreaction theories of short-run momentum and long-run reversal in the cross section of stock returns. Momentum profits depend on the state of the market, as predicted. From 1929 to 1995, the mean monthly momentum profit following positive market returns is 0.93%, whereas the mean profit following negative market returns is −0.37%. The up-market momentum reverses in the long-run. Our results are robust to the conditioning information in macroeconomic factors. Moreover, we find that macroeconomic factors are unable to explain momentum profits after simple methodological adjustments to take account of microstructure concerns. [ABSTRACT FROM AUTHOR]