Lily H. Fang

Media Coverage and the Cross-Section of Stock Returns

By reaching a broad population of investors, mass media can alleviate informational frictions and affect security pricing even if it does not supply genuine news. We investigate this hypothesis by studying the cross-sectional relation between media coverage and expected stock returns. We find that stocks with no media coverage earn higher returns than stocks with high media coverage even after controlling for well-known risk factors. These results are more pronounced among small stocks and stocks with high individual ownership, low analyst following, and high idiosyncratic volatility. Our findings suggest that the breadth of information dissemination affects stock returns. MASS MEDIA OUTLETS, such as newspapers, play an important role in disseminating information to a broad audience, especially to individual investors. Every weekday, some 55 million newspaper copies are sold to individual readers in the United States, reaching about 20% of the nation’s population. If we consider online subscriptions and multiple readers per copy, the actual readership of the printed press is even larger, and certainly far broader than other sources of corporate information such as analyst reports. Given mass media’s broad reach, one might expect it to affect securities markets. Interest in the relation between media and the market has been on the rise among both researchers and practitioners. Klibanoff, Lamont, and Wizman (1998), Tetlock (2007), and Tetlock, Saar-Tsechansky, and Macskassy (2008) are examples of this growing literature.1 We contribute to this strand of research by examining the cross-sectional relation between mass media coverage and stock returns. We find that stocks not covered by the media earn significantly higher future returns than stocks that are heavily covered, even after accounting for widely accepted risk characteristics. A portfolio of stocks with no media coverage outperforms a portfolio of ∗Lily Fang and Joel Peress are both at INSEAD. We would like to thank Bernard Dumas, Edward Fang, Harald Hau, Pierre Hillion, Harrison Hong, Soeren Hvidkjaer, Charles Jones, Massimo Massa, Steve Monahan, Paul Tetlock, Clara Vega, Kent Womack, Lu Zheng, and seminar participants at Imperial College London, INSEAD, Lehman Brothers, Numeric Investors LLC, University of Wisconsin Madison, and Singapore International Conference on Finance (2007) for helpful comments and discussions. We are also grateful to an anonymous referee and Campbell Harvey (the editor) for many insightful comments and detailed suggestions. We thank William Fisk, Shirish Tatikonda, Pradeed Mittal, Ananda Kumar, Sriram Ganesan, and Sriram Subramaniam for outstanding assistance with the data collection process. 1 A detailed literature review appears in Section I.

Intellectual Property Rights Protection, Ownership, and Innovation: Evidence from China

Using a difference-in-difference approach, we study how intellectual property right (IPR) protection affects innovation in China in the years around the privatizations of state-owned enterprises (SOEs). Innovation increases after SOE privatizations, and this increase is larger in cities with strong IPR protection. Our results support theoretical arguments that IPR protection strengthens firms’ incentives to innovate and that private sector firms are more sensitive to IPR protection than SOEs.

Uncertainty, Skill, and Analysts' Dynamic Forecasting Behavior

We study the risk-taking behavior of stock analysts under varying market conditions. We examine how the risk analysts take by providing bold forecasts that deviate from consensus depends on the degree of uncertainty in the environment as well as the analysts’ skill level. We provide evidence that low-skill analysts become significantly bolder, hence taking more risk, and significantly less accurate when market uncertainty increases. These findings are consistent with previous experimental results that show that skill levels moderate differential attitudes towards uncertainty. We further provide evidence that the difference in an analyst’s boldness between times of low and high uncertainty is a signal of the analyst’s skill that predicts future forecasting accuracy over and above standard skill measures such as past forecasting accuracy.

Inattention as a Limit to Arbitrage: Evidence from School Holidays

Globally, market returns are 0.5% to 1% lower in the month after major school holidays than other times. The same seasonality is not observed in either macroeconomic variables or the corporate earnings news. During holidays, abnormal institutional buys, sells, and short selling around earnings announcements are 8%, 14%, and 18% lower than other times, and institutional trades account for a smaller percentage of total market volume. Market response to negative news is delayed. Our evidence suggests that the low after-holiday returns are attributable to the market being collectively less attentive during holidays, and (negative) news is slowly incorporated into prices.