Complicated Firms

Lauren  Cohen; Dong  Lou

Article | Journal of Financial Economics | May 2012

Complicated Firms

Abstract

We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyze firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyze firms predict their future revisions of more complicated firms.

Keywords: Investment Portfolio; Information; Price; Forecasting and Prediction; Complexity; Mathematical Methods;

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Cohen, Lauren, and Dong Lou. "Complicated Firms." Journal of Financial Economics 104, no. 2 (May 2012). (Winner of Istanbul Stock Exchange 25th Anniversary Best Paper Competition. First Prize presented by Istanbul Stock Exchange. Winner of Center for Research in Security Prices Forum. Best Paper Prize presented by University of Chicago Booth School of Business. Winner of Paul Woolley Centre for the Study of Capital Market Dysfunctionality. Academic Grant presented by Paul Woolley Centre for the Study of Capital Market Dysfunctionality. Winner of Crowell Memorial Prize For the best paper on quantitative investing presented by PanAgora Asset Management, Inc.)

Article | Journal of Finance | June 2020

Lazy Prices

Lauren Cohen, Christopher J. Malloy and Quoc Nguyen

We explore the implications of a subtle "default" choice that firms make in their regular reporting practices, namely that firms typically repeat what they most recently reported. Using the complete history of regular quarterly and annual filings by U.S. corporations from 1995 to 2014, we show that when firms make an active change in their reporting practices, this conveys an important signal about the firm. Changes to the language and construction of financial reports have strong implications for firms' future returns: a portfolio that shorts "changers" and buys "non-changers" earns up to 188 basis points per month (over 22% per year) in abnormal returns in the future. These reporting changes are concentrated in the management discussion (MD&A) section. Changes in language referring to the executive (CEO and CFO) team, or regarding litigation, are especially informative for future returns.

Keywords: information; default behavior; inertia; firms; annual reports; disclosure; Information; Business or Company Management; Behavior; Corporate Disclosure; Financial Reporting; United States;

Citation:

Cohen, Lauren, Christopher J. Malloy, and Quoc Nguyen. "Lazy Prices." Journal of Finance 75, no. 3 (June 2020): 1371–1415. (Winner of the First Prize, Chicago Quantitative Alliance Academic Paper Competition, 2016. Winner of the Jack Treynor Prize for superior work in the field of investment management and financial markets, sponsored by the Q-Group,The Institute for Quantitative Research in Finance, 2016. Winner of the Hillcrest Behavioral Finance Prize, 2016.) View Details

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Three years ago, Alvin Ang and his partner founded fidentiaX in Singapore, with the ambition to create the world’s first marketplace for tradable insurance policies on blockchain. With a 26-page white paper, the start-up closed a successful fundraising round through an initial coin offering (ICO). Three years later, however, the company still had not completed the infrastructure for the insurance trading platform. Besides the rapidly dwindling funds, fidentiaX had to fight with a tardy development team, uncooperative incumbent insurers, and begrudging investors. The case provides an overview of the blockchain industry and insights into the secondary life insurance market. Through the case, students will assess the company’s business strategies and learn about typical challenges faced by technology start-ups.

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