Despite the benefits of greater transparency, public disclosures may reveal proprietary information that ultimately harms the disclosing firm by allowing competitors to view and imitate its strategies, an activity known as “copycatting.” An SEC proposal in July 2020 to increase the reporting threshold for the quarterly 13F holdings of investment companies from $100 million to $3.5 billion was partly aimed at reducing the costs from copycatting. Although prior studies have shown how proprietary costs and competition shape the decisions of disclosing firms (e.g., Leuz and Wysocki, 2016), copycatting by peers remains relatively unexplored, mainly because such behavior is so difficult to see directly.
In a recent paper, we investigate whether and when copycats profit from imitating peer companies and under what conditions they harm those companies. We focus on the granular data on the SEC EDGAR website, which allow us to identify both copycats and copycatted companies. The website provides electronic access to all public companies’ filings to the SEC and is thus an authoritative source for investors. The SEC maintains the information retrieval records for all filings through the EDGAR Log File, which enables us to track copycatting.
For three reasons, we focus on investment companies whose operational decisions (i.e., changes in holdings) are disclosed through mandatory quarterly 13F filings. First, unlike industrial companies, whose disclosed strategies (e.g., business expansion plans) tend to be unstructured and difficult to analyze, investment companies disclose trading strategies that can be easily quantified and linked to the subsequent actions of copycats. Second, academic studies have documented that trades disclosed in 13F filings contain proprietary information. Third, this focus allows us to quantify the benefits to companies of copycatting by calculating the performance of copycatted trades.
Our research differentiates between copycatted trades and coincidental trades, i.e., correlated trades based on information sources other than peer companies’ 13F filings. To draw such a distinction, we consider the treatment group of companies that view peers’ 13F disclosures on EDGAR and the control group of companies that do not view peers’ 13F disclosures but may still execute coincidental trades. The trade correlation for the treatment group is about 22.3 percent higher than for the control group, offering strong evidence of copycatting.
We investigate whether copycats can discern useful information from peer companies’ voluminous disclosures. We first document that copycatted stock positions outperform other trades disclosed by the copycatted companies. The risk-adjusted return difference, 5.5 percent annually, is economically and statistically significant. We then explore the sources of copycats’ stock-screening skills and find that the performance of copycatted trades increases with sophistication and research intensity (the number of times a copycat retrieves other periodic financial statements including forms 10-K and 10-Q). The evidence suggests that, contrary to conventional wisdom, copycatting is not a naive mimicking of disclosed strategies. Instead, it requires effort and resources to collect data from peer disclosures and isolate valuable information.
Copycats can impose significant costs on disclosing companies by front-running their disclosed trades. When a disclosing company builds its positions over several quarters, copycats that track its disclosed initial positions may prevent it from accumulating positions at low prices and thus keep it from reaping the full benefits of its private information (Huddart, Hughes, and Levine, 2001). However, such costs are lower when copycat companies cannot identify particularly profitable trades, when the disclosing company has completed the disclosed strategy, or when the disclosed trades contain little private information. We thus examine the conditions under which copycats cause competitive harm to and impose proprietary costs on disclosing companies.
We first document that the subsequent performance of the disclosing company is negatively associated with the existence and prevalence of copycats, providing direct evidence of proprietary costs. Furthermore, the damage to the performance of the disclosing company increases with copycat sophistication and research intensity, the position-building horizon of the disclosing company, and the information asymmetry of disclosed portfolio stocks. We also find that, in the absence of sophisticated copycats or copycats with high research intensity, the disclosing company will not incur proprietary costs.
We conduct several additional tests to refine our analysis. First, we find that, when a hedge fund requests confidential treatment to withhold certain informed trades (Agarwal et al., 2013), viewers are less likely to follow the disclosed trades. Moreover, even when viewers copycat a hedge fund with confidential treatment, the disclosing hedge fund does not incur significant costs. Second, we find that copycats that view 13F filings sooner are more skilled and impose greater costs on the disclosing company. Lastly, we find that, while robot copycats also exist, they tend to inflict less damage on the disclosing company.
Our paper is the first to directly examine how copycats obtain information and selectively imitate their peers’ strategies. Identifying this mechanism allows us to understand the skills of copycats and how such skills affect the costs inflicted on disclosing companies. We find that, contrary to popular belief, copycatting is not naive imitation but instead a skilled effort to acquire and process information. We also show that the proprietary costs to disclosing companies depend on copycats’ ability as well as the characteristics of the disclosed information. Our findings can inform disclosure regulation that weighs the benefits of transparency against the proprietary costs of disclosure.
REFERENCES
Huddart, S., J. Hughes, and C. Levine. 2001. Public disclosure and dissimulation of insider trades. Econometrica 69: 665–681.
Agarwal, V., W. Jiang, Y. Tang, and B. Yang. 2013. Uncovering hedge fund skill from the portfolio holdings they hide. Journal of Finance 68: 739–783.
Leuz, C., and P. Wysocki. 2016. The economics of disclosure and financial reporting regulation: Evidence and suggestions for future research. Journal of Accounting Research 54: 525–622.
This post comes to us from professors Sean Cao at Georgia State University’s J. Mack Robinson College of Business, Kai Du at Pennsylvania State University’s Smeal College of Business, Alan L. Zhang at Florida International University’s College of Business, and Baozhong Yang at Georgia State University’s J. Mack Robinson College of Business. It is based on their recent article, “Copycat Skills and Disclosure Costs: Evidence from Peer Companies’ Digital Footprints,” available here.