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Paul Ma
Job Market Candidate
Stanford University
Department of Economics
579 Serra Mall
Stanford, CA 94305
650-644-8827
paulma@stanford.edu
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Research
Information or Spin? Evidence from Language
Differences Between 8-Ks and Press Releases
JOB MARKET PAPER
Abstract:
This paper examines whether investors correctly distinguish qualitative information from promotional language in press releases related to material events of US public firms. For a variety of material events, firms are required to issue a Form 8-K, but 37% of the time also voluntarily issue a press release concerning the same event, half of which occur prior to the 8-K filing date. Using textual analysis, I find that firms are more likely to issue a press release if the underlying 8-K tone is positive, and that tonal differences between the 8-K and the press release are driven in part by quotes from officers. I also find economically significant responses in firms' stock returns to tonal language in the 8-K, as well as to tonal differences between the two disclosures. To verify whether my strategy of comparing the press release against the 8-K is isolating the effects of promotional language or additional information, I test and find evidence of an initial positive reaction but subsequent negative drift from positively toned press releases. This implies that investors may have initially responded to both information and spin. Nominating
investor inattention as a possible mechanism for overreaction, I use novel search traffic micro-data from the SEC EDGAR website and detect lower 8-K search intensity in the presence of a press release. Together, my results are consistent with some investors overestimating the degree of substitutability between the two disclosures
and thus failing to readjust expectations accordingly.
Identifying Peer Firms:
Evidence from EDGAR Search Traffic
(with Charles MC Lee and Charles CY Wang)
Abstract: Using internet traffic patterns at the SEC EDGAR website, we show that firms appearing in chronologically adjacent searches by the same individual are fundamentally similar on multiple dimensions. In fact, traffic-based peer firms identified by our algorithm significantly outperform peer firms based on six-digit GICS industry grouping in explaining cross-sectional variations in base firms' stock returns, valuation multiples, forecasted and realized growth rates, research and development expenditures, and various other key financial ratios. Our results highlight the usefulness of EDGAR data, as well as the latent intelligence in search traffic patterns.
Motivating Graph
The Impact of High Frequency Arbitrageurs Upon Market Liquidity: Evidence from Exchange Outages
(with Matt Harding)[Old Version, Under Revision]
Abstract: We identify the presence of high frequency arbitrageurs in the US treasury market through intraday exchange outages. Evidence complementing our identification
shows that order cancelation behavior also changed during the outage, consistent with arbitrageurs' profit maximization motives. Our estimates suggest that
arbitrageurs represent approximately 69 to 94% of the quote depth in the spot treasury market. In addition, their presence seems to have large effects for
the bid-ask spread of the 30-year treasury bond, which is the most illiquid product within its class. Motivating Graph
Work-In-Progress
The Cost of Search (with Scott Bauguess)
The Earnings Scheduling Game: Evidence from China (with Mary Barth and Greg Clinch)
A Structural Approach of Estimating Analysts’
Weights of Public and Private Information (with Ivan Marinovic)
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