Selling on the news
Partisan Professionals: Evidence from Credit Rating Analysts
Elisabeth Kempf & Margarita Tsoutsoura
NBER Working Paper, November 2018
Abstract:
Partisan bias affects the decisions of financial analysts. Using a novel hand-collected dataset that links credit rating analysts to party affiliations from voter registration records, we show that analysts who are not affiliated with the U.S. President's party are more likely to downward-adjust corporate credit ratings. Our identification approach compares analysts with different party affiliations covering the same firm at the same point in time, ensuring that differences in the fundamentals of rated firms cannot explain the results. The effect is more pronounced in periods of high partisan conflict and for analysts who vote frequently. Our results suggest that partisan bias and political polarization create distortions in the cost of capital of U.S. firms.
Analyst Days, Stock Prices, and Firm Performance
Di (Andrew) Wu & Amir Yaron
University of Pennsylvania Working Paper, October 2018
Abstract:
We construct a comprehensive dataset of 3,890 analyst days, which are firm-hosted gatherings where information is disclosed to equity analysts and institutional investors. We demonstrate that firms holding these events have significantly higher abnormal returns after these events, despite the Regulation Fair Disclosure requirement that such information be simultaneously disclosed to the public. A buy-and-hold strategy that holds these stocks for 20 days earns a market-adjusted return of 1.6%, and a similar calendar-time portfolio has a one-month, four-factor alpha of 1.8%. We find no evidence of mean reversion or change in risk exposure after analyst days, and abnormal returns remain significantly positive for up to six months. We classify analyst days into four major types---product announcement, review of results, discussion of strategy, and technology and markets---according to the textual content of their announcements, and we show that product- and market-related analyst days earn significantly higher returns than events reviewing past financial results. Finally, firms holding analyst days have significantly higher revenue growth, earnings per share, and dividend yields up to two years after these events. Analyst coverage, earning estimates, and price targets also increase, and these estimates have lower dispersion. Our results thus suggest that firms use analyst days to convey positive incremental information that has not been incorporated in their stock prices, and market participants significantly underreact to this information.
Should Retail Investors' Leverage Be Limited?
Rawley Heimer & Alp Simsek
Journal of Financial Economics, forthcoming
Abstract:
Does the provision of leverage to retail traders improve market quality or facilitate socially inefficient speculation that enriches financial intermediaries? We evaluate the effects of 2010 regulations that cap leverage in the U.S. retail foreign exchange market. Using three unique data sets and a difference-in-differences approach, we document that the leverage-constraint reduces trading volume by 23%, alleviates high-leverage traders' losses by 40%, and reduces brokerages' operating capital by 25%. Yet, the policy does not affect the relative bid-ask prices charged by the brokerages. These results suggest the policy improves belief-neutral social welfare without reducing market liquidity.
Text-Based Industry Momentum
Gerard Hoberg & Gordon Phillips
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
We test the hypothesis that low-visibility shocks to text-based network industry peers can explain industry momentum. We consider industry peer firms identified through 10-K product text and focus on economic peer links that do not share common Standard Industrial Classification (SIC) codes. Shocks to less visible peers generate economically large momentum profits and are stronger than own-firm momentum variables. More visible traditional SIC-based peers generate only small, short-lived momentum profits. Our findings are consistent with momentum profits arising partially from inattention to economic links of less visible industry peers.
Tick Size Tolls: Can a Trading Slowdown Improve Price Discovery?
Charles Lee & Edward Watts
Stanford Working Paper, October 2018
Abstract:
This study examines how an increase in tick size affects algorithmic trading (AT), fundamental information acquisition (FIA), and the price discovery process around earnings announcements (EAs). Leveraging the SEC's randomized "Tick Size Pilot" experiment, we show a tick size increase results in a universal decline across four commonly-used proxies for AT. This decrease in AT is accompanied by a sharp drop in abnormal volatility and volume around EAs. More importantly, we find causal evidence of increased FIA in the pre-announcement period. Specifically, we show that with a larger tick size: (a) treatment firms' pre-announcement returns better anticipate next quarter's standardized unexpected earnings (SUEs); (b) their pre-announcement returns capture more of their total returns; (c) they experience an increase in EDGAR web traffic in the days leading up to EAs; and (d) they exhibit a drop in price synchronicity with index returns. Taken together, our evidence shows that while an increase in tick size reduces AT and abnormal market reaction after EAs, it also increases FIA activities prior to EAs.
The Impact of Linguistic Distance and Financial Reporting Readability on Foreign Holdings of U.S. Stocks
Kristian Allee, Lisa Anderson & Michael Crawley
University of Arkansas Working Paper, September 2018
Abstract:
Using a sample of 75 countries from U.S. Treasury regulatory data, we show that foreign investors invest less (more) in U.S. stocks (U.S. Treasuries) when they are from countries with greater linguistic distances and when U.S. financial reports are more difficult to read. This suggests that linguistic distance and financial reporting readability act as significant frictions for foreign investors when investing in equities, even in the U.S. market where foreign investors should have the greatest ability, resources, and economic incentives to overcome language translation and readability issues. Our results on U.S. Treasuries are consistent with a "substitution effect" where foreign investors who want to invest in U.S. stocks, but are sufficiently deterred by linguistic distance and financial reporting readability frictions, appear to seek the relative simplicity of investing in Treasury securities.
Outside Insiders: Does Access to Information Prior to an IPO Generate a Trading Advantage After the IPO?
Umit Ozmel, Timothy Trombley & Deniz Yavuz
Journal of Financial and Quantitative Analysis, forthcoming
Abstract:
We investigate whether access to information prior to an initial public offering (IPO) generates a trading advantage after the IPO. We find that limited partners (LPs) of lead venture capital funds obtain high returns when they invest in newly listed stocks backed by their funds. These returns are not explained by LPs' differing stock-picking abilities, and they are higher when LPs' information advantage over the public is higher. LPs are more likely to invest if they have an information advantage, and access to information eliminates the familiarity bias that they display otherwise.
The effect of fast trading on price discovery and efficiency: Evidence from a betting exchange
Paolo Bizzozero, Raphael Flepp & Egon Franck
Journal of Economic Behavior & Organization, December 2018, Pages 126-143
Abstract:
We examine how the presence of fast traders impacts price discovery and efficiency in a real-world setting, i.e., courtsiding, the activity of live betting from a tennis stadium. This setting allows us to isolate the activity of fast-acting traders who have a short-term monopolistic access to important information with respect to other traders who trade based on delayed TV images. Using live-tennis betting data combined with detailed point-by-point match data, our results show that courtsider trading promotes quick price discovery and correctly incorporates new information into prices. We estimate that a simple trading strategy yields a positive trading return to fast traders after the occurrence of important informational events.
Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy
Luis Felipe Costa Sperb et al.
International Journal of Forecasting, forthcoming
Abstract:
Increasingly, prediction markets are being embraced as a mechanism for eliciting and aggregating dispersed information and providing a means of deriving probabilistic forecasts of future uncertain events. The efficient market hypothesis postulates that prediction market prices should incorporate all information that is relevant to the performances of the contracts traded. This paper shows that such may not be the case in relation to information regarding environmental factors such as the weather and atmospheric conditions. In the context of horserace betting markets, we demonstrate that even after the effects of these factors on the contestants (horses and jockeys) have been discounted, the accuracy of the probabilities derived from market prices is affected systematically by the prevailing weather and atmospheric conditions. We show that significantly better forecasts can be derived from prediction markets if we correct for this phenomenon, and that these improvements have substantial economic value.
The Limits of Data Mining: A Thought Experiment
Andrew Chen
Federal Reserve Working Paper, October 2018
Abstract:
Suppose that asset pricing factors are just data mined noise. How much data mining is required to produce the more than 300 factors documented by academics? This short paper shows that, if 10,000 academics generate 1 factor every minute, it takes 15 million years of full-time data mining. This absurd conclusion comes from rigorously pursuing the data mining theory and applying it to data. To fit the fat right tail of published t-stats, a pure data mining model implies that the probability of publishing t-stats < 6.0 is ridiculously small, and thus it takes a ridiculous amount of mining to publish a single t-stat. These results show that the data mining alone cannot explain the zoo of asset pricing factors.
Do Credit Default Swaps Mitigate the Impact of Credit Rating Downgrades?
Sudheer Chava, Rohan Ganduri & Chayawat Ornthanalai
Review of Finance, forthcoming
Abstract:
We find that a firm's stock price reaction to its credit rating downgrade announcement is muted by 44-52% when credit default swaps (CDSs) trade on its debt. We explore the role of the CDS markets in providing information ex ante and relieving financing frictions ex post for downgraded firms. We find that the impact of CDS trading is more pronounced for firms whose debt financing is more dependent on credit ratings (e.g., those rated around the speculative-grade boundary, those with a higher number of rating-based covenants). Reductions in debt and investment, and the increase in financing costs are less severe for CDS firms than non-CDS firms following an identical credit rating downgrade. Our results suggest that CDSs mute the stock market reaction to a credit rating downgrade by alleviating the financing frictions faced by downgraded firms.