Long or short
Short Interest and Aggregate Stock Returns
David Rapach, Matthew Ringgenberg & Guofu Zhou
Journal of Financial Economics, forthcoming
Abstract:
We show that short interest is arguably the strongest known predictor of aggregate stock returns. It outperforms a host of popular return predictors both in and out of sample, with annual R2 statistics of 12.89% and 13.24%, respectively. In addition, short interest can generate utility gains of over 300 basis points per annum for a mean-variance investor. A vector autoregression decomposition shows that the economic source of short interest’s predictive power stems predominantly from a cash flow channel. Overall, our evidence indicates that short sellers are informed traders who are able to anticipate future aggregate cash flows and associated market returns.
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The Wisdom of Twitter Crowds: Predicting Stock Market Reactions to FOMC Meetings via Twitter Feeds
Pablo Azar & Andrew Lo
MIT Working Paper, March 2016
Abstract:
With the rise of social media, investors have a new tool to measure sentiment in real time. However, the nature of these sources of data raises serious questions about its quality. Since anyone on social media can participate in a conversation about markets -- whether they are informed or not -- it is possible that this data may have very little information about future asset prices. In this paper, we show that this is not the case by analyzing a recurring event that has a high impact on asset prices: Federal Open Market Committee (FOMC) meetings. We exploit a new dataset of tweets referencing the Federal Reserve and shows that the content of tweets can be used to predict future returns, even after controlling for common asset pricing factors. To gauge the economic magnitude of these predictions, the authors construct a simple hypothetical trading strategy based on this data. They find that a tweet-based asset-allocation strategy outperforms several benchmarks, including a strategy that buys and holds a market index as well as a comparable dynamic asset allocation strategy that does not use Twitter information.
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The Customer Knows Best: The Investment Value of Consumer Opinions
Jiekun Huang
University of Illinois Working Paper, March 2016
Abstract:
This paper investigates the investment value of consumer opinions. Using a dataset of over 5.9 million customer product reviews on Amazon.com from 2004 through 2015, I find evidence that consumer opinions contain information for stock pricing. A spread portfolio that buys stocks in the top tercile of abnormal customer ratings and sells stocks in the bottom tercile delivers an abnormal return of about 72-80 basis points per month. There is no evidence of return reversals in the subsequent year. I also find that abnormal customer ratings positively predict revenues and earnings surprises. Furthermore, there is evidence suggesting that hedge funds exploit information contained in customer reviews. These results suggest that consumer opinions contain novel information about firms' fundamentals and stock pricing.
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The Realization Effect: Risk-Taking After Realized Versus Paper Losses
Alex Imas
American Economic Review, forthcoming
Abstract:
Understanding how prior outcomes affect risk attitudes is critical for the study of choice under uncertainty. A large literature documents the significant influence of prior losses on risk attitudes. The findings appear contradictory: some studies find greater risk-taking after a loss, whereas others show the opposite – that people take on less risk. I reconcile these seemingly inconsistent findings by distinguishing between realized versus paper losses. Using new and existing data, I replicate prior findings and demonstrate that following a realized loss, individuals avoid risk; if the same loss is not realized, a paper loss, individuals take on greater risk.
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Local Ownership, Crises, and Asset Prices: Evidence from US Mutual Funds
Mariassunta Giannetti & Luc Laeven
Review of Finance, May 2016, Pages 947-978
Abstract:
We exploit the domestic portfolios of US mutual funds to provide microeconomic evidence that investors are more likely to liquidate geographically remote investments at times of high aggregate market volatility. This has important implications for asset prices. The valuations of stocks with ex ante less local ownership decline more when aggregate market volatility is high. Furthermore, the returns of stocks with geographically distant owners are more exposed to changes in aggregate market volatility.
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The Value of Crowdsourced Earnings Forecasts
Russell Jame et al.
Journal of Accounting Research, forthcoming
Abstract:
Crowdsourcing — when a task normally performed by employees is outsourced to a large network of people via an open call — is making inroads into the investment research industry. We shed light on this new phenomenon by examining the value of crowdsourced earnings forecasts. Our sample includes 51,012 forecasts provided by Estimize, an open platform that solicits and reports forecasts from over 3,000 contributors. We find that Estimize forecasts are incrementally useful in forecasting earnings and measuring the market's expectations of earnings. Our results are stronger when the number of Estimize contributors is larger, consistent with the benefits of crowdsourcing increasing with the size of the crowd. Finally, Estimize consensus revisions generate significant two-day size-adjusted returns. The combined evidence suggests that crowdsourced forecasts are a useful supplementary source of information in capital markets.
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Roni Michaely, Amir Rubin & Alexander Vedrashko
Journal of Accounting and Economics, August 2016, Pages 24–45
Abstract:
Using combinations of weekdays and times of day (before, during, and after trading hours) of earnings announcements, we examine whether managers attempt to strategically time these announcements. We document that the worst earnings news is announced on Friday evening and find robust evidence that only Friday evening announcements represent managers’ rational opportunistic behavior. Friday evening announcements are followed by insider trading in the direction of earnings news and the largest post-earnings announcement drift. Managers also attempt to reduce interaction with investors and hide more than just earnings news by announcing on Friday evening. We find that Friday evening announcements occur later in the evening than announcements on other evenings, firms have a reduced propensity to hold conference calls, and major firm restructuring events are relatively more likely to occur after Friday evening announcements.
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It Pays to Set the Menu: Mutual Fund Investment Options in 401(k) Plans
Veronika Pool, Clemens Sialm & Irina Stefanescu
Journal of Finance, forthcoming
Abstract:
This paper investigates whether mutual fund families acting as service providers in 401(k) plans display favoritism toward their own affiliated funds. Using a hand-collected data set on the menu of investment options offered to plan participants, we show that fund deletions and additions are less sensitive to prior performance for affiliated than unaffiliated funds. We find no evidence that plan participants undo this affiliation bias through their investment choices. Finally, we find that the subsequent performance of poorly performing affiliated funds indicates that this favoritism is not information driven.
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Rating friends: The effect of personal connections on credit ratings
Seyed Hossein Khatami, Maria-Teresa Marchica & Roberto Mura
Journal of Corporate Finance, forthcoming
Abstract:
Using a large sample of US public debt issues we show that personal connections between directors of issuing companies and rating agencies result in higher credit ratings. We estimate the average effect to be about one notch. Moreover, our tests indicate that issues by connected firms are 30% more likely to be rated A3. Results are robust to several alternative tests including additional controls for managerial traits, firm fixed effects, and propensity score matching. Furthermore, our tests on default rates and bond yields suggest that personal connections act as a mechanism to reduce asymmetric information between the rating agency and the issuer.
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Do Earnings Estimates Add Value to Sell-Side Analysts’ Investment Recommendations?
Ambrus Kecskés, Roni Michaely & Kent Womack
Management Science, forthcoming
Abstract:
Sell-side analysts change their stock recommendations when their valuations differ from the market’s. These valuation differences can arise from either differences in earnings estimates or the nonearnings components of valuation methodologies. We find that recommendation changes motivated by earnings estimate revisions have a greater initial price reaction than the same recommendation changes without earnings estimate revisions: about +1.3% (−2.8%) greater for upgrades (downgrades). Nevertheless, the postrecommendation drift is also greater, suggesting that investors underreact to earnings-based recommendation changes. Implemented as a trading strategy, earnings-based recommendation changes earn risk-adjusted returns of 3% per month, considerably more than non-earnings-based recommendation changes. Evidence from variation in firms’ information environment and analysts’ regulatory environment suggests that recommendation changes with earnings estimate revisions are less affected by analysts’ cognitive and incentive biases.
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Pseudo-Precision? Precise Forecasts and Impression Management in Managerial Earnings Forecasts
Mathew Hayward & Markus Fitza
Academy of Management Journal, forthcoming
Abstract:
We examine earnings guidance precision as a mechanism of organization impression management (OIM) and, specifically, suggest that strategic leaders use very precise earnings forecasts as an OIM tactic to convey a greater sense of authority and control over organizational performance after material organizational setbacks. Contributing to the OIM literature, we argue that the use of more precise judgment makes use of different physiological mechanisms than kinds of OIM that have been previously studied. Results presented here suggest that a) OIM is an important motivation for more precise earnings forecasts b) precision as an OIM tactic is more likely to arise when managers convey impressions of brighter performance prospects and c) investors generally respond favorably to the tactic.
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Social Media, News Media and the Stock Market
Peiran Jiao, Andre Veiga & Ansgar Walther
University of Oxford Working Paper, April 2016
Abstract:
We contrast the impact of traditional news media and social media coverage on stock market volatility and trading volume. We develop a theoretical model of asset pricing and information processing, which allows for both rational traders and a variety of commonly studied behavioural biases. The model yields several novel and testable predictions about the impact of news and social media on asset prices. We then test the model’s theoretical predictions using a unique dataset which measures coverage of individual stocks in social and news media using a broad spectrum of print and online sources. Stocks with high social media coverage in one month experience high idiosyncratic volatility of returns and trading volume in the following month. Conversely, stocks with high news media coverage experience low volatility and low trading volume in the following month. These effects are statistically and economically significant and robust to controlling for stock and time fixed effects, as well as time-varying stock characteristics. The empirical evidence on news media is consistent with a market in which some traders are overconfident when interpreting new information. The evidence on social media is consistent with Tetlock’s (2011) “stale news” hypothesis (investors treat repeated information on social networks as though it were new) and with a model where investors’ perceptions are subject to random sentiment shocks.
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It Hurts (Stock Prices) When Your Team is about to Lose a Soccer Match
Michael Ehrmann & David-Jan Jansen
Review of Finance, May 2016, Pages 1215-1233
Abstract:
The end result of major sporting events has been shown to affect next day stock returns through shifts in investor mood. By studying intraday data during the soccer matches that led to the elimination of France and Italy from the 2010 FIFA World Cup, we test whether mood-related pricing effects already materialize as events unfold. We use data for a cross-listed firm, which allows for a straightforward identification of underpricing. During the matches, the firm’s stock is underpriced by up to 7 basis points in the country that eventually loses. The probability of underpricing increases as elimination becomes more likely.
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Alok Kumar, Jeremy Page & Oliver Spalt
Journal of Financial and Quantitative Analysis, February 2016, Pages 85-111
Abstract:
This study shows that correlated trading by gambling-motivated investors generates excess return comovement among stocks with lottery features. Lottery-like stocks comove strongly with one another, and this return comovement is strongest among lottery stocks located in regions where investors exhibit stronger gambling propensity. Looking directly at investor trades, we find that investors with a greater propensity to gamble trade lottery-like stocks more actively and that those trades are more strongly correlated. Finally, we demonstrate that time variation in general gambling enthusiasm and income shocks from fluctuating economic conditions induce a systematic component in investors’ demand for lottery-like stocks.
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Trading Skill: Evidence from Trades of Corporate Insiders in Their Personal Portfolios
Itzhak Ben-David, Justin Birru & Andrea Rossi
NBER Working Paper, March 2016
Abstract:
We study trading patterns of corporate insiders in their own personal portfolios. To do so, we identify accounts of corporate insiders in a large dataset provided by a retail discount broker. We show that insiders overweight firms from their own industry. Furthermore, insiders earn substantial abnormal returns only on stocks from their industry, especially obscure stocks (small, low analyst coverage, high volatility). In a battery of tests, we find no evidence that corporate insiders use private information and conclude that insiders have an informational advantage in trading stocks from their own industry over outsiders to the industry.
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Is There a “Boom Bias” in Agency Ratings?
Mark Dilly & Thomas Mählmann
Review of Finance, May 2016, Pages 979-1011
Abstract:
Theory predicts rating agencies’ incentive conflicts to be stronger in boom periods, leading to biased ratings and a reduced level of rating quality. We investigate this prediction empirically based on three different approaches. First, we show that initial ratings disagree with bond spread levels during boom periods in the way that rating agencies hold a systematically more optimistic view. Second, we reveal that boom bond ratings tend to be more heavily downgraded from an ex post perspective; and, third, we demonstrate that boom ratings are inflated compared with “conflicts-free” benchmark ratings. In several robustness tests we show that the observed “boom bias” does not result from changes in credit-worthiness, adjustments in rating standards, competitive pressure, or market supply, but rather from rating agencies’ incentive conflicts.
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Political Conflict and Foreign Portfolio Investment: Evidence from North Korean Attacks
Jeffrey Gerlach & Youngsuk Yook
Federal Reserve Working Paper, April 2016
Abstract:
We examine the response of foreign (i.e., non-South Korean) investors to escalating political conflict and its impact on the South Korean stock market surrounding 13 North Korean military attacks between 1999 and 2010. Using domestic (i.e., South Korean) institutions and individuals as benchmarks, we evaluate the trading behavior and performance of foreign investors. Following attacks, foreigners increase their holdings of Korean stocks and buy more shares of risky stocks. Performance results show foreigners maintain their pre-attack level of performance while domestic individuals, who make the overwhelming majority of domestic trades, perform worse. In addition, domestic institutions improve their performance. Overall, the results are consistent with the predictions based on the benefits of international diversification. Unlike domestic individuals, foreigners trade more shares than usual and deviate from their general strategy of positive feedback trading.
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The Capital Market Consequences of Language Barriers in the Conference Calls of Non-U.S. Firms
Francois Brochet, Patricia Naranjo & Gwen Yu
Accounting Review, forthcoming
Abstract:
We examine how language barriers affect the capital market reaction to information disclosures. Using transcripts from non-U.S. firms' English-language conference calls, we find that the calls of firms in countries with greater language barriers are more likely to contain non-plain English and erroneous expressions. For non-U.S. firms that hire an English-speaking manager, we find less use of non-plain English and fewer erroneous expressions. Calls with a greater use of non-plain English and more erroneous expressions show lower intraday price movement and trading volume. The capital market responses to non-plain English and erroneous expressions are more negative when the firm is located in a non-English-speaking country and has more English-speaking analysts participating in the call. Our results highlight that, when disclosure happens verbally, language barriers between speakers and listeners affect its transparency, which in turn impacts the market's reaction.
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Why Don't We Agree? Evidence from a Social Network of Investors
Anthony Cookson & Marina Niessner
Yale Working Paper, March 2016
Abstract:
We develop a new measure of disagreement based on the sentiment expressed by investors on a social network investing platform. Changes in our measure of disagreement robustly forecast abnormal trading volume, even though it is unlikely that investor trades from those on the investing platform move the market. Using information on the investment philosophies of the investors (e.g., technical, fundamental, short term, long term), we test existing theories that suggest that differing investment philosophies are an important source of disagreement. Although we also find significant scope for disagreement among investors with the same investment philosophy, our findings suggest that investment approaches matter fundamentally to disagreement. Therefore, even with perfectly informationally efficient markets, investor disagreement, and thus high trading volume and volatility, would likely persist.
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Why Do Traders Choose Dark Markets?
Ryan Garvey, Tao Huang & Fei Wu
Journal of Banking & Finance, July 2016, Pages 12–28
Abstract:
We examine U.S. equity trader use of dark and lit markets. Marketable orders executed in the dark have lower information content and smaller fill rates. Dark orders take longer to execute, but they execute at more favorable prices. Traders are more likely to go dark when the bid-ask spread is wider and those with higher dark participation are more sophisticated. Although market regulators have expressed concern over the rise in dark trading, our results indicate that dark markets provide important benefits to traders that lit markets do not.