Why do security analysts issue overly positive recommendations? We propose a novel approach to distinguish strategic motives (e.g., generating small-investor purchases and pleasing management) from nonstrategic motives (genuine overoptimism). We argue that nonstrategic distorters tend to issue both positive recommendations and optimistic forecasts, while strategic distorters "speak in two tongues," issuing overly positive recommendations but less optimistic forecasts. We show that the incidence of strategic distortion is large and systematically related to proxies for incentive misalignment. Our "two-tongues metric" reveals strategic distortion beyond those indicators and provides a new tool for detecting incentives to distort that are hard to identify otherwise.

ABSTRACT Prior research demonstrates that investors respond differently to earnings surprises that are part of a string of consecutive earnings increases or surprises than to those that are not. To shed light on who values these patterns, I compare trading responses of small and large traders to earnings surprises that occur during a series of positive or negative surprises. I find that the relative intensity of small traders' trading response (and, to a lesser extent, that of medium traders) to earnings surprises generally increases as a series progresses. Small traders respond more negatively to the second (third) negative surprise in a series than to the first (second), and more positively for the first three surprises in a positive series. Moreover, I find that announcement-period returns are related to the trading of small and medium traders. These results suggest that less sophisticated smaller traders, responding to earnings series, contribute to previously documented pricing patterns. Data Availability: All data used in this study, with the exception of data obtained from an anonymous discount brokerage firm, are publicly available from the sources indicated in the text.

ABSTRACT We examine the impact of distance on internet search, and the effect of the “local bias” in search on the stock market response around earnings announcements. We find significant local bias in search behavior. Motivated by theories explaining local bias, local information advantage, and familiarity bias, we predict and find that firms with higher local bias in search experience higher bid-ask spreads, lower trading volumes, and lower earnings response coefficients at the time of earnings announcements, consistent with non-local investors relying more than locals on public information announcements. Consistent with local information advantage, we find that in the week prior to the announcement, firms with higher local bias have higher bid-ask spreads, higher trading volumes, and returns that are more predictive of the coming earnings surprise. Consistent with familiarity bias, firms with higher local bias in search experience stronger post-earnings announcement drift. We use unique predictions, propensity score matching, and two-stage least squares to identify the effects of local bias separately from the effects of overall visibility. Overall, we show there is significant local bias in search, and that this local bias has a significant impact on the market response around earnings announcements.

Security analysts tend to bias stock recommendations upward, particularly if they are affiliated with the underwriter. We analyze how investors account for such distortions. Using the NYSE Trades and Quotations database, we find that large traders adjust their trading response downward. While they exert buy pressure following strong buy recommendations, they display no reaction to buy recommendations and selling pressure following hold recommendations. This “discounting” is even more pronounced when the analyst is affiliated with the underwriter. Small traders, instead, follow recommendations literally. They exert positive pressure following both buy and strong buy recommendations and zero pressure following hold recommendations. We discuss possible explanations for the differences in trading response, including information costs and investor naiveté.

Why do analysts display overoptimism about the stocks they cover? According to the selection hypothesis, analysts pick their favorite stocks and are truly too optimistic. According to the conflict-of-interest hypothesis, analysts distort their view to maximize profits via commissions and underwriting business, in particular if affiliated with an underwriting bank. We analyze the concurrent issuance of recommendations and earnings forecasts to assess the relative importance of both explanations for affiliated and for unaffiliated analysts. First, we show that recommendations and forecasts reach different audiences. Small traders follow recommendations but not forecast updates; large traders discount recommendations and follow earnings forecasts. As a result, analysts may choose to distort recommendations but prove their analyst quality in their forecasts. The selection hypothesis implies, instead, a positive correlation between recommendation and forecast overoptimism. We find that, while affiliated analysts issue more optimistic recommendations than unaffiliated analysts, their earnings forecasts are more pessimistic. Moreover, forecast optimism is negatively correlated with recommendation optimism for affiliated analysts but positively for unaffiliated analysts. Similar discrepancies between the timing of recommendations and forecasts confirm that active distortion is a major explanation for the recommendation optimism of affiliated analysts.

Abstract Using unique new data, we examine whether brokerage trading volume creates a conflict of interest for analysts. We find that earnings forecast optimism is associated with higher brokerage volume, even controlling for forecast and analyst quality, recommendations, and target prices. However, forecast accuracy is also significantly associated with higher volume. When analysts change brokerage houses, they bring trading volume with them, influencing trading volume at the new brokerage. This indicates that analysts drive the volume effects we observe. Consistent with a reward for generating volume, brokerage houses are less likely to demote analysts who generate more volume. Finally, analysts strategically adjust forecast optimism based on expected volume impact. Analysts become more (less) optimistic if their optimistic forecasts in the prior year were more (less) successful at generating volume. However, consistent with higher costs to increasing accuracy, analysts do not update accuracy based on expected volume impact. Overall, our results are consistent with a brokerage trading volume conflict of interest moving analysts towards more optimistic earnings forecasts, despite the volume reward for accuracy.

Abstract The revised Markets in Financial Instruments Directive (MiFID II) requires the unbundling of research payments from trading execution, fundamentally changing the way in which investors typically pay for analyst research in Europe. We examine the effectiveness of the regulation in changing the link between analyst research and trading, the research‐trading link, and the analyst response to this potential change in incentives. Using a difference‐in‐differences research design, we find that forecast frequency, optimism, and accuracy are less associated with the brokerage trading share after MiFID II, suggesting that MiFID II weakened the link between the brokerage share of trading and analyst research. Following MiFID II, analysts in Europe are less likely than analysts in the United States to continue high forecast frequency, optimism, and accuracy for stocks with high share importance for the analyst's brokerage house. We find similar results throughout for buy/sell recommendations. Overall, our evidence suggests that MiFID II is at least partially successful in unbundling research from execution, and impacts both the trading effects and the production of analyst research.

ABSTRACT We study how public firm misvaluation affects private peer firm investments. An economic competition hypothesis predicts a negative relation because misvaluation-induced new investment by public firms crowds out investment by private peers that share common input or output markets. An alternative shared sentiment hypothesis predicts a positive relation because private firm stakeholders share in the sentiment associated with misvaluation in public markets. Misvaluation is proxied using both the price-to-fundamental ratio and an exogenous instrument obtained from mutual fund flows. The evidence is consistent with the shared sentiment hypothesis, and robust to alternative treatments for growth opportunities. Private firms finance misvaluation-induced investment primarily internally or externally with debt, not equity. Finally, misvaluation-induced investment increases future return on investment for private firms, in contrast with public firms. Overall, these findings suggest that overvaluation in public markets increases private firm investments and has beneficial effects on private firm investments by relaxing financing constraints. JEL Classifications: G32; M41. Data Availability: Data are available from sources identified in the paper.

Abstract We build a novel comprehensive data set of new product trademarks as an output measure of product development innovation. We show that risk-taking incentives in CEO compensation motivate this type of innovation and that this innovation improves firm performance. Using an exogenous shock to executive compensation, we find that reductions in stock option compensation cause reductions in new product development. We also find that firms undertaking new product development experience increases in future cash flow from operations and return on assets. These findings suggest the importance of product development innovation to firms and new trademarks as a novel innovation measure.