Analyst Revisions Research Articles

The Information Content of Analyst Revisions, Stock Price Synchronicity and Ownership Structure: Updated Evidence From China

The Information Content of Analyst Revisions, Stock Price Synchronicity and Ownership Structure: Updated Evidence From China

Tone complexity and analyst forecast behaviors: evidence from earnings conference calls

PurposeBoth the SEC (Securities and Exchange Commission) and the popular press have routinely criticized firms for the complexity of their financial disclosures. This study aims to investigate how financial analysts respond to the tone complexity of firm disclosures.Design/methodology/approachUsing approximately 20,000 earnings conference call transcripts of S&P 1,500 firms between 2005 and 2015, the authors first calculate the abnormal negative tone, the measure of tone complexity; then use such tone measure in econometric models to examine analyst forecast behavior. The authors also test the robustness of the results under different model specifications, tone word lists and alternative tone measure calculations.FindingsConsistent with the notion that analysts respond to the information demand from investors and incur more costs and effort to analyze firm disclosure when the tone is more complex, the authors find that higher tone complexity is positively and significantly associated with more analyst following, longer report duration, more forecast revisions, larger forecast error and larger forecast dispersion. In addition, the authors find that tone complexity has a long-term impact on analyst following but has a limited long-term impact on analyst report duration, analyst revision, forecast error and dispersion.Originality/valueThis study complements existing literature by highlighting the information role of financial analysts and by providing evidence that analysts incorporate the management tone disclosed during conference calls to adjust their forecasting behaviors. The results can be used by policymakers as evidence and support for further improving firm communication from a new dimension of disclosure tone.

Analyst ability and research effort: non-EPS forecast provision as a research quality signal

The range of non-EPS forecast types provided by individual analysts to I/B/E/S has increased dramatically over time but varies considerably across firms. We propose that in providing a broader range of forecast types, analysts can signal superior research ability and research effort. Consistent with this hypothesis, we document positive associations between the number of forecast types (NFT) an analyst provides and common proxies for research quality, including earnings forecast accuracy, price target accuracy, stock recommendation profitability, market reactions to stock recommendation revisions, and analyst career outcomes. The effects of NFT are incremental to other quality proxies used in the literature and are distinct from the issuance of specific non-EPS forecast types studied previously (e.g., cash flow forecasts). We demonstrate the information value of NFT to investors by examining the out-of-sample performance of portfolios formed conditional on NFT and exploiting revisions in consensus earnings forecasts and individual analysts’ stock recommendations. We conclude that the number of forecast types an analyst provides for a firm is a readily available proxy for the quality of her research.

The price impact of analyst revisions and the state of the economy: Evidence around the world

AbstractThis paper examines the price impact of analyst revisions in distinct economic states around the world. We find stronger average 2‐day cumulative abnormal returns in bad times, though this pattern is mainly observed in developed countries. In addition, trading strategies following analyst revisions, with holding periods from 1 to 6 months, are generally more profitable in good times with lower macroeconomic uncertainty, after controlling for market and common risk factors. The profitability, however, disappears or declines substantially after accounting for time‐varying risk premia conditioned on lagged macroeconomic information, indicating a reduced information production role played by analysts in recent decades.

Beyond Fama-French Factors: Alpha from Short-Term Signals

Short-term alpha signals are generally dismissed in traditional asset pricing models, primarily due to market friction concerns. However, this paper demonstrates that investors can obtain a significant net alpha by applying a combination of signals to a liquid global universe and with advanced buy/sell trading rules that mitigate transaction costs. The composite model consists of short-term reversal, short-term momentum, short-term analyst revisions, short-term risk, and monthly seasonality signals. The resulting alpha is present in out-of-sample and post-publication periods and across regions, translates into long-only applications, is robust to incorporating implementation lags of several days, and is uncorrelated to traditional Fama-French factors.

Informational role of analyst and investor days

This study empirically clarifies whether analyst and investor days (AI days) affect earnings expectations of participants. The analyses reveal that the tone of the question-and-answer (Q&A) session, rather than that of the management presentation, is positively associated with subsequent revisions of analysts' earnings forecasts. This suggests that such an interactive discussion during a Q&A session plays a key role in affecting analysts' expectations. Furthermore, abnormal returns around the AI days are irrelevant to the tone of the Q&A session. This suggests that AI days mainly provide a partially known (supplemental) information rather than offering new information to analysts and investors.

The Impact of Analyst, CEO, and Firm Reputations on Investors in the UK and Japanese Stock Markets

AbstractWe examine the importance of multiple agents’ reputations on the market's reaction to analysts’ stock recommendation revisions (analyst revisions), individually and interactively, in the UK and Japanese stock markets. We find some notable variations in reputation effects between the two markets. In the UK, analyst reputation amplifies the market's reaction to analyst revisions, while in Japan, analyst reputation has no significant impact. Firm reputation diminishes (amplifies) the market's reaction to analyst revisions in the UK (Japan). Only CEO reputation generates similar effects in the UK and Japan, dampening the market's reaction to analyst revisions. We also find that reputations interact in different ways in the two markets. Specifically, firm reputation and CEO reputation tend to moderate the positive effect of analyst reputation in the UK; however, in Japan, CEO reputation tends to moderate the positive effect of firm reputation, but there is no significant interaction effect between analyst reputation and CEO/firm reputation. Our findings are explained using insights both from formal economic models and from various cultural and institutional characteristics.

Internal Relevance between Analysts’ Forecasts and Target Prices - Informativeness and Investment Value

ABSTRACT Analysts’ decision-making process, through which they use earnings and non-earnings forecasts to provide their target price revisions, remains opaque. Based on the decision tree analysis, we develop a new multivariate information metric, Internal Relevance (IR), to measure the extent to which the revisions of analysts’ consensus earnings and sales forecasts are incorporated into the revisions of consensus target prices. We show that stocks with higher IR have stronger market reactions to target price revisions in terms of abnormal return, abnormal trading volume, and abnormal return volatility. These results remain consistent across a series of robustness checks. Finally, we perform portfolio analysis to show that IR can be used to screen stocks to improve trading profitability.

How Do Retail Investors Evaluate the Credibility of Directionally Inconsistent Analyst Revisions? Experimental Evidence

How Do Retail Investors Evaluate the Credibility of Directionally Inconsistent Analyst Revisions? Experimental Evidence

Peer Effects in Equity Research

AbstractWe study the importance of peer effects among sell-side analysts who work at the same brokerage house, but cover different firms. By mapping the information network within each brokerage, we identify analysts who occupy central positions in the network. Central analysts incorporate more information from their coworkers and produce better research. Using shocks to network structures around brokerage mergers, we identify the influence of peer effects and the importance of industry expertise on analysts’ performance. A portfolio strategy that exploits the forecast revisions of central analysts earns up to 24% per annum.

Google searches around analyst recommendation revision announcements: Evidence from the Taiwan stock market

We investigate the impact of Google search volume on stock prices and trading volume around recommendation revision announcements made by securities firms in the Taiwan stock market. Our results reveal that for upgrade announcements, the internet searches that are driven by investor attention lead to a temporary increase in positive price pressure around the revision announcements, whereas the price effect of the information extracted from the Google searches is persistent. We also find that trading volume reflects the incoming news around the revision announcements. Our results suggest that individual investors, who receive analyst revision reports gratis from securities firms before these reports are made public, will search through the Internet to obtain valid firm-specific information relating to the recommendation revisions.

Is the Bottom Line the Top Priority? A Choice Model of Revenue and Earnings Guidance

Based on the observation that managers provide almost 30% more revenue than earnings forecasts in recent periods, we jointly explore the decision to provide or forego revenue and/or earnings guidance. Our modeling innovation combines a random effects multinomial logit model, instrumental variables, and a correction for selection bias, which correctly classifies over 90% of observed guidance decisions. We find a stronger investor reaction to guidance surprises for firms whose guidance choice conforms to the predicted decision, suggesting that predictable guidance policies engender forecast credibility. The market response is driven more by managerial guidance than analyst revisions. Non-guiders quickly switch to guiding when the choice model suggests that guidance is the expected choice.

Tipping in Korea

Prior research documents that analyst revisions are important information events and that some investors trade ahead of them. However, prior studies have been unable to show which investors trade ahead of analyst revisions, the aggregate benefits to trading ahead, and the costs borne by various investors from trading against investors that anticipate revisions. To address these questions, we exploit high-frequency trading information from the Korea Exchange (KRX) that characterizes all purchase and sale transactions of twenty different investor groups. We first validate that analyst revisions contain valuable private information: upgrades increase prices by 2.5% and downgrades decrease prices by 2.9%. We next document that asset managers who are geographically and socially close to analysts anticipate recommendations up to two days before they are released, while other institutions do not. Lastly, we show that this ability to anticipate analyst revisions enables these investors to trade profitably against domestic retail investors and foreign professional investors. Local hedge funds earn $2.5 million more than normal when trading against foreign professionals ahead of analyst revisions, which is more than all other investor groups combined. Notably, local asset managers typically lose money when trading against foreign professionals, who seem to earn profits by engaging in high-frequency market making. In sum, asset managers in Korea appear to receive tips from brokerages about upcoming revisions, which shifts the competitive balance between domestic institutions and skilled foreign market makers, and aggregate profits around revisions depend on investor sophistication, geographic proximity, and cultural affinity.

Analyst Confirmation of Management Forecast Credibility During a Global Crisis

This paper examines whether textual management forecast commonalities that arise in a global crisis setting relate to ex post forecast accuracy, and whether subsequent analyst revisions confirm the credibility relevance of these commonalities. This approach is motivated by two conclusions. First, extant studies focus on general commonalities such as external (vs. internal) attributions, instead of specific subsets of these regularities that have the capacity to affect many management forecasts at the same time. Second, studies seldom focus on global crisis periods, although they acknowledge that those periods serve as catalysts for creating measures to assess management forecast credibility. After arguing that sales forecasts are most directly affected by global crisis conditions, I predict and find that management who attribute their sales forecasts (in full or in part) to the global crisis issue forecasts that are more accurate ex post. This finding is not consistent with the common assumption that external attributions are not based on skill and effort, and consistent with theoretical models of signaling and management ability. Furthermore, the ‘crisis’ attribution gives rise to a dictionary-free alternative to the linguistic tone measure which is related to ex post forecast accuracy. Analyst confirmation of the credibility relevance of these two measures suggests that they are useful for future research. Policy makers and regulators should find these results interesting as they offer new ways to improve the comparability of management forecasts.

Soft Information in the Financial Press and Analyst Revisions

Both sell-side analysts and the media are information intermediaries in capital markets. This study investigates the association between sell-side analyst research and information in firm-specific news coverage. More frequent recent news coverage is associated with stronger market reactions to analysts’ research revisions, and primarily explained by soft information in news coverage. The primary result is robust to using both an instrumental variable and a quasi-natural experimental setting to generate exogenous variation in media coverage, alleviating concerns about endogeneity. In addition, using textual analysis, we document that explicit media references in analyst research reports are significantly associated with more frequent analyst revisions and stronger market reactions to revisions. Our study provides empirical evidence of analysts’ assimilation of information from the financial press and their role in the efficiency of capital markets.

Soft Information in the Financial Press and Analyst Revisions

ABSTRACT Both sell-side analysts and the media are information intermediaries in capital markets. This study investigates the association between sell-side analyst research and information in firm-specific news coverage. More frequent recent news coverage is associated with stronger market reactions to analysts' research revisions, and primarily explained by soft information in news coverage. The primary result is robust to using both an instrumental variable and a quasi-natural experimental setting to generate exogenous variation in media coverage, alleviating concerns about endogeneity. In addition, using textual analysis, we document that explicit media references in analyst research reports are significantly associated with more frequent analyst revisions and stronger market reactions to revisions. Our study provides empirical evidence of analysts' assimilation of information from the financial press and their role in the efficiency of capital markets. JEL Classifications: G12; G14; G24.

Do Short Sellers Use Textual Information? Evidence from Annual Reports

We examine short sellers’ use of textual information in annual reports for shorting activities. We find that more uncertainty and negative words in annual reports are associated with greater abnormal shorting volume. Short selling motivated by textual information negatively predicts stock price reaction around the filing date of 10-K reports. We further provide some evidence that textual information used by short sellers are related to revisions of analysts’ earnings forecasts, changes in firm fundamentals, and increasing crash risk subsequently. Our results suggest that textual information in annual reports forms an important part of short sellers’ information advantage.

Month-End Reporting, Cash-Flow News, and Asset Pricing

We show that the stock market regularly and systematically receives information about company fundamentals through month-end reporting, even before the quarterly earnings announcement. Such cash-flow news concentrates at the beginning of a month and affects company announcements, analyst revisions, and stock returns. Using this time variation in cash-flow news, we show evidence supporting cash-flow news being more persistent than discount-rate news. Individual stock returns exhibit a post-monthly-announcement drift. Time series market momentum exists only when conditioning on past first-half month return, and is stronger when the past market-wide earnings surprise is bigger.

Oil price forecasts and security analysts: evidence from the oil industry

ABSTRACT This study examines the relation between the U.S. Energy Information Administration (EIA) oil forecasts and analyst earnings forecasts for oil firms. Analyst forecast biases (revisions) are positively related to EIA oil forecast biases (revisions) but only for firms with greater analyst coverage. For these firms, we also document a positive association between analyst revisions and future oil prices. This association becomes insignificant after the introduction of concurrent EIA oil forecast revisions, suggesting that security analysts might not possess incremental information on future oil prices.

Factor Performance 2010–2019: A Lost Decade?

The factors in the widely used Fama–French model experienced a negative average return during the 2010–2019 period. Perhaps surprisingly, such a lost decade is not unprecedented in history, as factor performance in the 2010s was, in fact, remarkably similar to factor performance in the 1990s. By contrast, many other factors did deliver a positive premium during the past decade. These factors include low risk, price momentum, earnings momentum, analyst revisions, seasonals, and short-term reversal. Thus, there appears to be a clear dichotomy in recent factor performance: while generally accepted factors struggled, various factors that are considered to be inferior or redundant remained effective. <b>TOPICS:</b>Factor-based models, style investing, volatility measures <b>Key Findings</b> • The factors in the widely used Fama–French model experienced a negative average return during the 2010–2019 period. This lost decade is remarkably similar to the 1990–1999 period. • Many other factors did deliver a positive premium during the past decade—for example, low risk, price momentum, earnings momentum, analyst revisions, seasonals, and short-term reversal. • In sum, there has been a clear dichotomy in recent factor performance: Although generally accepted factors struggled, other factors remained effective.