Sell-side Equity Analysts Research Articles

So sánh tính đáng tin cậy của các ước tính giá trị nội tại tạo ra từ ba mô hình định giá dòng tiền và mô hình bội số

Different equity valuation models in theory provide identical estimates of equity intrinsic values if they are implemented with consistent assumptions. In practice, it is not unusual to obtain different value estimates from different models. Prior research on the comparison between multiples-based valuation model and flowsbased valuation models are quite limited. This research contributes to the literature by comparing the accuracy and reliability of three flows-based valuation models (discount dividend model, discounted free cash flow model, residual income valuation model) and multiples-based valuation model using one-year forward forecasted earning (PE1). For the analysis, all models are tested for bias, accuracy and explainability using t-tests, Wilcoxon tests and OLS regressions with a large sample of 40.547 observations from U.S public firms during the period from 2010 to 2020. Results show that PE1 value estimates are more accurate and reliable than that of flows-based models; and among flows-based models, residual income valuation model performs best. This research provides evidence for the performance and usage of such models to support sell-side equity analysts while making decisions of which model to use.

The Effect of Asymmetric Information on the Pricing of Equity Issuance

Purpose: This paper examined the adverse selection in the market for seasoned equity issuance.
 Methodology: The asymmetric information explained the price reduction at the date of equity issuance. In particular, equity issuance tended to follow credible information releases since companies issued equity when the market was the most informed about the quality of their firms. The paper exploited brokerage mergers as a quasi-natural experiment that increased information asymmetry through their effect on the extent of research coverage by sell-side equity analysts.
 Findings: The broker mergers unexpectedly terminated brokers operation, and the level of analyst coverage decreased for the firms previously covered by these analysts. This paper showed that the cumulative abnormal return was positive around the date of equity issuance when asymmetric information increased and more substantial for stocks that lost analyst coverage relative to the stocks that never lost any coverage. Moreover, affected companies by the brokerage mergers issued more equity after the events compared to the control group. This paper showed the causal impact of losing analyst coverage on price at the time of equity issuance.

A Star Is Born: The Relationship Between Performance and Achieving Status Through Certification Contests in the Context of Equity Analysts

We investigate how the relationship between status and performance decouples over time by addressing two questions: (1) how performance affects the likelihood that an actor achieves high status and (2) how achieving high status affects the actor’s subsequent performance. In doing so, we focus on the role repeated certification contests play, where evaluators assess actors’ performance along particular dimensions and confer high status on the contest winners. Using the context of sell-side (brokerage) equity analysts and the “All-Star” list from Institutional Investor magazine, we first investigate whether analysts who make the All-Star list are more likely to produce accurate and/or independent forecasts. Then, we investigate analyst performance after recent and multiple wins. Our results demonstrate the decoupling of status and performance over time and the roles played by both the high-status actor and the social evaluators conferring their status. Whereas analyst performance increases the likelihood of being designated an All-Star, recent and multiple All-Star designations differentially affect both how subsequent performance is assessed, and how the All-Star analysts subsequently perform. In the short term, achieving high status can increase performance and solidify an analyst’s status position; however, in the long term, it can lead to lower performance and eventually result in status loss, which further erodes performance.

When Do Associate Analysts Matter?

Although extant literature investigates the role of sell-side equity analysts in capital markets, most studies do not consider that sell-side equity analysts often work in hierarchical teams. Lead analysts manage a team of associate and junior analysts who participate in the team’s tasks. Building on the delegation theory in the management literature, we hypothesize and find a division of labor between lead and associate analysts, where lead analysts are more likely to delegate tasks (1) that are less significant, (2) that are simpler, (3) when the workload of the lead analyst increases, and (4) when the associate analyst is more competent. Our results further suggest that associate analysts play a significant role in forecasting. By contrast, lead analysts are the main contributors to the qualitative aspects of analyst reports and are more likely to participate in earnings conference calls. Overall, our study documents the significant role of associate analysts in forecasting and the division of labor between lead and associate analysts. This paper was accepted by Brian Bushee, accounting.

Social learning and analyst behavior

This study examines whether sell-side equity analysts engage in “social learning” in which their earnings forecasts for certain firms are influenced by the forecasts and outcomes of “peer” analysts associated with other firms in their respective portfolios. We find that analyst optimism is negatively correlated with recent forecast errors, by peers, on other firms in the analyst's portfolio. An analyst is also more likely to issue “bold” forecasts when peers recently issued similar forecasts for other portfolio firms. Analysts learn more from peers with similar personal characteristics. Overall, social learning benefits analysts and improves their forecast accuracy.

Student Recommendations and Subsequent Stock Returns for Smif Investments

This paper measures the predictive power of buy-sell-and-hold recommendations made by students engaged in the management of a student-managed investment fund (SMIF). In their roles as analysts and portfolio managers for the SMIF, undergraduate students were required to follow traditional security analytical techniques such as discounted cash flow analysis and comparative valuation that were taught in the introductory investment management class, which is a pre-requisite. We evaluated the stock price performance of the stocks which the students analyzed across multiple holding periods, following student recommendations to buy, sell, or hold. We also compared the recommendations of the student-analysts to the contemporaneous recommendations of sell-side equity analysts.

Aggregating Artificially Intelligent Earnings Forecasts

This paper proposes a new artificial intelligence-based framework for aggregating the opinions of sell-side equity analysts. Our key conjecture is that analyst-level individual errors are more predictable and can be corrected more effectively than the aggregate consensus forecast. Artificial neural network models are able to learn the individual-level biases of sell-side equity analysts and can compensate for their biases more effectively. Using the bias-corrected consensus earnings forecasts and a neural network-based aggregation method, we find that the accuracy of the consensus forecast improves by 24% relative to a benchmark linear model. The neural network-based model can predict the correct sign for the earnings surprise 68% of the time. A portfolio strategy that uses the improved consensus forecasts earns a monthly abnormal return of 0.50% on a risk-adjusted basis.

Sell-side equity analysts and equity sales: A study of interaction

The extensive literature on sell-side analysts makes little reference to equity sales as a significant economic actor in the field. Drawing on a recent field study, our empirical evidence identified equity sales teams within brokers, who promote research to external clients, as a powerful agent cluster in close time-space proximity to analysts. This paper sheds light on analyst-sales interactions, which we contend represent an important field condition. The study employs concepts from strong structuration theory, in particular position-practice relations, to develop a narrative about sell-side analysts’ and sales team positional obligations, privileges, power relations and matters of trust. Our study makes three contributions. Firstly, we identify the symbiosis embedded in the relationship between sales and research - analysts need equity sales to market their product, to positively influence client perceptions of analysts and to provide access to prized fund managers. In turn, sales need analysts to provide content for them to market. Secondly, integral to sales-analyst interactions is the provision of feedback, which causes difficulties in the relationship, leaving analysts vulnerable to sales influence. Thirdly, regulatory tension has changed sales-analyst interactions, and this can enrich our understanding of why analysts continue to publish commoditised research into highly competitive markets.

Personal Financial Distress, Limited Attention, and Sell-Side Analysts

By linking sell-side equity analysts to their deed records and LinkedIn profiles, I show that analysts with higher exposure to negative wealth shocks issue more pessimistic and less accurate forecasts. The effects are stronger when analysts have higher leverage in their homes and face career concerns. I also find that stocks recommended by exposed analysts underperform those of non-exposed counterparts, by an amount that is significant and economically large in magnitude. The results remain robust to unobserved skill differences, the potential endogeneity of housing prices, the self-selection of analysts into neighborhoods with certain traits, and placebo tests where housing wealth shocks are randomized across analysts. Collectively, this study provides new evidence on if and how personal wealth shocks impact analysts' work productivity and forecast behavior.

Terrorist Attacks, Analyst Sentiment, and Earnings Forecasts

We examine whether exogenous and extremely negative events, such as terrorist attacks and mass shootings, influence the sentiment and forecasts of sell-side equity analysts. We find that analysts who are local to these attacks issue forecasts that are relatively more pessimistic than the consensus forecast. This effect is stronger when the analyst is closer to the event and located in a low-crime region. Impacted analysts are also relatively more pessimistic around the one- and two-year anniversaries of the attacks. Collectively, these findings indicate that exposure to extreme negative events affects the behavior of information intermediaries and the information dissemination process in financial markets.This paper was accepted by David Simchi-Levi, finance.

Incentives, Clienteles, and Information Production: New Evidence from Investor-paid and Issuer-Paid Agency Credit Ratings and Equity Analyst Recommendations

We compare the timeliness of the information signals produced by investor-paid credit rating agencies (Egan and Jones), issuer-paid credit rating agencies (Standard and Poor's), and by sell-side equity analysts, and study the predictive power of this information for the bond and equity markets and for firm investment levels. We conjecture that the three information producing intermediaries differ in two important dimensions: first, in their compensation structure, giving rise to differences in their incentives to produce and transmit timely information signals; and second, in their information consuming clientele, giving rise to differences in the aspects of firms' future cash flow distribution on which they focus. We develop testable hypotheses based on the above two differences. Consistent with our hypotheses, we find the following. First, information signals produced by the investor-paid rating agency are the most timely, and anticipates those produced by the issuer-paid agency and equity analysts. Second, while investor-paid agency rating changes have the greatest predictive power for bond yield spreads, equity analyst recommendations have the greatest predictive power for excess stock returns. Third, credit rating changes by the investor-paid rating agency have the greatest predictive power for firms' investment levels.

Social Learning and Analyst Behavior

This study examines whether sell-side equity analysts engage in “social learning” where their earnings forecasts are influenced by the forecasts and outcomes of other analysts associated with other firms (i.e., the “peers”) in their respective portfolios. We find that analyst optimism is negatively correlated with the recent forecast errors among peers on other firms in the analyst portfolio. An analyst is also more likely to issue “bold” forecasts when similar forecasts were recently issued for other portfolio firms. Analysts learn more from their peers with similar personal characteristics. Overall, social learning is beneficial to analysts and improves their forecast accuracy.

Are Social Media Analysts Disrupting the Information Content of Sell-Side Analysts’ Reports?

We examine how research posted by “social media analysts” (SMAs), individuals posting equity research online via social media investment platforms, is related to research subsequently produced by professional sell-side equity analysts. Using data from Seeking Alpha, we find that the market reaction to sell-side analyst research is substantially reduced when preceded by the report of an SMA, and this is particularly true for sell-side analysts’ earnings forecasts. We further find that this effect is more pronounced when SMA reports contain more decision-useful language, are produced by SMAs with greater expertise, and relate to firms with greater retail investor ownership. We also provide evidence that the attenuated response to sell-side research is most likely explained by SMA research preempting information in sell-side research and that analysts respond to SMA preemption with bolder and more disaggregated forecasts. Collectively, our results suggest that equity research posted online by SMAs provides investors with information similar to but earlier than sell-side equity research and speak to the connected and evolving roles of information intermediaries in capital markets.

Do Sell-Side Analysts Say Buy While Whispering Sell?

I examine how sell-side equity analysts strategically disclose different information to the public and buy-side mutual fund managers to whom they are connected. I specifically test the possibility that analysts’ public recommendations tell the public to “buy” but they are whispering “sell” to their connected fund managers. I measure the likelihood of such “say buy/whisper sell” behavior based upon the percentage of managers’ selling stocks that analysts recommend buying. Using mutual fund managers’ votes for sell-side analysts in a Chinese “star analyst” competition as a proxy for managers’ evaluations of analysts, I find that managers are more likely to vote for the analysts who exhibit more say buy/whisper sell behavior with these managers. This result suggests that managers receive more-precise information in private communications with an analyst than in the analyst’s public recommendations and reward the favor by voting for the analyst in the “star analyst” competition. This different information disclosure by analysts results in a form of information asymmetry, which incurs a significant cost on uninformed investors; among analysts’ positive recommendations, the stocks bought by the managers who vote for the analysts outperform the stocks sold by these managers around the recommendation dates.

Is There a Quid Pro Quo between Hedge Funds and Sell-Side Equity Analysts?

In this article, the authors posit a quid pro quo in economic benefits between sell-side equity analysts and large hedge fund managers. They show that large hedge funds opportunistically trade one to four days prior to the publication of a recommendation change, a finding consistent with flow of information from analysts to hedge funds. Next, the authors demonstrate that in return for the information provided, analysts benefit from (1) better external evaluations and (2) higher trading commissions and fees for their brokerage firm. Notably, pre-trading occurs only when the analyst issuing the recommendations has a high external evaluation and the analyst’s brokerage house is a prime broker to the hedge fund. TOPICS:Manager selection, fundamental equity analysis, portfolio construction

How Does Going Public Affect Employee Behavior? Evidence from Brokerage IPOs

This study examines the effects of initial public offerings (IPOs) by brokerages (henceforth, broker IPOs) on the objectivity of sell-side equity analysts employed by those brokers. Using a generalized difference-in-differences research design, we provide evidence that analysts produce more optimistically biased earnings forecasts relative to their peers following their employer’s IPO. We further find that the effect of broker IPOs on analysts’ forecast bias is more pronounced when analysts have greater economic incentives for optimistic bias. We also find that brokers hire more biased analysts following their IPOs. Our results are consistent with IPOs impacting individual non-executive employees by increasing the alignment of their incentives with those of the firm.

Noise from Other Industries: Overgeneralization and Analyst Belief

This paper provides evidence that individuals overweight recent experiences with one task when forming beliefs about other tasks, which I term overgeneralization. Using data on sell-side equity analysts and exploiting the diversity of their industry coverage, I show that analysts overgeneralize bad news from other coverage industries and make overpessimistic earnings forecasts for the focal firms. By comparing analysts who cover the same firm at the same time but experience different news from other industries, my empirical approach ensures that differences in firms' fundamentals cannot drive the results. Furthermore, I document that analyst overgeneralization has significant effects on the stock market: the resulting analyst disagreement increases trading volumes and return volatilities, and the resulting analysts' pessimism leads to temporary underpricing.

Do Associate Analysts Matter?

While extant literature investigates the role of sell-side equity analysts in capital markets, most studies do not consider that sell-side equity analysts often work in hierarchical teams. Lead analysts manage a team of associate and junior analysts who participate in the team’s tasks. Building on the delegation theory in the management literature, we hypothesize and find a division of labor between lead and associate analysts, where lead analysts are more likely to delegate tasks that are (1) less significant and (2) simpler, and when (3) the workload of the lead analyst increases, and (4) the associate analyst is more competent. Our results further suggest that associate analysts play a significant role in forecasting. In contrast, lead analysts are the main contributors to the qualitative aspects of analyst reports and are more likely to participate in earnings conference calls. Overall, our study documents the significant role of associate analysts in forecasting and the division of labor between lead and associate analysts.

Do Financial Analysts Fully Incorporate the Future Earnings Implications of Really Dirty Surplus into Their Earnings Forecasts?

This paper investigates whether sell-side equity analysts fully incorporate the future earnings implications of really dirty surplus (RDS) into their earnings forecasts. RDS refers to gains or losses from contingent equity transactions settled at prices other than the fair value. We find that analysts’ earnings forecasts are over-optimistic for firms with large RDS losses, RDS over-optimism is lower for firms with higher analyst following, and the over-optimism carries over to stock recommendations. Our findings suggest that the lack of fair value information in accounting records about the off-market settlement drives the RDS-related analyst over-optimism.

Biases in Analysts' Multiyear Forecasted Income Statements, Balance Sheets, and Cash Flow Statements

We evaluate sell-side equity analysts’ multiyear forecasted income statements, balance sheets and cash flow statements, and the profitability, efficiency and leverage ratios that they imply. Using both small- sample data extracted manually from Investext PDFs, and large-sample data taken from the I/B/E/S non-EPS archival detail history file, we find that analysts’ long-horizon financial statements contain many biases, many but not all of which are optimistic. Analysts make highly optimistic forecasts of long-horizon EPS, ROE, ROA, ROS and asset turnover, driven by overly bullish projections about revenues and all common-sized expenses except income tax, which they forecast pessimistically. Analysts are optimistic about both long-horizon operating cash flows and operating accruals, and while they are unbiased in their forecasts of long-horizon total assets, they underestimate long-horizon debt and overestimate long-horizon equity. Our regressions support the view that analysts strategically inflate their long-horizon forecasts of EPS the more intangible and hard-to-verify are the firm’s assets.