Analyst Target Prices Research Articles

The Effect of Dispersion on the Informativeness of Consensus Analyst Target Prices

Consensus analyst target prices are widely available online at no cost to investors. In this paper, we examine how the amount of dispersion in the individual target prices comprising the consensus affects the predictive association between the consensus target price and future returns. We find that returns implied by consensus target prices and realized future returns are positively correlated when dispersion is low, but they become highly negatively correlated when dispersion is high. Further analyses suggest that the differing effect of dispersion stems from incentive-driven staleness in price targets by some analysts after bad news. As a stock performs poorly and some analysts are slow to update their target prices, dispersion increases, and the consensus target price becomes too high. This has important implications for how consensus analyst target prices should inform investment decisions. We show that a hedge strategy taking a long (short) position in stocks with the highest predicted returns among stocks with the lowest (highest) dispersion earns more than 11% annually. Finally, we show that the negative correlation between consensus-based predicted returns and future realized returns for high-dispersion stocks exists mainly for stocks with high retail interest, suggesting that unsophisticated investors are misled by inflated target prices that are available freely online. This paper was accepted by Suraj Srinivasan, accounting. Funding: The authors acknowledge financial support from Indiana University and Yale University. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2021.03549 .

Consensus Analysts Target Price and Stock Price Returns in Nigeria

This study focuses on the effect of an Investment Valuation technique (Consensus Analysts Target Price) on Stock Price Return of listed companies in the Nigerian Exchange between the period of 2011 and 2023. The ex-post facto research design was employed in this research due to the use of historic (secondary) data from the selected fifteen (15) companies across 3 major sectors on the Nigeria Exchange (NGX). Panel autoregressive distribution lag model was the estimation techniques and inference made on 5% significance level. Prior to the data analysis, a number or pre-estimation test were carried out such as co-integration, homogeneity, and cross-sectional dependence in addition to basis correlation and descriptive analysis. Findings from the short run reveals a significant negative coefficient (-0.273) for lagged Stock Price Return (L.STR), indicating a substantial short-term correction effect. Conversely, the lagged Consensus Analyst Target Price (L.CATP) shows a positive coefficient (0.141) without statistical significance, suggesting a modest positive relationship without an immediate impact on Stock Price Return. Transitioning to the long run, the highly significant negative coefficient (-1.273) for long-run Stock Price Return (lr_STR) emphasizes a robust and persistent negative adjustment effect. Over an extended period, Consensus Analyst Target Price (lr_CATP) introduces a marginally significant positive coefficient (0.077), implying a modest positive impact on Stock Price Return. Based on the results, one recommendation concerning Consensus Analyst Target Price (CATP) and Stock Price Return is to exercise caution in relying solely on CATP for short-term decision-making. Investors should be aware that, in the short term, deviations from the lagged return may not be significantly influenced by CATP. Therefore, considering additional factors or indicators alongside CATP could enhance the accuracy of short-term decision-making in understanding stock price movements.

A multi-dimensional assessment of the accuracy of analyst target prices

This paper provides the first assessment for the quality of analyst target forecasts within an emerging market. We find that analysts' target forecasts tend to commit systematically upward bias (9.4%), large absolute pricing error (24.8%), over-prediction of the actual price changes (21%), and a low proportion (54%) of correct directional forecasts. The forecasting quality decays over time as the information in the target prices becomes obsolete, long before the one-year expiry period indicated in the analyst reports. Nevertheless, analysts’ target forecasts consistently outperformed alternative forecasts generated solely based on historical data, which confirms the price discovery function of analyst forecasting. A number of factors are found to be influential to the target performance. Target quality is adversely associated with stock idiosyncratic risk, prior index volatility, the aggressiveness of the target forecasts, and the optimism of consensus targets. In addition, more accurate target prices are delivered by brokerages that have prior experience with the industry and the companies under review, but not by brokerages that possess monopoly power on the stock-specific information.

Analyst herding – whether, why, and when? Two new tests for herding detection in target forecast prices

This study proposes two novel tests for security analyst herding based on binomial correlation and forecast error volatility scaling and applies it to investigate herding patterns in analyst target prices in 2008-2020 in the UK. Analysts robustly herd in their valuations, with results consistent across years, sectors, in panel fixed effect, quantile, instrumental variable regressions, and when controlled for optimism and conservatism. Herding becomes prominent for stocks followed by at least five analysts and towards the long sides of Fama-French sorts, reinforcing its non-spurious and behavioral nature. Analyst herd more strongly subject to low volatility and uncertainty.

Analyst target price and dividend forecasts and expected stock returns

This paper examines whether adding expected dividend yields implied by analyst dividend forecasts to expected capital gains implied by analyst target prices improves the portfolio strategy of buying stocks with the highest expected returns and selling stocks with the lowest expected returns. We find that the strategy based on the expected total returns performs only slightly better at the 1-month horizon because the short-term return predictability of the expected dividend yield is weak. We find that the strategy generates significant abnormal returns regardless of sorting the stocks universally or within industries, although sorting stocks within industries improves the performance.

Analyst target price revisions and institutional herding

We document that institutional herding behavior is associated with analyst target price revisions even after controlling for the effects of analyst recommendations and earnings forecasts, and provide insights into the price impact of institutional herding. Institutional investors tend to buy the same stocks following an upward target price revision and sell the same stocks following a downward price revision. Moreover, institutional investors tend to overreact to analysts' target price revisions, which exacerbates the mispricing in the stock market. Such price destabilizing effect is particularly pronounced for herding among investment firms.

Betting against analyst target price

Using a robust measure that captures the market’s reaction to analysts’ target price releases, we show that the initial stock price reaction corresponds to target prices, but the price drifts in the opposite direction for a long period, resulting in negative cross-sectional predictability. In the U.S. market from 1999 to 2020, the derived long-short portfolio generates a significant one-month ahead return of 0.75% and 10.00% over a year and possesses favorable features: its profit is higher among large and liquid stocks, originates from long positions, and lasts long. Empirical evidence suggests that the return reversal is caused by both discount rate shifts and mispricing correction following target price releases.

The information content of target price forecasts: Evidence from mergers and acquisitions

AbstractThis paper investigates the informativeness and value relevance of analyst target prices in the context of mergers and acquisitions. Our results indicate that firms with high 12‐month ahead target prices relative to current stock prices are more likely to become a takeover target and offer premium, and acquirers’ announcement returns are positively associated with firms’ target price premium. We also show that a long‐short trading strategy formed on target prices and firms’ takeover likelihood generates economically significant returns. Our results are robust to a battery of additional analysis, and the informativeness of target prices is not subsumed by other analyst forecast outputs such as earnings forecasts and recommendations. Overall, our findings suggest that analysts convey valuable information through target price forecasts, which are useful for participants in the corporate takeover markets.

Does Wall Street Discriminate by Race? Evidence from Analyst Target Prices

Does Wall Street Discriminate by Race? Evidence from Analyst Target Prices

Does foreign exchange risk matter to equity research analysts when forecasting stock prices? Evidence from U.S. firms

We study the relationship between the foreign exchange risk and analyst target price forecast error using U.S. firm-level data for the sample period between 1999 and 2014. We find that the target price forecast error is higher when foreign exchange risk is higher. The relationship is stronger for smaller firms and less pronounced among financial firms. Collectively, the findings suggest that analysts make fewer errors when forecasting for firms that are more capable of managing foreign exchange risks. These findings imply that either analyst does not make a significant effort in incorporating foreign exchange risk into their forecast models, or they do not have the skills for that task.

애널리스트의 목표주가 변경은 투자자들에게 유용한 정보인가?

애널리스트의 목표주가 변경은 투자자들에게 유용한 정보인가?

The Information Content of Target Price Forecasts: Evidence from Mergers and Acquisitions

This paper investigates the informativeness and value relevance of analyst target prices in the context of mergers and acquisitions (M&A). Our results indicate that firms with high 12-month ahead target prices relative to current stock prices are more likely to become a takeover target and offer premium and acquirers’ announcement returns are positively associated with firms’ target price premium. We also show that a long-short trading strategy formed on target prices and firms’ takeover likelihood generates economically significant returns. Our results are robust to a battery of additional analysis, and the informativeness of target prices is not subsumed by other analyst-forecast outputs such as earnings forecasts and recommendations. Overall, our findings suggest that analysts convey valuable information through target price forecasts, which are useful for participants in the corporate takeover markets.

Consensus Analyst Target Prices: Information Content and Implications for Investors

Consensus analyst target prices are widely available online at no cost to investors. In this paper we consider whether these consensus target prices are informative for predicting future returns. We find that when considered in isolation, consensus target prices are not generally informative about future returns. However, we find that the dispersion of individual analysts’ target prices that comprise the consensus is an important moderating factor. When dispersion is low (high), there is a strong positive (negative) correlation between predicted returns based on the consensus target price and future realized returns. Further analyses suggest that this phenomenon is partially due to consensus target prices being slow to reflect bad news. In addition, we show that the negative correlation between consensus-based predicted returns and future realized returns for high-dispersion stocks exists only for stocks with high short interest or low institutional ownership, suggesting that limits to arbitrage play a role in the observed mispricing and that unsophisticated investors are negatively impacted by high consensus target prices.

Do Analysts’ Cash Flow Forecasts Improve Their Target Price Accuracy?

ABSTRACTThe literature on the usefulness of analysts’ cash flow forecasts is unsettled, with Call et al. (), Mohanram (), and Radhakrishnan and Wu () providing evidence in favor of their usefulness, and Givoly et al. (), Bilinski (), and Ecker and Schipper () questioning this. Target prices provide a good setting to test the usefulness of cash flow forecasts because they are an ultimate output of an analyst's valuation process to which cash flow forecasts are an input. Moreover, studying the effect of cash flow forecasts on target prices is more relevant for assessing their usefulness than is studying their effect on earnings‐forecast accuracy, as the accuracy of target prices requires a comparison with market prices, which are less subject to management influence than reported earnings. By improving an analyst's understanding of unexpected accruals and permanent earnings, a cash flow forecast can increase an analyst's target price accuracy and signal an analyst's superior forecasting ability. We examine whether, conditional on their earnings forecasts, analysts’ cash flow forecasts improve their target price accuracy. We find that when analysts issue cash flow forecasts, their target price accuracy increases. We also find that this accuracy increases with the accuracy of their cash flow forecasts. Finally, we find that this increased target price accuracy is greater for more challenging‐to‐value firms. Our study provides confirmatory evidence of the usefulness of analysts’ cash flow forecasts.

Factors Mitigating Firm-specific Information Asymmetry and Target Price Accuracy in India

Executive Summary Over the last decade, efforts have been made to improve the quality of financial reporting and corporate governance standards prevailing in emerging markets. Even after 20 years of globalization, emerging markets continue to trade as a separate class ( Bekaert & Harvey, 2014 ). On account of a weak regulatory environment, firm-specific information asymmetry is expected to be on the higher side as compared to developed markets. In such an environment, any factors which mitigate information asymmetry may help improve efficiency of information providers such as equity research analysts. The role of equity research analysts is to process financial information and provide estimates which may be used by investors to make informed investment decisions. This study investigates whether the factors which mitigate firm-specific information asymmetry improve analyst target price accuracy in India. We expect sophisticated financial intermediaries such as equity research analysts to produce more accurate target price forecasts for firms with higher frequency of corporate announcements, higher analyst coverage, and higher foreign institutional holdings. Past research suggests that these three factors reduce information asymmetry and this reduction could possibly help analysts produce superior results. Our results show that higher frequency of corporate announcements creates short-term noise which reduces target price accuracy at the end of one-year forecast horizon. Our findings reveal that higher analyst coverage leads to better flow of firm-specific private information and improves target price accuracy anytime during or at the end of one year. We report that higher foreign institutional holding possibly improves stock liquidity, attracting more traders, which eventually leads to better target price accuracy at the end of forecast horizon. Our key finding is that there is a reduction in firm-specific information asymmetry due to the presence of more number of analysts and higher percentage of institutional holding.

The economic consequences associated with integrated report quality: Capital market and real effects

The International Integrated Reporting Council's Framework identifies two goals for integrated reporting: improved information for outside providers of financial capital and better internal decision making. We extend prior research that finds a positive association between integrated report quality (IRQ) and firm value by examining two channels through which this association may arise—a capital market channel and a real effects channel. To conduct these tests, we disaggregate firm value into three components: liquidity, cost of capital, and expected future cash flows. Using data from South Africa where integrated reporting is mandatory and an IRQ measure based on proprietary EY data, we find a positive association between IRQ and liquidity, which supports the capital market channel. We find no evidence of a relation between IRQ and cost of capital. We also find a positive association between IRQ and expected future cash flows. Because this association could reflect better investor cash flow forecasts—a capital market effect, better internal decisions—a real effect, or both, we attempt to distinguish these explanations. We find higher IRQ is (not) associated with higher realized future operating cash flows (greater analyst target price forecast accuracy), and find higher IRQ is associated with higher investment efficiency. These findings support the real effects channel. Together, our findings are consistent with integrated reporting achieving its dual objective of improved external information and better internal decisions.

The impact of country-level corporate governance on analyst boldness and performance with target price forecasts

This study investigates the impact of country-level corporate governance on analyst boldness and performance with target price forecasts in Asian markets. Results suggest that analysts working in countries with better corporate governance standards have higher boldness with target price forecasts reflecting higher confidence in a more transparent environment. However, the study fails to establish a consistent relationship between country-level corporate governance and analyst performance with target price forecasts. The positive effects of better country-level corporate governance on analyst target price performance are visible only in the short-term and not at the end of the forecast horizon of one year. Past studies document a positive relationship between analyst accuracy and better corporate governance in western markets; we find partial evidence of the benefits of better country-level corporate governance on analyst target price performance in Asian markets.

Do analysts cater to investor beliefs via target prices

This study examines analyst target price bias within the framework of catering theory. Given that analyst catering is more probable when the clients of the analyst forecasts are less sophisticated investors who are less likely detect it, we focus on a unique stock market where individual investors rather than institutions are the predominant group and account for 75% of the total security trading. Our results show that analysts do cater to investors via overshooting actual end-of-forecast-period prices even after controlling market sentiment index, analyst and company characteristics. Furthermore, results show that foreign analysts produced more biased target prices compared to domestic peers.

Strategic Distortions in Analyst Target Prices in the Presence of Short-Term Institutional Investors

Strategic Distortions in Analyst Target Prices in the Presence of Short-Term Institutional Investors

Separating the Wheat from the Chaff: Identifying the Signal and Predictable Error Components of Target Price Forecasts

Using the analytical framework originated in Campbell and Shiller (1988), we show that target price implied returns are a function of expected dividends, analysts’ private information about future stock returns, and errors with respect to forecasting cash flows and discount rates. Our empirical application of the model explains approximately 24 percent of the cross-sectional variation in target price implied returns, of which around eight percent is explained by analysts’ information about expected dividends and future stock returns. We also find that analyst errors in assessing the returns to risk are more important than poor fundamental forecasts or badly aligned economic incentives in explaining the cross-sectional variation in implied returns. We then use the model to decompose target price implied returns into a signal and a predictable error component. The results show that the signal component is positively associated with future returns over short time horizons (the following two months), while the predictable error component is negatively associated with future returns up to at least six months. Two trading strategies based on the two components earn abnormal returns of 74 to 113 basis points per month. These results suggest that investors fail to react efficiently to the signal and the predictable noise components of analyst target price forecasts.