Impact Of Analysts Research Articles

The Impact of Analysts' Forecast Behavior on Companies

As an important information intermediary between public companies and investors, analysts are gaining an increasingly significant position in the capital market. They make use of their expertise and professional skills to interpret and analyze market information, and lead investors to make decisions by writing research reports. Hence, it is vitally essential for analysts to forecast relevant events or market participants’ behaviors correctly and accurately in the investment process of the market. Excessive deviation from the forecasts may damage the interests of investors and contribute to a bubble in the capital market. This paper focuses on the factors affecting analysts' forecast accuracy, such as analysts' valuation model selection preferences, systematic optimism bias, information disclosure quality, etc. By systematically combing the remarkable literature on analysts' forecasting behaviors and influences, this paper summarizes the impacts of both analysts' forecasting behaviors and the prediction accuracy on firms' share prices, investments and innovations, as well as puts forward suggestions for analysts themselves and for regulatory.

Security Analysts’ Site Visits and Stock Price Synchronicity

AbstractThis paper investigates how security analysts’ corporate site visits impact listed firms’ stock‐price informativeness. Examining a sample of security analysts’ visits to Chinese listed firms from 2010 to 2019, we find that security analysts incorporate firm‐specific information into share prices through site visits, significantly reducing the visited firms’ stock price synchronicity. This finding is robust to an alternative measure of stock price informativeness and a two‐stage least‐squares approach using the introduction of high‐speed rail as the instrumental variable. We also find that the impact of analysts’ site visits on firms’ stock price synchronicity is more pronounced for firms with lower information disclosure quality and poor corporate governance than for other firms. Further analysis on firm characteristics documents that this effect is stronger for large‐size firms, firms in the manufacturing industry, and state‐owned enterprises.

Does the market reward meeting or beating analyst earnings forecasts? Empirical evidence from China

PurposeUsing a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).Design/methodology/approachThe authors use an event study methodology to capture market reactions to MBE.FindingsThe authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.Research limitations/implicationsThe authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.Practical implicationsThe findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.Originality/valueThe authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

The short-term impact of analyst recommendations: evidence from the Indian stock market

Purpose This study aims to evaluate the short-term impact of brokerage analysts’ recommendations on abnormal returns using a sample selected from the S&P BSE 100 in the Indian context. The efficient market hypothesis, specifically, its semi-strong form, is tested for “Buy” stock recommendations published in the electronic version of Business Standard. The crucial issue is, are there any abnormal returns that can be earned following a recommendation? If so, how quickly do prices incorporate the information value of these recommendations? It tests the impact of analyst recommendations on average abnormal returns (AARs) and standardized abnormal returns (SRs) to determine their statistical significance. Design/methodology/approach Using a sample of stock recommendations published in the e-version of Business Standard, the event study methodology is used to determine whether AARs and SRs are significantly different from zero for the duration of the event window by using several significance tests. Findings The findings indicate a marginal opportunity for profit in the short term, restricted to the event day. However, the effect does not persist, i.e. the market is efficient in its semi-strong form implying that investors cannot consistently earn abnormal returns by following analysts’ recommendations. Post the event date, the market reaction to analyst recommendations becomes positive, however, insignificant until the ninth day after the recommendation providing support to the underreaction hypothesis given by Shliefer (2000) and post-recommendation price drift documented by Womack (1996). The study contributes by using different statistical tests to determine the significance of returns. Practical implications There are important implications for traders, investors and portfolio managers. The speed with which market prices incorporate publicly available information is useful in formulating trading strategies. However, stock characteristics such as market capitalization, volatility and level of analyst coverage need to be incorporated while making investment decisions. Originality/value The study contributes by using different statistical tests to determine the significance of returns.

Do financial analysts discourage or encourage corporate fraud? Empirical evidence from China

Purpose This paper aims to focus on the role of financial analysts in corporate fraud in the Chinese stock market. Design/methodology/approach Data on the analyst coverage and all the types of corporate fraud were obtained for 16,284 company-year observations of Chinese companies. The sample was subsequently divided into those of state-owned enterprises, before and after financial crisis. Findings The overall results indicate that analyst coverage effectively deters the occurrence of fraud. The sub-sample results suggest that the impact of analysts on deterring fraud is more pronounced in non-state-owned enterprises, especially after the financial crisis. The path analyses show that analyst coverage can deter corporate frauds by affecting information transparency and investor attention. Furthermore, the results show that the deterrence role of financial analysts varies with fraud types: it is more pronounced in deterring disclosure fraud, but not as effective in illegal guarantees and illegal insider dealing. Moreover, analyst coverage can deter the occurrence of fictitious reporting, intentional postponement and material omission. Originality/value This paper not only examined the overall fraud probability but also taking into consideration the heterogeneity of the information availability and research focus of financial analysts and examined the analysts’ impact on the occurrence of difference types of fraud. Moreover, this paper explored why financial analysts can deter corporate frauds through path analyses.

The Impact of Analysts on the Slack in Management Earnings Forecasts

The Impact of Analysts on the Slack in Management Earnings Forecasts

Beating Market Expectations, Analysts’ Forecasts Dispersion and the Pricing of Credit Default Swaps

The purpose of this paper is to study the impact of beating analysts’ forecasts and the impact of analysts’ forecast dispersion on the pricing of firms’ credit default swaps (CDSs). CDS premium is the compensation required by investors for bearing firms’ credit default risk. Sell-side analysts collect market, industry and firm information and provide important information in the form of stock recommendations, stock price targets and accounting number forecasts. For that reason, the information contained in their forecasts may provide additional information to investors to price CDSs. My results show that firms that beat analysts’ earnings and revenue forecasts, and firms with less dispersed analysts’ earnings and revenue forecasts have on average a reduction in their CDS premia around the earnings announcement date. These effects are stronger for firm that jointly beat the two forecasts and for firms with high risk of default. I also document that the effect of beating analysts’ earnings (revenue) forecasts is stronger for firms with more (less) earnings quality.

Entrepreneurship and Economic Change in a Developing Region: Opportunities and Challenges in Africa

The Impact of Analysts’ Recommendations on the Cost of Debt: International Evidence Dr. Satt Harit Abstract We documentthe link between analysts’ reviews and bonds ratings. This study took 12 years and was carried out on samples obtained from 26 countries. The focus is to point out the positive relationship between analysts’ reviews commendations and bonds ratings. Thus, a probit regression analysis was done for this purpose. It was strongly noted that there is a great connection between the recommendation and the bond’s rating. In other words, the more a company receives positive recommendations from financial analysts, the rating of its bonds increases. More verification to the creditors’ rights shields was included through our outcomes, plus its impact on debt cost. Full Text: PDF DOI: 10.15640/rcbr.v4n2a2

Impact of Analysts' Recommendations on Stock Prices: Evidence from Karachi Stock Exchange

This study analyzes the impact of analysts’ recommendations on stock prices in the Karachi Stock Exchange (KSE) using the Morning Shout, a report published daily by Khadim Ali Shah Bukhari Securities Ltd (KASB) which includes buy and sale recommendations about different stocks. Using event study methodology, a sample period of 2 years and 277 recommendations were analyzed. Market model is used to estimate abnormal returns for stocks around the recommendation dates. Results of the study indicate that analysts’ recommendations do create positive abnormal returns for investors and these abnormal returns are the result of the information content. Results show that stocks earned on average 0.41% abnormal return on the day of publication of recommendations and continued to earn abnormal returns till the 10th day of publication of recommendations. Further analysis shows that there is a possibility of information leakage prior to the publication of recommendations, as these securities earned positive abnormal returns prior to the publication of Morning Shout.

Discussion of The Impact of Analysts' Forecast Errors and Forecast Revisions on Stock Prices

<i>Discussion of</i> The Impact of Analysts' Forecast Errors and Forecast Revisions on Stock Prices

The Impact of Analysts' Forecast Errors and Forecast Revisions on Stock Prices

Abstract: We present a comprehensive analysis of the association between stock returns, quarterly earnings forecast errors, and quarter‐ahead and year‐ahead earnings forecast revisions. We find that forecast errors and the two forecast revisions have significant effects on stock prices, indicating each conveys information content. Findings also show that the fourth quarter differs from other quarters—the relative importance of the forecast error (quarter‐ahead forecast revision) is lower (higher). We also find a marked upward shift over time in the forecast error and forecast revision coefficients, consistent with the I/B/E/S database reflecting an improved quality of both earnings forecasts and actual earnings.

Impact of Analysts' Recommendations on Stock Performance

This paper examines the effect of analysts' recommendations on stock return, volume and volatility. The study covers a sample of 36 large cap stocks traded on the US stock market over the period June 1997–May 2003. The empirical evidence suggests a significant impact of analysts' recommendations on the stock market. The research considers market microstructure and looks at the motivation and behaviour of analysts.

Impact of analysts' theories

Impact of analysts' theories

A new beta incorporating analysts' forecasts

T he standard beta risk measure, based on historical data, is unable to account for the superior returns on small firms or for the returns on securities neglected by analysts. The superior risk-adjusted returns on small firms were first rigorously documented by Banz [1981] and Keim [1982], while the returns on neglected firms were reported by Arbel and Strebel [1982]. When we compute the standard beta, the historical return distributions are employed without modification as the best estimate of investors’ future expectations. The standard measurement of beta makes no allowance for the information contained in analysts’ forecasts, or for estimation risk in general. Thus, it gives no attention to the impact of analysts’ forecasts on investors’ expectations concerning the future volatility of returns, nor does it take account of instability in the historical return time series. These factors are not critical in the case of large, highly researched firms with relatively stable return data, where beta provides a reasonable estimate of future risk. For small neglected firms, however, the historical measurement of anticipated risk may be grossly inaccurate. We present a new beta derived from a respecified capital asset pricing model (CAPM), incorporating the information contained in analysts’ forecasts by allowing for uncertainty in the mean of the expected return distribution. The conceptual basis of the new beta is described in the next section. We then use a sample of 660 securities to test the new beta relative to the old beta in terms of its ability to 81