证券分析师VS统计模型:证券分析师盈余预测的相对准确性及其决定因素

本文使用2005年35家券商对我国上市公司做出的每股盈余预测数据,考察了证券分析师盈余预测相对于统计模型的相对准确性及其决定因素。我们发现,我国证券分析师做出的盈余预测,同以年度历史数据为基础的统计模型得出的盈余预测相比,预测误差较小,证券分析师盈余预测具有一定的优势;但同某些以季度历史数据为基础的统计模型得出的盈余预测相比,预测误差较大,证券分析师盈余预测不具有优势。我们同时考察了决定证券分析师盈余预测相对准确性的决定因素。我们发现,公司每股盈余的波动性越大,公司上市越晚,跟踪公司的分析师越多,证券分析师的优势就越大。我们的研究对证券分析师以及投资者都有一定的启示作用。     

Financial Analyst Characteristics and Herding Behavior in Forecasting

This study classifies analysts' earnings forecasts as herding or bold and finds that (1) boldness likelihood increases with the analyst's prior accuracy, brokerage size, and experience and declines with the number of industries the analyst follows, consistent with theory linking boldness with career concerns and ability; (2) bold forecasts are more accurate than herding forecasts; and (3) herding forecast revisions are more strongly associated with analysts' earnings forecast errors (actual earnings—forecast) than are bold forecast revisions. Thus, bold forecasts incorporate analysts' private information more completely and provide more relevant information to investors than herding forecasts.     

The accuracy of IPO earnings forecasts in Thailand and their relationships with stock market valuation

In order to help reduce information asymmetry between managers and prospective investors, IPO prospectuses in Thailand are required to publish managers' forecasts of the forthcoming year's earnings. This type of direct disclosure is especially important in a developing economy such as Thailand where financial intermediaries and information vendors are relatively sparse, and where investors are rarely professionals. Our results demonstrate that managers' earnings forecasts are much more accurate than extrapolations of historical earnings. We show that forecast accuracy is related to underpricing, and it has a directional, but not statistical, association with one-year stock returns and one-year wealth relatives.     

Management Forecast Consistency

We posit that management forecasts, which are predictable transformations of realized earnings without random errors, are more informative than unbiased forecasts, which manifest small but unpredictable errors, even if biased forecasts are less accurate. Consistent with this intuition, we find that managers who make consistent forecasting errors have a greater ability to influence investor reactions and analyst revisions, even after controlling for the effect of accuracy. This effect is more economically significant and statistically robust than that of forecast accuracy. More sophisticated investors and experienced analysts are found to have a better understanding of the benefits of consistent management forecasts.     

The Effect of Issuing Biased Earnings Forecasts on Analysts' Access to Management and Survival

This study offers evidence on the earnings forecast bias analysts use to please firm management and the associated benefits they obtain from issuing such biased forecasts in the years prior to Regulation Fair Disclosure. Analysts who issue initial optimistic earnings forecasts followed by pessimistic earnings forecasts before the earnings announcement produce more accurate earnings forecasts and are less likely to be fired by their employers. The effect of such biased earnings forecasts on forecast accuracy and firing is stronger for analysts who follow firms with heavy insider selling and hard‐to‐predict earnings. The above results hold regardless of whether a brokerage firm has investment banking business or not. These results are consistent with the hypothesis that analysts use biased earnings forecasts to curry favor with firm management in order to obtain better access to management's private information.     

Model-based earnings forecasts vs. financial analysts' earnings forecasts

Existing accounting-based forecasting models of earnings either do not fully consider information that is contained in stock prices or use an ad hoc specification that is not based on rigorous valuation theory. In this paper, we develop an earnings forecasting model built on the theoretical linkages between future earnings and stock prices as well as a number of accounting fundamental variables. We find that our model-based forecasts of earnings are in general less biased and more accurate than both existing model-based forecasts and analysts' consensus forecasts, at both shorter and longer horizons. We also show that the accuracy of both model-based forecasts and financial analysts' forecasts depend on firm-specific characteristics such as firm size and industry membership.     

Market implied future earnings and analysts’ forecasts

This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.     

Long-Term Earnings Forecasts in the Electric Utility Industry: Accuracy and Valuation Implications

This paper integrates research on the accuracy of alternative long-term earnings forecasts, the gain in accuracy achievable from combining various forecasts, and the power of different long-term earnings forecasts to explain stock prices. The tests are performed on 82 electric utility firms because of the relative homogeneity of accounting data in that industry and because of the importance of the findings for the determination of the cost of capital in a regulatory proceeding. The results are consistent with earlier research findings that analyst forecasts of long-term earnings growth are more accurate than forecasts from extrapolative models. Combined forecasts applied to out-of-sample data, however, did not result in markedly improved forecasting accuracy. Finally, valuation tests of alternative forecasting techniques offered strong evidence that investors place the greatest weight on forecasts from Value Line.     

Determinants of analysts’ revenue forecast accuracy

This study investigates financial analysts’ revenue forecasts and identifies determinants of the forecasts’ accuracy. We find that revenue forecast accuracy is determined by forecast and analyst characteristics similar to those of earnings forecast accuracy—namely, forecast horizon, days elapsed since the last forecast, analysts’ forecasting experience, forecast frequency, forecast portfolio, reputation, earnings forecast issuance, forecast boldness, and analysts’ prior performance in forecasting revenues and earnings. We develop a model that predicts the usefulness of revenue forecasts. Thereby, our study helps to ex ante identify more accurate revenue forecasts. Furthermore, we find that analysts concern themselves with their revenue forecasting performance. Analysts with poor revenue forecasting performance are more likely to stop forecasting revenues than analysts with better performance. Their decision is reasonable because revenue forecast accuracy affects analysts’ career prospects in terms of being promoted or terminated. Our study helps investors and academic researchers to understand determinants of revenue forecasts. This understanding is also beneficial for evaluating earnings forecasts because revenue forecasts reveal whether changes in earnings forecasts are due to anticipated changes in revenues or expenses.     

The accuracy of analysts' dividend forecasts around the world

We examine the link between the accuracy of consensus analysts' dividend forecasts, earnings predictability and dividend policies of firms in 39 countries from 1995 to 2004. For firms that display stronger dividend smoothing, as modeled by Lintner [Lintner, J., 1956. Distribution of incomes of corporations among dividends, retained earnings and taxes. American Economic Review 46, 97–113], there is a lower correlation between dividend and earnings forecast errors, with less of the earnings uncertainty being passed into dividend uncertainty. The link between earnings and dividend forecast errors is weaker in common-law, capital market-based countries and in countries with well-developed financial (debt and equity) markets, where firm managers have greater incentives to smooth dividends and to use dividends for signaling.     

Do Managers Always Know Better? The Relative Accuracy of Management and Analyst Forecasts

We examine the relative accuracy of management and analyst forecasts of annual EPS. We predict and find that analysts’ information advantage resides at the macroeconomic level. They provide more accurate earnings forecasts than management when a firm's fortunes move in concert with macroeconomic factors such as Gross Domestic Product and energy costs. In contrast, we predict and find that management's information advantage resides at the firm level. Their forecasts are more accurate than analysts’ when management's actions, which affect reported earnings, are difficult to anticipate by outsiders, such as when the firm's inventories are abnormally high or the firm has excess capacity or is experiencing a loss. Although analysts are commonly viewed as industry specialists, we fail to find evidence that analysts have an information advantage over managers at the industry level. The two have comparable abilities to forecast earnings for firms with revenues or earnings that are more synchronous with their industries.     

Analysts' Forecasts Following Forced CEO Changes

This paper examines analysts' earnings forecasts during the period of uncertainty following a change of chief executive officer (CEO). It distinguishes between forced and non‐forced CEO changes, and examines whether analysts utilize their information advantage to reduce the heightened uncertainty of a forced change of CEO. Examining a sample of Australian companies followed by analysts between 1999 and 2009, we find that forecasting accuracy is lower and earnings forecasts are more optimistic for firms experiencing forced CEO turnover compared to firms not undergoing such a change. However, dispersion is not statistically different. The results suggest that forced CEO turnover events provide a challenge to the forecasting environment for analysts. During CEO changes, investors should be aware that forecasts are less accurate and have an optimistic bias.     

Group-Affiliated Analysts’ Strategic Forecasts During a Year: Evidence from Korea

In examining the family-controlled business groups in Korea, prior literature shows that group-affiliated analysts’ forecasts are optimistically biased. This article investigates whether the group-affiliated analysts strategically time the level of accuracy and bias in their forecasts for the same group-affiliated firms due to the change in information asymmetry in the market. The results show that the group-affiliated analysts issue more accurate and less optimistic earnings forecasts for the affiliated firms when the level of information asymmetry is low; particularly, in April, which is right after annual earnings announcements.     

Underwriting relationships,analysts' earnings forecasts and investment recommendations

We examine the effect of underwriting relationships on analysts' earnings forecasts and recommendations. Lead and co-underwriter analysts' growth forecasts and recommendations are significantly more favorable than those made by unaffiliated analysts, although their earnings forecasts are not generally greater. Investors respond similarly to lead underwriter and unaffiliated `Strong buy' and `Buy' recommendations, but three-day returns to lead underwriter `Hold' recommendations are significantly more negative than those to unaffiliated `Hold' recommendations. The findings suggest investors expect lead analysts are more likely to recommend `Hold' when `Sell' is warranted. The post-announcement returns following affiliated and unaffiliated analysts' recommendations are not significantly different.     

THE RELATION AMONG DIVIDEND POLICY,FIRM SIZE,AND THE INFORMATION CONTENT OF EARNINGS ANNOUNCEMENTS

In this paper we investigate the role of dividends in explaining the size effect. The previous literature concludes that before the firm's earnings announcement, small firm stock prices impound less information than large firm stock prices. This size effect is evidenced by the greater market reaction to small firm earnings announcements than to large firm earnings announcements. We find that if the dividend announcement precedes the earnings announcement, no size effect exists. The implication is that the information conveyed by dividend announcements includes the information conveyed to investors in large firms by other information sources. However, if the firm does not pay dividends or if the firm's earnings announcement precedes its dividend announcement, the size effect exists. The implication is that dividends do not completely explain the size effect. That is, there are information sources other than dividends that are exclusively available to investors in large firms, and the information provided by these sources is reflected in the stock price of large firms before the earnings announcement.     

Analysts' forecasts as earnings expectations

I examine three composite analyst forecast of earnings per share as proxies for expected earnings. The most current forecast weakly dominates the mean and median forecasts in accuracy. This is evidence that forecast dates are more relevant for determining accuracy than individual error. Consistent with previous research, I find analysts more accurate than time-series models. However prior knowledge of forecast errors from a quarterly autoregressive model predicts excess stock returns better than prior knowledge of analysts' errors. This is inconsistent with previous research, and is anomalous given analysts' greater accuracy.     

Are analysts’ earnings forecasts more accurate when accompanied by cash flow forecasts?

We examine whether analysts’ earnings forecasts are more accurate when they also issue cash flow forecasts. We find that (i) analysts’ earnings forecasts issued together with cash flow forecasts are more accurate than those not accompanied by cash flow forecasts, and (ii) analysts’ earnings forecasts reflect a better understanding of the implications of current earnings for future earnings when they are accompanied by cash flow forecasts. These results are consistent with analysts adopting a more structured and disciplined approach to forecasting earnings when they also issue cash flow forecasts. Finally, we find that more accurate cash flow forecasts decrease the likelihood of analysts being fired, suggesting that cash flow forecast accuracy is relevant to analysts’ career outcomes.     

Management Guidance Pre‐ and Post‐Restatement

We examine whether the quality of restating firms’ management guidance differs in periods before and after restatement announcements. While characteristics of restating firms and the consequences of restatement have been a central topic in accounting and auditing research, the quality of management guidance around restatements is less well understood. We consider two competing characterizations of the link between management forecast accuracy and bias and restatement (an event that tends to signal poor financial controls): “Forecast–Opportunism Explanation” and “Forecast–Ability Explanation”. Under the Forecast–Opportunism Explanation, pre‐restatement weaknesses in financial controls enable managers to manipulate earnings toward forecasts and to meet or exceed opportunistically biased forecasts, and the post‐restatement strengthening of financial controls constrains opportunistic behavior. Under the Forecast–Ability Explanation, pre‐restatement weaknesses in financial controls impede managers’ ability to issue accurate forecasts, and post‐restatement improvements remove impediments so that the accuracy of forecasts improves; forecast bias remains unaffected. Evidence indicates that before a restatement, restating firms’ forecasts are more accurate and relatively more downwardly biased than control firms’ forecasts. Post‐restatement, restating firms have less accurate and less downwardly biased management guidance. Our overall results are consistent with the Forecast–Opportunism Explanation.     

Value relevance of analyst earnings forecasts in emerging markets

Even though research in accounting and finance has extensively examined the role of financial analysts in developed economies, this issue has not been thoroughly examined in an emerging market setting. In this paper, I examine whether, following a market opening, analyst forecast accuracy and the market's reliance on analyst forecasts increase with time. Accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience. Results indicate that time is positively related to analyst forecast accuracy after controlling for a number of other firm and country characteristics. Second, I posit that time should also be related to the market's propensity to use analyst forecasts to form earnings expectations. As markets open and investors become more sophisticated, the reliance on analyst forecasts should also increase. Results are consistent with this expectation. In particular, I find that in the first sub-period earnings expectations based on random walk exhibit greater relative information content than earnings expectations based on analyst forecasts. This pattern is reversed in the third sub-period where analyst forecast errors better explain returns. Incremental information content tests produce similar results. Future research should further investigate the relation between financial analysts and other important market characteristics in emerging economies.     

Sell on the news: Differences of opinion,short-sales constraints,and returns around earnings announcements

Miller [1977. Risk, uncertainty, and divergence of opinion. Journal of Finance 32, 1151–1168] hypothesizes that prices of stocks subject to high differences of opinion and short-sales constraints are biased upward. We expect earnings announcements to reduce differences of opinion among investors, and consequently, these announcements should reduce overvaluation. Using five distinct proxies for differences of opinion, we find that high differences of opinion stocks earn significantly lower returns around earnings announcements than low differences of opinion stocks. In addition, the returns on high differences of opinion stocks are more negative within the subsample of stocks that are most difficult for investors to sell short. These results are robust when we control for the size effect and the market-to-book effect and when we examine alternative explanations such as financial leverage, earnings announcement premium, post-earnings announcement drift, return momentum, and potential biases in analysts’ forecasts. Also consistent with Miller's theory, we find that stocks subject to high differences of opinion and more binding short-sales constraints have a price run-up just prior to earnings announcements that is followed by an even larger decline after the announcements.