Long-term Earnings Forecasts Research Articles

Do financial analysts publish long-term forecasts in response to firms’ overinvestments?

ABSTRACT This study examines the relationship between analysts issuing long-term earnings forecasts and firms overinvestment. This research demonstrates that a positive relationship exists between analysts issuing long-term forecasts and firms overinvesting. The relationship between analysts issuing a long-term forecast and firms overinvesting is more significant where asymmetry of information exists. Additionally, we find that a positive relation between overinvestments and long-term analyst forecast publications is more pronounced for firms covered by competent analysts. Finally, analysts benefit from promotion by issuing long-term forecasts in response to the firms’ overinvestment. These findings contribute to the related literature by confirming that investment decisions are considered important in analysts’ long-term earnings forecasts.

Macroeconomic outlook optimism and analysts’ four-quarter-ahead quarterly earnings forecast optimism*

ABSTRACT We examine the relationship between the long-run macroeconomic outlook and four-quarter-ahead quarterly earnings forecasts and find that the four-quarter-ahead quarterly earnings forecasts are more optimistically biased in periods when the four-quarter-ahead quarterly macroeconomic forecasts are optimistically biased as well. This relationship is stronger when forecasts are for periods that turn out to be recessionary, which is attributable to all forecasters’ inability to predict recessions. Collectively, our results provide a non-opportunistic rationale for the optimistic bias in long-term quarterly earnings forecasts.

Long-Term Earnings Forecasts, Shifting Segment Earnings, and Stock Returns

Long-Term Earnings Forecasts, Shifting Segment Earnings, and Stock Returns

Analysts’ Cultural Attitudes to Time Orientation

We study how analysts’ cultural attitudes to time orientation affect their production of long-term earnings forecasts, the profitability of their stock recommendations, and managerial myopia for the firms they cover. We find that analysts from a long-term oriented culture produce more long-term earnings forecasts, issue more timely long-term forecasts and more profitable stock recommendations. These results are more pronounced among firms with more long-term investments, for smaller firms, and during periods of higher economic uncertainty. Exploring the quasi-natural experiments of brokerage houses’ mergers and closures, we find a positive and plausibly causal effect of the coverage by long-term oriented analysts on firm innovation. Contrary to extant research finding that analysts’ coverage in general fosters managerial myopia, our paper shows that the coverage of long-term oriented analysts ameliorates managerial myopia.

Comparison of Cross-Sectional Earnings Forecasting Models for the European Market

This paper aims to compare the cross-sectional models of earnings forecasts to the analysts’ earnings forecasts in the European markets. We introduce the models of Fama and French (2006), Novy-Marx (2013), and Hou et al. (2012). The target of the forecasting methods is to minimize the bias and to have a high forecasting accuracy in comparison to real earnings. Our results show that for almost all regions, the cross-sectional models of earnings forecast have a lower bias, but they are not as accurate as the analyst’s earnings forecast. In addition, the outcomes also show that cross-sectional models of earnings forecasts tend to be more accurate for long-term earnings forecasts, whereas for short-term forecasts analysts’ earnings forecasts are more reliable. The best cross-sectional earnings forecasts are calculated with the model of Novy-Marx (2013) in all the observed regions. Finally, the bias results show that even the cross-sectional forecasts are over-optimistic.

Analysts’ Incentives to Overweight Management Guidance when Revising Their Short-Term Earnings Forecasts

We document that, when revising their short-term earnings forecasts in response to management guidance, analysts wishing to curry favor with management weight the guidance more heavily than predicted based on the credibility and usefulness of the guidance. This overweighting of guidance is present prior to equity offerings and other events that could lead to investment banking business. Although analysts sacrifice their forecast accuracy by overweighting management guidance, they appear to benefit, on average, by subsequently gaining the underwriting business for their banks. Thus, while analysts wishing to please managers are optimistic in their long-term earnings forecasts, they take their cue from management when determining their short-term earnings forecasts.

The Empirical Relationship Between Stock Prices and Long-Term Earnings

This article shows stock prices to be related to be a function of long-term earnings forecasts, as is consistent with financial theory. Stock prices reflect not only the average of the IBES long-term earnings predictions but also some superior forecasting power beyond that aggregated average prediction. <b>TOPICS:</b>Security analysis and valuation, statistical methods, exchanges/markets/clearinghouses

Patterns in Analysts’ Long-Term Earnings Forecasts

Patterns in Analysts’ Long-Term Earnings Forecasts

Patterns in Analysts' Long-Term Earnings Forecasts

This article examines the accuracy of analysts9 long-term estimates (made before the beginning of the year being forecast) of annual operating earnings during the 1986–2002 period, as provided in the Thomson First Call I/B/E/S database. The article asks whether an investor can use the pattern of a particular analyst9s earnings estimates as a way of discerning analyst accuracy; that is, whether there are biases or signals in those patterns. Examining the change between consecutive earnings estimates, we find larger changes (negative or positive) are associated with lower forecast accuracy. Examining the difference between an analyst9s estimate of earnings and the previous year9s actual earnings in joint tests, we find that estimates predicting larger increases in earnings are decreasingly accurate, but those predicting larger decreases in earnings are increasingly accurate. Examining the number of estimates produced by an analyst as a signal of quality, we find no relationship in univariate tests, although one has been reported previously in the literature; in joint tests, a negative relationship is found between forecast frequency and accuracy. <b>TOPICS:</b>Security analysis and valuation, fundamental equity analysis, quantitative methods, statistical methods

Analysts’ Incentives to Overweight Management Guidance When Revising Their Short-Term Earnings Forecasts

ABSTRACT: We document that, when revising their short-term earnings forecasts in response to management guidance, analysts wishing to curry favor with management weight the guidance more heavily than predicted, based on the credibility and usefulness of the guidance. This overweighting of guidance is present prior to equity offerings and other events that could lead to investment banking business. Although analysts sacrifice their forecast accuracy by overweighting management guidance, they appear to benefit, on average, by subsequently gaining the underwriting business for their banks. Thus, while analysts wishing to please managers are optimistic in their long-term earnings forecasts, they take their cue from management when determining their short-term earnings forecasts.

Earnings Smoothness, Average Returns, and Implied Cost of Equity Capital

ABSTRACT: Despite a belief among corporate executives that smooth earnings paths lead to a lower cost of equity capital, I find no relation between earnings smoothness and average stock returns over the last 30 years. In other words, owners of firms with volatile earnings are not compensated with higher returns, as one would expect if volatile earnings lead to greater risk exposure. Although prior empirical work links smoother earnings to a lower implied cost of capital, I offer evidence that this link is driven primarily by optimism in analysts' long-term earnings forecasts. This optimism yields target prices and implied cost of capital estimates that are systematically too high for firms with volatile earnings. Overall, the evidence is inconsistent with the notion that attempts to smooth earnings can lead to a lower cost of equity capital.

The Role of “Other Information” in the Valuation of Foreign Income for U.S. Multinationals

In this paper, we examine investors' valuation of the domestic and foreign components of total earnings after controlling for information beyond current earnings. Our sample consists of U.S. multinationals during the 1985-2002 period. In a prior study, Bodnar and Weintrop (1997) find that investors place a higher weight on foreign earnings than on domestic earnings in valuing securities, and that this finding can be explained in part by the higher growth opportunities in foreign markets. While this explanation is intuitively appealing, other possible explanations include the varying importance of information other than current accounting earnings in pricing securities and the possible misspecification of their model. One potentially important source of other information is information contained in revisions of analysts' forecasts of future (abnormal) earnings and terminal values. Excluding this information from the regression specification potentially leads to a correlated omitted variables problem. In this paper, we use the Liu and Thomas (2000) proxy for “other information,” which is derived from analysts' revisions of near-term and long-term earnings forecasts and discount rate changes. Including the “other information” variable greatly improves the explanatory power of the returns—earnings regression. Consistent with our predictions, we find that the bias resulting from excluding other value-relevant information has a greater effect on foreign earnings than on domestic earnings. Foreign earnings are no longer incrementally value relevant when we control for “other information.”

Decomposing Credit Spreads

This paper investigates the information contained in the yields of corporate debt securities using a structural credit risk model. As previous studies have found, credit risk is not the only factor that affects corporate yield spreads. The aim is to decompose credit spreads, using a structural model of credit risk, into credit and non-credit risk components. The contribution relative to the existing literature is the use of contemporaneous forward-looking information on equity risk premia and equity value uncertainty in a structural model. In particular, implied equity risk premia from a three-stage dividend discount model that incorporates analysts' long-term earnings forecasts are used, together with implied measures of equity value uncertainty from option prices. The paper examines the evolution of the different components of spreads across time as well as the effect of particular events. It also analyses the relationship between the derived components and other financial variables, such as swap spreads and the equity risk premium.

The Role of 'Other Information' in the Valuation of Foreign Income for U.S. Multinationals

In this paper, we examine investors' valuation of the domestic and foreign components of total earnings after controlling for beyond current earnings. Our sample consists of U.S. multinationals during the 1985-2002 period. In a prior study, Bodnar and Weintrop (1997) find that investors place a higher weight on foreign earnings than on domestic earnings in valuing securities, and that this finding can be explained in part by the higher growth opportunities in foreign markets. While this explanation is intuitively appealing, possible explanations include the varying importance of than current accounting earnings in pricing securities and the possible mis-specification of their model. One potentially important source of is contained in revisions of analysts' forecasts of future (abnormal) earnings and terminal values. Excluding this from the regression specification potentially leads to a correlated omitted variables problem. In this paper, we use the Liu and Thomas (2000) proxy for other information, which is derived from analysts' revisions of near-term and long-term earnings forecasts and discount rate changes. Including the other information variable greatly improves the explanatory power of the returns-earnings regression. Consistent with our predictions, we find that the bias resulting from excluding value-relevant has a greater effect on foreign earnings than on domestic earnings. Foreign earnings are no longer incrementally value relevant when we control for other information.

Transitory and persistent earnings components as reflected in analysts' short-term and long-term earnings forecasts: evidence from a nonlinear model

This study uses a nonlinear framework to examine the relative proportion of transitory and persistent earnings components in financial analysts' earnings forecasts for three different time horizons (one quarter ahead, one year ahead, and three-to-five years ahead). We find that the proportion of transitory earnings components in analysts' forecasts decreases as the forecast horizon is extended. Using a nonlinear multivariate model, we find that both short-term and long-term forecast revisions are important for explaining stock price changes. Our study is important to investors because its results are consistent with analysts using short-term earnings forecasts to signal their expectations about a firm's reported GAAP earnings, and longer-term forecasts to convey their expectations about a firm's more persistent earnings. Moreover, both short-term and long-term forecasts are shown to provide value-relevant information to investors. Our study is important to researchers because it suggests that a nonlinear model is more appropriate for describing the relation between returns and analysts' forecast revisions. Prior studies, using linear models, have underestimated the value-relevance of forecast revisions, especially short-term ones.

Analysts' use of earnings forecasts in predicting stock returns: Forecast horizon effects

Little attention has been paid to a principal decision context in which analysts' earnings forecasts are prepared, namely, as an input to their recommendations. We use two data sets, Value Line, USA, and Research Evaluation Service, Canada, and examine the importance of analysts' earnings forecasts for their stock price forecasts via three hypotheses: (1) analysts' earnings forecasts are important for their stock price forecasts; (2) analysts' long-term earnings forecasts are more important than their short-term earnings forecasts for their predictions of stock prices over a particular stock price forecast horizon; (3) the importance of analysts' earnings forecasts for their stock price forecasts rises as the joint earnings and stock price forecast horizon increases. We show that: (1) when the earnings forecast horizon is the next fiscal year, forecasted earnings explain only 30% of the variation in forecasted price; (2) the importance of forecasted earnings for forecasted price rises as the earnings forecast horizon increases; (3) in the long run, (i.e. three to five years hence), forecasted earnings explain about 60% of the variation in forecasted price. Decision usefulness is an ex ante concept, but tests regarding the usefulness of earnings for stock price generally have used actual (not expectational) data. Our evidence suggests that earnings expectations are decision useful, where the decision context is sell-side analysts' stock price forecasts. Our results are potentially important to users of sell-side analyst research reports. When a stock recommendation is accompanied only by short-run earnings forecasts, investors need to closely examine estimates of non-earnings variables to assess the quality of stock recommendations. In contrast, when stock recommendations are accompanied by both short-run and long-run earnings forecasts, investors need to examine estimates of non-earnings information variables less closely.

The accuracy of long-term earnings forecasts in the electric utility industry

This paper examines the accuracy of various methods of forecasting long-term earnings growth for firms in the electric utility industry. In addition to a number of extrapolative techniques, Value Line analyst forecasts are also evaluated. Value Line analyst forecasts for a five-year time horizon are found to be superior to many of the extrapolative models. Among the extrapolative models examined, implied growth and historical book value per share growth rate models performed best. These results provide strong support for using Value Line growth forecasts in cost of capital estimates for electric utilities in the context of utility rate cases. Value Line forecast errors could be explained by changes in dividend payout ratios, the firm's regulatory environment and bond rating changes.