Long-term Growth Forecasts Research Articles

Valuation, Observability of Valuation Drivers, and Future Stock Returns

This article shows that the relationship between favorable equity market valuations and subsequent equity market returns depends on the extent to which the reasons for such valuations are likely to be observable to investors. The authors use the Implied Equity Risk Premium (ERP) to measure whether the U.S. equity market is favorably valued, and a macroeconomic model to explain the level of ERP and allow a determination of whether valuations are consistent with observable data. The model for explaining ERPs considers factors such as interest rates, GDP growth, analysts’ longterm growth forecasts, and investors’ preference for equities with high asset value relative to investors’ preference for equities with high future growth opportunities. When the reasons for the favorable valuations are likely to be known to investors, such as when the negative macroeconomic data consistent with current ERP levels are already public information, higher ERPs are predictive of higher future stock market returns in the long term. However, when the reasons for the favorable valuations are not as likely to be known to investors, higher ERPs are predictive of lower stock market returns in the short term. The rationale is that investor concerns that lead to higher ERPs are more likely to be fully priced when those concerns reflect data that are publicly available, setting the stage for higher future returns. The relevant implication for investors is that valuation is not a sufficient signal for increasing equity allocations. Rather, even if valuation appears attractive, investors should wait to increase equity allocations until the valuation level can be explained by observable data.

Predicting Long-Term Earnings Growth from Multiple Information Sources

While expected long-term earnings growth plays a pivotal role in valuation and investment applications, its common proxy, analysts' long-term growth forecasts (LTG), is well known for being over-optimistic. Guided by a stylized growth model, this paper uses three information sources to improve growth prediction — analysts' forecasts, stock prices, and financial statements. We find that the growth model using LTG, past earnings growth, the forward earnings-to-price ratio and past returns as predictors is unbiased and most accurate among the models considered in this paper. We further show that this growth prediction results in higher trading profits, more accurate equity predictions, and more reliable estimates of cost of equity. The findings suggest that this improvement in growth prediction leads to economically significant consequences in valuation and investment applications.

Divergence of Opinion, Overallotment, and IPO Long-Run Performance

We apply an ex ante measure of divergence of investor opinions – industry-level dispersion in analyst earnings forecast – to test the Miller (1977) prediction about IPO overvaluation. Our measure of divergence of opinion is the dispersion in analyst long-term earnings growth forecasts divided by the absolute value of the mean long-term growth forecast averaged at the industry level in the month prior to the IPO. We focus on the effect of divergence of opinion on long-run IPO performance, and test two hypotheses. First, greater divergence of opinion should predict lower long-run performance. Second, since the Miller effect depends on the demand of the offer relative to the supply, we further predict that the effect of belief dispersion should be stronger for offers with high investor demand, as measured by issue overallotment at the time of the offer. Using a sample of about 7,000 IPOs from 1982 to 2005, we find that IPOs in industries with high divergence of opinion have lower long-run returns in the following 3-5 years than IPOs in industries with low divergence of opinion. The effect of belief dispersion on long-run performance primarily exists among IPOs with high demand, as measured by the overallotment at the time of the offer, and this effect remains strong when returns are value-weighted. These findings support Miller’s hypothesis that in markets with restricted short-selling, valuations reflect the most optimistic investor’s appraisal in the short-run, and the initial overvaluation is corrected in the long-run. There is evidence that IPOs with high divergence of opinion also have lower first-day returns, but this association is weakened by the amount of overallotment, suggesting that the correction of initial overvaluation starts shortly after the offer, but the initial correction is dampened by investor demand at the time of the offer.

Comments: Price Swings

Editor's column A new report from Ernst & Young seeks to find a bottom for commodity prices and any signs that might point to economic recovery. Among its findings are that the recent oil price fall was the steepest ever, at 75%, and that past price corrections have lasted an average of 73 weeks before recovering. Because recessions eventually have given way to economic resurgence that relies heavily on energy, the report concludes that now is the time for the oil and gas industry to prepare for economic recovery by continuing to drill, ensuring that it is retaining talent, and investing in alternative fuels. Others have sounded a similar note of late. At last month's annual Cambridge Energy Research Associates (CERA) conference, executives from BP, Shell, and other firms noted the importance of continued investment in energy. Robust long-term growth forecasts for hydrocarbons have not changed, and the industry could be caught flat-footed when the recovery comes if it shuts down too much now. Shell Chief Executive Jeroen van der Veer said he believes that global energy demand still will double over the next 40 years, boosted by consumption from the developing world. BP Chief Executive Officer Tony Hayward also showed optimism. "The world economy will recover," he said. "The future is not canceled." (For additional reporting on the event, go to JPT Online at www.spe.org/jpt.) The statements lend credence to the idea that many in the industry are trying to avoid some of the mistakes of the past, when R&D and staff were sharply cut in the wake of down cycles. But nothing paralyzes the oil market so much as price instability. After the steep drop in prices in the second half of last year, oil seemed to be recovering, only to fall again and remain volatile. Such unexpected swings deter decisions about investment, particularly those projects with sensitive price thresholds such as oil sands and unconventionals. Volatility also hampers merger and acquisition activity. Sellers are reluctant to shed assets at low prices while potential buyers continue to sit on cash. "Nobody has been willing to pull the trigger. Everybody has been waiting for the upside," said IHS executive Linda Kinney at a conference last month in Houston sponsored by the consulting firm. Daniel Yergin, Chairman of CERA, says the oil markets "are suffering acute whiplash" and that the price volatility since mid-last year is causing confusion and uncertainty. The International Energy Agency says a shortage of capacity was really at the center of the steep run-up in prices that ended last year. Although "speculation" may have played a role, it was really the fundamentals of supply and demand that drove the market. Strong growth from places such as China and India exploited years of industry underinvestment in both the upstream and downstream, constraining supplies. It expects a similar tightness could occur in just a few years after the global economy fully emerges from what appears to be a severe recession.

The Subprime Crisis and House Price Appreciation

This paper argues that econometric analysis of housing price indexes before 2006 generated forecasts of future long-term price growth and low estimated probabilities of extreme price decreases. These forecasts of future increases in home-loan collateral values may have affected both the demand and the supply of mortgages. Standard time series models using repeat-sales indices suggested that positive trends had a long half-life. Expectations based on such models supported expectations that could lead to an asset bubble. Analysis of data from the HMDA loan data base and LoanPerformance at the MSA level and at the loan level substantiates both supply and demand effects of past price trends in housing markets, particularly with respect to subprime mortgage applications and approvals. At the MSA level, past home price increases are associated with higher subprime applications and loan to value ratios. Approval probability of subprime loans was not affected by higher loan to value ratios. At the loan level, the approval probability of subprime applications is also positively associated with past home price appreciation. These results differ for prime mortgages.

The Disparity between Long-Term and Short-Term Forecasted Earnings Growth

We find the disparity between long-term and short-term analyst forecasted earnings growth is a robust predictor of future returns and revisions in long-term forecasted earnings growth. After adjusting for industry characteristics, stocks whose long-term earnings growth forecasts are far above or far below their implied short-term forecasts for earnings growth have negative and positive subsequent risk-adjusted returns, respectively. Despite the importance of conditioning on short-term forecasted earnings growth, these returns are not driven by earnings momentum. Instead, consistent with investors having limited attention, predictable revisions in long-term analyst forecasts appear to induce return predictability.

Does Affiliation Bias Analyst Long-Term Earnings Growth Forecasts?

We study long-term earnings growth (LTG) forecasts around seasoned equity offerings. We document that LTG forecasts for firms with fewer analysts are generally higher than forecasts for firms with more analysts covering the stock. In contrast to prior studies, we find no difference between LTG forecasts of affiliated analysts who work for investment banks that have relationships with equity issuing firms and those of unaffiliated analysts. Further analysis shows that aggregation bias influences the prior studies' conclusion that affiliated analysts make more optimistic LTG forecasts. Both affiliated and unaffiliated analyst forecasts are more optimistic for firms with fewer analysts. In addition, the number of unaffiliated analysts relative to the number of affiliated analysts covering the same firm increases with the firm's analyst coverage. As a result, the mean forecast bias of unaffiliated analysts turns out to be lower than the mean forecast bias of affiliated analysts. However, this observed difference in mean forecast bias is driven by analyst coverage rather than analyst affiliation.

Do Financial Analysts’ Long-Term Growth Forecasts Reflect Effective Effort Towards Informative Stock Recommendations?

Prior literature finds that economic incentives related to generating investment banking business and trading commissions dominate explanations for the variation in analysts’ forecasts of firms’ long-term earnings growth (LTG) and, therefore, LTG forecasts provide little, if any, insight into the real growth prospects and current valuation of a firm’s equity securities. However, it is puzzling why stock analysts issue long-term growth forecasts that bear no relation to their effort in formulating stock recommendations that identify mispriced securities. This paper attempts to address this puzzling, but interesting question by examining whether the issuance of LTG forecasts reflects analyst effort that enhances the value-relevance of their stock recommendations. We show that the stock market responds more strongly to recommendation revisions by analysts who also issue LTG forecasts, and investors following the stock recommendations of analysts issuing LTG forecasts earn more trading profits than investors relying on the recommendations of analysts not issuing LTG forecasts. Our results suggest that analysts’ LTG forecasts reflect effective effort to increase the value-relevance of stock recommendations. Finally, we investigate the effect of LTG forecast issuance on analyst career outcomes and find that analysts issuing LTG forecasts are less likely to be demoted or terminated. Thus, analysts’ effort to issue LTG forecast and effective application of LTG in making recommendations are rewarded with higher job security.

An Analysis of Financial Analysts' Optimism in Long-term Growth Forecasts

A large body of literature has rejected rational expectations in relation to analyst forecasts. In this paper we start with a boundedly rational premise that analysts and managers adopt are influenced by the availability heuristic (Tversky and Kahneman [1973]). In the presence of business cycles, a rational growth forecast presupposes precise knowledge of the factors that cause a business cycle. In contrast, under the availability heuristic the current state is overweighted in the growth forecast and so whatever part of the business cycle the economy is currently in will be preserved by the investment decision. As a result, under the hypothesis of the availability heuristic we will observe ex-post, a systematic association between the drivers of this behavior (e.g., current state of the economy, industry, current performance) and subsequent forecast errors and (realized) growth when related to specific properties of the business cycle. We test for this condition and find evidence in support of it. The boundedly rational premise also provides a prediction for the nature of information that can improve analyst forecasts. The results from our analysis provide support for conclusion that a major driver of the boundedly rational behavior is ignoring the business cycle. Together these results provide direct evidence in support of Sargent's [2001] conjecture that a plausible reason for departures from rational expectations is the overly strong assumptions regarding the knowledge the agents are assumed to possess regarding the underlying laws of motion for the economy.

The Existence and Value-Relevance of Financial Analysts' Long-Term Growth Forecasts*

This paper investigates two questions. First, why do we observe analysts’ long-term earnings growth forecasts (hereafter, LTG forecasts) for some firms but not others and why do some analysts issue LTG forecasts while others do not? Second, are the LTG forecasts viewed as value-relevant by investors and do they enhance the value-relevance of stock recommendations? For the first question, at the firm level, we predict a positive (negative) relation with investors’ demand for LTG forecasts (the cost of collecting long-term oriented information). In particular, we hypothesize that the existence of LTG forecasts increases with the firm’s growth opportunities, the firm’s financial health, the proportion of shareholdings by long-horizon investors, firm size, and firm age and decrease with loss occurrence. At the analyst level, we predict that analysts with less time and resource constraints, with more experience and ability, and inputting more research effort in covering a firm are more likely to issue LTG forecasts. Empirical results are largely consistent with our predictions. For the second question, we find that the stock market responds significantly to LTG forecast revisions. In addition, the stock market responds more strongly to recommendation revisions by analysts who also issue LTG forecasts. Further, investors following the stock recommendations of analysts issuing LTG forecasts earn more trading profits than investors relying on the recommendations of analysts not issuing LTG forecasts.

Analyst Incentives and the Financial Characteristics of Wall Street Darlings and Dogs

Wall Street darlings, stocks with consensus strong buy recommendations, tend to be stocks with recent positive EPS momentum and surprise, recent positive relative price momentum, and recent positive EPS forecast revisions. Darlings also have stronger balance sheets, in the sense of lower debt, and tend to have lower dividend yields. Finally, darlings also tend to have higher long-term EPS growth forecasts and lower book-to-market ratios. Wall Street dogs, stocks with consensus hold and sell recommendations, tend to have the opposite characteristics. <b>TOPICS:</b>Equity portfolio management, security analysis and valuation, portfolio construction

Term Structure Forecasts of Long-Term Consumption Growth

AbstractRelying on a simple general equilibrium model of the term structure, we show that both nominal yields and real consumption growth rates can be affine in the unobservable state variables. We can then express real consumption growth rates in terms of nominal yields rather than the unobservable state variables with the coefficients of the resultant forecasting relation being endogenously determined by the term structure model. Using term structure data over the 1985 to 2000 sample period, the empirical evidence is consistent with our model more accurately predicting real consumption growth rates than a regression model based on the term spread.

How Does the Market Interpret Analysts' Long-Term Growth Forecasts?

The long-term growth forecasts of equity analysts do not have well-defined horizons, an ambiguity of substantial import for many applications. I propose an empirical valuation model, derived from the Campbell-Shiller dividend-price ratio model, in which the forecast horizon used by the “market” can be deduced from linear regressions. Specifically, in this model, the horizon can be inferred from the elasticity of the price-earnings ratio with respect to the long-term growth forecast. The model is estimated on industry- and sector-level portfolios of S&amp;P 500 firms over 1983-2001. The estimated coefficients on consensus long-term growth forecasts suggest that the market applies these forecasts to an average horizon somewhere in the range of 5 to 10 years.

An Evaluation of Accounting-Based Measures of Expected Returns

We develop an empirical method that allows us to evaluate the reliability of an expected return proxy via its association with realized returns even if realized returns are biased and noisy measures of expected returns. We use our approach to examine seven accounting-based proxies that are imputed from prices and contemporaneous analysts' earnings forecasts. Our results suggest that, for the entire crosssection of firms, these proxies are unreliable. None of them has a positive association with realized returns, even after controlling for the bias and noise in realized returns attributable to contemporaneous information surprises. Moreover, the simplest proxy, which is based on the least reasonable assumptions, contains no more measurement error than the remaining proxies. These results remain even after we attempt to purge the proxies of their measurement error via the use of instrumental variables and grouping. We provide additional evidence, however, that demonstrates that some proxies are reliable when the consensus long-term growth forecasts are low and/or when analysts' forecast accuracy is high.

How Does the Market Interpret Analysts' Long-Term Growth Forecasts?

The long-term growth forecasts of equity analysts do not have well-defined horizons, an ambiguity of substantial import for many applications. I propose an empirical valuation model, derived from the Campbell-Shiller dividend-price ratio model, in which the forecast horizon used by the &amp;amp;quot;market&amp;amp;quot; can be deduced from linear regressions. Specifically, in this model, the horizon can be inferred from the elasticity of the price-earnings ratio with respect to the long-term growth forecast. The model is estimated on industry- and sector-level portfolios of S&amp;amp;amp;P; 500 firms over 1983-2001. The estimated coefficients on consensus long-term growth forecasts suggest that the market applies these forecasts to an average horizon of at least 6 years, and as many as 10 years.

Analyst Conflicts and Research Quality

This paper examines whether the quality of stock analysts’ forecasts is related to conflicts of interest from their employers’ investment banking (IB) and brokerage businesses. We consider four aspects of forecast quality: accuracy, bias, and revision frequency of quarterly earnings per share (EPS) forecasts and relative optimism in long-term earnings growth (LTG) forecasts. Using a unique dataset that contains the annual revenue breakdown of analysts’ employers among IB, brokerage, and other businesses, we uncover two main findings. First, accuracy and bias in quarterly EPS forecasts appear to be unrelated to conflict magnitudes, after controlling for forecast age, firm resources and analyst characteristics. Second, relative optimism in LTG forecasts and the revision frequency of quarterly EPS forecasts are positively related to the importance of brokerage business to analysts’ employers. Additional tests suggest that the frequency of quarterly forecast revisions is positively related to analysts’ trade generation incentives. Our findings suggest that reputation concerns keep analysts honest with respect to short-term earnings forecasts but not long-term growth forecasts. In addition, conflicts from brokerage appear to play a more important role in shaping analysts’ forecasting behavior than has been previously recognized.

Do Analysts at Independent Research Firms Make Better Earnings Forecasts?

This study compares the earnings forecasts of analysts employed by independent research firms to those of analysts employed by investment banks along the dimensions of accuracy and optimism. We discuss the conflicts of interest faced by both groups and suggest that, despite incentives stemming from corporate financing operations, investment bank analysts may nevertheless provide superior forecasts. We provide evidence on this empirical question using a sample of analyst forecasts from 1998-2001. Our results reveal that short-term forecasts made by investment bank analysts are on average more accurate and less optimistic than those from analysts employed by independent research firms. Our results are robust to controlling for several relevant factors identified in prior research and are consistent across both annual and quarterly earnings forecasts. We also examine the optimism in long-term earnings growth forecasts and fail to find a significant difference between the two groups.

Analyst Following and Equity Offerings Subsequent to Initial Public Offerings

Analyst forecast information is collected for firms following their IPOs and is used in an examination of subsequent seasoned equity offerings (SEOs). Consistent with information asymmetry arguments, the analysis indicates that a larger percentage of firms conducting SEOs within three years of the IPO are covered by financial analysts than those without SEOs, and that analyst coverage is a significant predictor of subsequent SEOs. In addition, the results indicate that long-term earnings growth forecasts are larger for firms with subsequent SEOs, but growth forecasts decline significantly following the SEOs. Further, SEO abnormal returns exhibit a significant negative relationship with earnings growth forecasts. These results are consistent with “windows of opportunity” arguments since they suggest that SEOs are “timed” to coincide with the peak of earnings growth expectations, but that market participants compensate by reacting more negatively to offerings by firms with high growth forecasts.

How Does the Market Interpret Analysts' Long-Term Growth Forecasts?

How Does the Market Interpret Analysts' Long-Term Growth Forecasts?

The Relation between Analysts' Forecasts of Long‐Term Earnings Growth and Stock Price Performance Following Equity Offerings*

AbstractIn this paper we evaluate the role of sell‐side analysts' long‐term earnings growth forecasts in the pricing of common equity offerings. We find that, in general, sell‐side analysts' long‐term growth forecasts are systematically overly optimistic around equity offerings and that analysts employed by the lead managers of the offerings make the most optimistic growth forecasts. In additional, we find a positive relation between the fees paid to the affiliated analysts' employers and the level of the affiliated analysts' growth forecasts. We also document that the post‐offering underperformance is most pronounced for firms with the highest growth forecasts made by affiliated analysts. Finally, we demonstrate that the post‐offering underperformance disappears once we control for the overoptimism in earnings growth expectations. Thus, the evidence presented in this paper is consistent with the “equity issue puzzle” arising from overly optimistic earnings growth expectations held at the time of the offerings.