Expectations and the Cross-Section of Stock Returns

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.     

Momentum Strategies

We examine whether the predictability of future returns from past returns is due to the market's underreaction to information, in particular to past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. Market risk, size, and book–to–market effects do not explain the drifts. There is little evidence of subsequent reversals in the returns of stocks with high price and earnings momentum. Security analysts' earnings forecasts also respond sluggishly to past news, especially in the case of stocks with the worst past performance. The results suggest a market that responds only gradually to new information.     

Analyst Forecasts and the Cross Section of European Stock Returns

We examine revisions to earnings forecasts by equity analysts and their role in predicting stock returns. We provide evidence that European stocks with net upward revised forecasts earn higher future returns than otherwise similar stocks. This effect is not concentrated in small stocks, stocks with low analyst coverage, or stocks with low book‐to‐market ratios. We find differences in the return continuation patterns of stocks with upward versus downward revisions, namely, bad news travels quickly, but good news travels slowly. This result is consistent with investors' attaching greater significance to poor earnings forecasts, but adopting a wait‐and‐see approach to good news.     

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 long-term analyst forecast errors. 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 along with downward and upward revisions in long-term forecasted earnings growth, respectively. Additional results indicate that investor inattention toward firm-level changes in long-term earnings growth is responsible for these risk-adjusted returns.     

Sell‐Side Analyst Research and Stock Comovement

We document that a stock's price around a recommendation or forecast covaries with prices of other stocks the issuing analyst covers. The effect of shared analyst coverage on stock price comovement extends beyond analyst activity days. A stock's daily returns covary with the returns of other stocks with which it shares analyst coverage. These links between stock price comovement and shared analyst coverage are consistent with the coverage‐specific information we find in earnings forecasts; analysts who cover both stocks in a pair expect future earnings of the stocks to be more highly correlated than do analysts who cover only one stock from the pair. Collectively, our evidence indicates that analyst research produces coverage‐specific spillovers that raise price comovement among stocks that share analyst coverage. The strength of these spillovers is comparable to spillovers from broad industry and market information in analyst research.     

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.     

ABNORMAL RETURNS AND ANALYSTS' EARNINGS FORECAST REVISIONS ASSOCIATED WITH THE PUBLICATION OF “STOCK HIGHLIGHTS” BY VALUE LINE INVESTMENT SURVEY

We examine the reaction of stocks and the response of financial analysts' earnings forecasts to securities recommended as “Stock Highlights” by Value Line Investment Survey. Significant abnormal returns appear around the publication of stock highlights. Stock price responses are relatively efficient and permanent. Using earnings expectation data provided by the Institutional Brokers Estimate System, we find analysts raise their forecasts significantly following Value Line recommendations. Near-term forecast revisions are significantly related to stock returns at the time of the recommendations. Thus, an explanation for Value Line's security recommendation success is its ability to generate firm-specific earnings information.     

Separating Winners from Losers among LowBook-to-Market Stocks using Financial Statement Analysis

This paper combines traditional fundamentals, such as earnings and cash flows, with measures tailored for growth firms, such as earnings stability, growth stability and intensity of R&D, capital expenditure and advertising, to create an index – GSCORE. A long–short strategy based on GSCORE earns significant excess returns, though most of the returns come from the short side. Results are robust in partitions of size, analyst following and liquidity and persist after controlling for momentum, book-to-market, accruals and size. High GSCORE firms have greater market reaction and analyst forecast surprises with respect to future earnings announcements. Further, the results are inconsistent with a risk-based explanation as returns are positive in most years, and firms with lower risk earn higher returns. Finally, a contextual approach towards fundamental analysis works best, with traditional analysis appropriate for high BM stocks and growth oriented fundamental analysis appropriate for low BM stocks.This revised version was published online in August 2005 with a corrected cover date.     

Common Stock Offerings and Earnings Expectations: A Test of the Release of Unfavorable Information

This paper examines the revisions of analysts' forecasts of future earnings around announcements of common stock offerings. The forecasts of the current year earnings are, on average, decreased when firms announce plans to issue additional common stock. The size of the decrease is significantly related to announcement period abnormal stock returns. In contrast, forecasts of the five-year growth rate of earnings are, on average, unchanged. We interpret these results as being consistent with the claim that equity offering announcements convey unfavorable information regarding the firm's short-term but not its long-term earnings prospects.     

Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts

Post–earnings announcement drift is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks following an earnings announcement. We show that the drift is significantly larger when defining the earnings surprise using analysts' forecasts and actual earnings from I/B/E/S than when using a time series model based on Compustat earnings data. Neither Compustat's policy of restating earnings nor the inclusion of “special items” in reported earnings contribute significantly to the disparity in drift magnitudes. Rather, our results suggest that this disparity is attributable to differences between analyst forecasts and those of time‐series models—or at least to factors correlated with these differences. Further, we document that analyst forecasts lead to return patterns around future earnings announcements that differ from those observed when using time‐series models, suggesting that the two types of surprises may capture somewhat different forms of mispricing.     

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.     

Differences of Opinion and the Cross Section of Stock Returns

We provide evidence that stocks with higher dispersion in analysts' earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks and stocks that have performed poorly over the past year. Interpreting dispersion in analysts' forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts' forecasts proxies for risk.     

Implied cost of capital investment strategies: evidence from international stock markets

Investors can generate excess returns by implementing trading strategies based on publicly available equity analyst forecasts. This paper captures the information provided by analysts by the implied cost of capital (ICC), the internal rate of return that equates a firm’s share price to the present value of analysts’ earnings forecasts. We find that U.S. stocks with a high ICC outperform low ICC stocks on average by 6.0 % per year. This spread is significant when controlling the investment returns for their risk exposure as proxied by standard pricing models. Further analysis across the world’s largest equity markets validates these results.     

The Role of Expectations in Explaining the Cross-Section of Stock Returns

We find highly significant results when the cross-section of market-adjusted stock returns is regressed against changes in analyst expectations this year about: (1) this year's earnings, (2) next year's earnings, (3) long-term earnings growth, and (4) noise (measured as the standard deviation of analyst forecasts). Surprisingly, changes in expectations about this year's earnings are not significant in a multiple regression with the other independent variables. Changes in expectations about next year's earnings are highly significant but with an impact that is much smaller than that of changes in expectations about the long-term growth in earnings. Changes in noise are also statistically significant and are negatively related to market-adjusted returns, an indication that the signal to noise ratio, rather than merely the signal, is what drives price adjustments to new information.     

Management earnings forecasts,insider trading,and information asymmetry

We investigate whether senior officers use accrual-based earnings management to meet voluntary earnings disclosure (i.e., management earnings forecasts) before selling or buying their own shares when they have private information. This study is the first to use the differences in timing of trades by senior officers and other insiders (e.g., directors or large shareholders) to infer information asymmetry. We hypothesize that the timing of senior officers' trades with no other insiders' trades at the same time indicates opportunistic trades and asymmetric information between senior officers and other insiders. Our results show that senior officers' exclusive sales are negatively associated with future returns, indicating that they tend to use insider information. Moreover, senior officers are more likely to meet their earnings forecasts when they plan to sell stocks.     

Earnings and Expected Returns

The aggregate dividend payout ratio forecasts excess returns on both stocks and corporate bonds in postwar U.S. data. High dividends forecast high returns. High earnings forecast low returns. The correlation of earnings with business conditions gives them predictive power for returns; they contain information about future returns that is not captured by other variables. Dividends and earnings contribute substantial explanatory power at short horizons. For forecasting long-horizon returns, however, only (scaled) stock prices matter. Forecasts of low long-horizon stock returns in the mid-1990s are caused not by earnings or dividends, but by high stock prices.     

Evaluating the information content of earnings forecasts

This study develops a framework to compare the ability of alternative earnings forecast approaches to capture the market expectation of future earnings. Given prior evidence of analysts’ systematic optimistic bias, we decompose earnings surprises into analysts’ earnings surprises and adjustments based on alternative forecasting models. An equal market response to these two components indicates that the associated earnings forecast is a sufficient estimate of the market expectation of future earnings. To apply our framework, we examine four recent regression-based earnings forecasting models, alongside a simple earnings-based random walk model and analysts’ forecasts. Using the earnings forecasts of the model that satisfies our sufficiency condition, we identify a set of stocks for which the market is unduly pessimistic about future earnings. The investment strategy of buying and holding these stocks generates statistically signi?cant abnormal returns. We offer an explanation as to why this and similar strategies might be successful.     

An Analysis of Contrarian Investment Strategies in the UK

The performance of contrarian, or value strategies – those that invest in stocks that have low market value relative to a measure of their fundamentals – continues to attract attention from researchers and practitioners alike. While there is much extant evidence on the profitability of value strategies, however, most of this evidence pertains to the US. In this paper, we provide a detailed characterisation of value strategies using data on UK stocks for the period 1975 to 1998. We first undertake simple one-way and two-way classifications of stocks in which value is defined using both past performance and expected future performance. Using sales growth as a proxy for past performance and book-to-market, earnings yield and cash flow yield as measures of expected future performance, we find that that stocks that have both poor past performance and low expected future performance have significantly higher returns than those that have either good past performance or good expected future performance. Allowing for size effects in returns reduces the value premium but it nevertheless remains significant. We go on to explore whether the profitability of value strategies in the UK can be explained using the three factor model of Fama and French (1996). Broadly consistent with the results for the US, we find that using the one-way classification the excess returns to almost all value strategies can be explained by their loading on the market, book-to-market and size factors. However, in contrast with the US, using the two-way classification there are excess returns to value strategies based on book-to-market and sales growth, even after controlling for their loading on the market, book-to-market and size factors.     

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.     

More Than Words: Quantifying Language to Measure Firms' Fundamentals

We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm-specific news stories forecasts low firm earnings; (2) firms' stock prices briefly underreact to the information embedded in negative words; and (3) the earnings and return predictability from negative words is largest for the stories that focus on fundamentals. Together these findings suggest that linguistic media content captures otherwise hard-to-quantify aspects of firms' fundamentals, which investors quickly incorporate into stock prices.