Standardized Unexpected Earnings Research Articles

New Return Anomalies and New-Keynesian ICAPM

I propose a new multi-factor asset pricing model with new-Keynesian factors to explain stock return anomalies from 1972Q1 to 2009Q2. This new model explains the average returns across testing portfolios formed on financial distress, momentum, and standardized unexpected earnings with misspecification-robust statistics. Test portfolios formed on net stock issues and total accruals are also partly explained by new-Keynesian factors. Two monetary policy factors play an important role in explaining these new anomalies. The credit aspect of these new anomalies suggests an economic rational for the model through capital market imperfections and the credit channel of monetary policy mechanism.

Is trading on earnings surprises a profitable strategy? Canadian evidence

This study examines the profitability of trading on earnings surprises in the post-earnings announcement period for Canadian equities spanning the period 1994–2009. There is clear evidence that stock prices drift in the direction of earnings surprise for several months following an earnings announcement. Specifically, we find that standardized unexpected earnings based on analyst forecasts (SUEAF), our main definition of earnings surprise, indicates that a hedge strategy of going long on firms in the highest SUEAF decile and going short on firms in the lowest SUEAF decile generates a greater than 6% excess return in the 60 days following the earnings announcement. We also show that that while both the SUEAF and standardized unexpected earnings (SUE) capture earnings surprise, each contains information that is not entirely subsumed by the other. In summary, we advance that the post-earnings announcement drift is caused by the market's delay in responding to earnings information. Our findings have major investment implications, since investors in general and Canadian investors in particular can exploit this anomaly.

Is Trading on Earnings Surprises a Profitable Strategy? Canadian Evidence

This study examines the profitability of trading on earnings surprises in the post-earnings announcement period for Canadian equities spanning the period 1994-2009. There is clear evidence that stock prices drift in the direction of earnings surprise for several months following an earnings announcement. Specifically, we find that standardized unexpected earnings based on analyst forecasts (SUEAF), our main definition of earnings surprise, indicates that a hedge strategy of going long on firms in the highest SUEAF decile and going short on firms in the lowest SUEAF decile generates a greater than 6% excess return in the 60 days following the earnings announcement. We also show that that while both the SUEAF and standardized unexpected earnings capture earnings surprise, each contains information that is not entirely subsumed by the other. In summary, we advance that the post-earnings announcement drift is caused by the market’s delay in responding to earnings information. Our findings have major investment implications, since investors in general and Canadian investors in particular can exploit this anomaly.

In Search of Fundamentals

We use search volume for firms' products to predict revenue surprises, earnings surprises and earnings announcement returns. We find that increases (decreases) in the search volume index (SVI) of a firm's most popular product strongly predicts positive (negative) revenue surprises. This predictive power is weaker for standardized unexpected earnings (SUE). SVI has strong predictability for returns around earnings announcements, especially among firms with few products, growth firms and firms that manage their reported earnings. Taken together, the evidence suggests that search volume for a firm's products is a value-relevent leading indicator about a firm's future cashflow that the market does not fully incorporate into prices until the earnings announcement.

The Asymmetry of Market Efficiency for Positive and Negative Earnings Surprises

I presume that due to conditional conservatism of investors, market efficiency is greater for bad news than for good news. I test the validity of this presumption by using earnings surprises as representatives for news. Positive earnings surprises represent good news and negative earnings surprises represent bad news. My research design is essentially an analysis of earnings response coefficients (ERC) and post earnings announcement drift (PEAD), i.e., I regress short term cumulative abnormal stock returns (CAR) around earnings announcements and long term CAR after earnings announcements on standardized unexpected earnings (SUE). However, unlike most prior ERC or PEAD studies, I use dummy variables to discriminate between positive and negative SUE. The regression results support my presumption because they show an asymmetry in the return reaction to earnings surprises. Positive earnings surprises have a positive effect on both short term CAR around earnings announcements and long term CAR after earnings announcements. Negative earnings surprises, on the other hand, have a negative effect only on short term CAR around earnings announcements. My finding that only positive earnings surprises have an effect on long term CAR after earnings announcements implies that the results of PEAD studies that do not discriminate between positive and negative earnings surprises can be misleading.

Risk Effect versus Delayed Price Response: The Case of the Post-Earnings-Announcement Drift in Germany

Summary/Zusammenfassung Risk Effect versus Delayed Price Response: the Case of the Post-Earnings-Announcement Drift in Germany This paper presents supporting evidence for the post-earnings-announcement drift using annual data on 850 firms listed on the Frankfurt stock exchange for the years 1990 to 2003. Standardized unexpected earnings and unexpected earnings based on the security return model yield significant abnormal returns to the drift trading strategy of about 3% to 6% over 59 to 109 days. In an analysis of covariance the variables size and book-to-market ratio are insignificant in explaining the drift. Further, a control variable for a momentum effect is highly significant, and the inverse Mills ratios to control for a survivorship bias are significant for periods starting from about 160 days. All variables combined cause the drift to become insignificant for the standardized unexpected earnings model and reduce the significance of the drift given by the security return model. The insignificance o...

Do IPO Earnings and Revenue Surprises Surprise Investors?

In this paper we explore the information conveyed by earnings and revenue surprises for IPO firms. Further, we examine the persistence of earnings and revenue surprises and the characteristics of IPO firms with extreme earnings and revenue surprises. We find a positive relation between announcement returns and both standardized unexpected earnings (SUE) and standardized unexpected revenue (SUR). We also find a positive relation between revenue surprises and one-year holding period returns. Overall, investors appear to pay more attention to the direction than magnitude of earnings and revenue surprises in the short-run but more on the magnitude of revenue surprises in the long-run. Our results suggest that it is hard for IPO firms to continuously surprise investors in terms of earnings and revenues.

Inflation Illusion and Post-Earnings-Announcement Drift

This paper examines the cross-sectional implications of the inflation illusion hypothesis for the post-earnings-announcement drift. The inflation illusion hypothesis suggests that stock market investors fail to incorporate inflation in forecasting future earnings growth rates, and this causes firms whose earnings growths are positively (negatively) related to inflation to be undervalued (overvalued). We argue and show that the sensitivity of earnings growth to inflation varies monotonically across stocks sorted on standardized unexpected earnings (SUE) and, consistent with the inflation illusion hypothesis, show that lagged inflation predicts future earnings growth, abnormal returns, and earnings announcement returns of SUE-sorted stocks. Interestingly, controlling for the return predictive ability of inflation weakens the ability of lagged SUE to predict future returns of SUE-sorted stocks.

The Relation between Dispersion in Analysts' Forecasts and Stock Returns: Optimism Versus Drift

This paper investigates the conclusion in Diether, Malloy, and Scherbina (2002) that dispersion in analysts' forecasts proxies for differences in investor beliefs, and that prices reflect the beliefs of optimistic investors when dispersion is high. If this is the case, we expect to find higher earnings response coefficients (ERCs), related to negative earnings surprises, for high versus low dispersion firms. This follows because the negative earnings surprises are less consistent with the beliefs of optimists. However, we find smaller ERCs, which calls into question the optimism argument in DMS. Further, we find that the relatively low future returns earned by high forecast dispersion firms, documented in DMS, are explained by the well known post-earnings-announcement drift phenomena. Specifically, after sorting observations based on prior period standardized unexpected earnings (SUEs), which are associated with drift, the difference between the future returns of high versus low dispersion firms is not statistically significant.

The Post-Earnings-Announcement Drift and Liquidity Risk

This paper investigates the relation between the post-earnings-announcement drift anomaly and liquidity. First, we find that, on average, bad-news firms (low standardized unexpected earnings (SUE)) are less liquid than good-news firms (high SUE), reflecting more information asymmetry and/or uncertainty among bad-news firms. Yet, we argue that this liquidity spread is less likely to explain the drift. Second, the returns of SUE-sorted portfolios are sensitive to fluctuations in market-wide liquidity. We find that systematic liquidity risk is an important determinant in explaining the cross-sectional variation of expected returns among SUE-sorted portfolios. This implies that a substantial part of the post-earnings-announcement drift anomaly can be viewed as compensation for risk associated with shocks to the information environment in the economy. Therefore, the evidence suggests that the previously reported anomalous returns are associated with model misspecification and/or hidden transaction costs.

A Requiem for SUE

We believe that standardized unexpected earnings (SUE, a.k.a. earnings surprise) has lost its power as a stock selection tool. The concept of surprise, acting on new information that was not previously reflected in stock prices, may still have merit. But measuring results versus expectations just before the announcement has been fatally compromised in our view by manipulation of expectations and earnings—a phenomenon that was unwittingly unleashed by SUE herself. We believe that other quantitative factors offer better hope for positive performance in the future, including earnings estimate revisions, valuation-based factors, and measures of earnings quality.

The Profitability of Momentum Strategies

Momentum strategies based on continuations in stock prices have attracted a wide following among money managers and investors. We evaluated the profitability of price momentum strategies based on past return and earnings momentum strategies based on standardized unexpected earnings and revisions of consensus forecasts. The strategies proved to be profitable for intermediate horizons. Chasing momentum can generate high turnover, however; hence, implementation of momentum strategies requires a focus on managing trading costs. Comparing the strategies yielded evidence that they reflect distinct phenomena and provided information about the sources of profits. The results indicate that the market is slow to incorporate the full impact of information in its valuations.

Earnings Surprise Research: Synthesis and Perspectives

An investigation of the relation between earnings surprise and three empirical anomalies—the P/E effect, the size effect, and the Value Line enigma—indicates that the standardized unexpected earnings (SUE) effect appears to be separate and distinct from each of the three. The relations between the SUE phenomenon and firm risk, the appropriateness of the earnings expectations model, and the role of transaction costs are also investigated. The SUE phenomenon is not attributable to inappropriate risk adjustment, use of the “wrong” earnings expectations model, or ignoring transaction costs. The SUE effect may be partly explained by analysts' behavior and is both predictable and profitable. The SUE effect has also been observed in Japan.

THE EARNINGS-PRICE AND STANDARDIZED UNEXPECTED EARNINGS EFFECTS: ONE ANOMALY OR TWO?

In this paper prior work on earnings-price (E/P) and standardized unexpected earnings (SUE) anomalies is re-examined and extended. A relation between excess returns and E/P is tested controlling for SUE. Results suggest that both anomalies are still present in the data, and that the E/P effect exists independently of the most recent earnings surprise.

FURTHER INSIGHT INTO THE STANDARDIZED UNEXPECTED EARNINGS ANOMALY: SIZE AND SERIAL CORRELATION EFFECTS

ABSTRACTStudying size and serial correlation effects, the authors examine why portfolios selected on the basis of standardized unexpected earnings (SUEs) exhibit excess returns. Results of the study indicate that the SUE effect and the size effect are independent anomalies; however, a more plausible explanation of the SUE effect may involve serial correlation of SUEs. The authors demonstrate that more than half of the post‐announcement responses to current quarter earnings may actually be pre‐announcement adjustments to next quarter's earnings.

Standardized Unexpected Earnings—1971–77

A RECENT ARTICLE IN this journal [5] measured the informational content of quarterly earnings reports and the effects of this information on stock prices. The empirical evidence presented, covering early 1971 through mid-1974, suggested that unexpected earnings were very significantly related to excess holding period returns and that the adjustment to the unexpected earnings was relatively slow. The semi-strong form of the Efficient Capital Market Hypothesis, while based on the postulate that stock prices respond to unanticipated earnings, leads to the additional hypothesis that the market response to unanticipated earnings changes occurs either before or simultaneously with publication of earnings and hence that unexpected earnings is not significantly correlated with excess returns for any period beginning after the publication date. As Sharpe [7] has noted: If better-than-expected earnings announcements indicate attractive opportunities for stock purchases days or weeks after the announcement has been made, the market is not performing in a perfectly efficient manner. The importance of this issue led us to perform additional tests with updated data in an attempt to answer the following questions (with answers contained in the cited tables): 1. What is the distribution of SUE (standardized unexpected earnings)? (Table 1) 2. Were cumulative returns related to unexpected earnings in the period 1974

STANDARDIZED UNEXPECTED EARNINGS—A PROGRESS REPORT

FINANCE THEORY IS GROUNDED on the assumption that security prices adjust to new information as it becomes available. This adjustment should be very quick in a perfect capital market where trading is frictionless and information flows freely to all participants and all participants value it equally. Otherwise there would be opportunities for riskless hedging. But in the real-world where there are trading costs, and delays in transmission and differences in interpretation and evaluation of information, the possibility of riskless hedging is less certain and the process of adjustment to new information less clear-cut. In this paper we will attempt to measure the informational content of quarterly reports and the effects of this information on stock prices.' New information can be described as information. If everyone expects a company to report $1.00 per share in the next quarter and it actually reports the $1.00, little new information has been added. It might reduce the uncertainty surrounding future but no major revision of expectations would be called for. On the other hand, if of $.50 or $2.00 were reported this would be information and clearly would call for a revision of probability beliefs about the future. We wish to test the hypothesis that this information and the accompanying revision of probability beliefs will have a measurable effect on stock prices. We postulate for the purpose of testing that extrapolated in the twenty-first quarter based on the seasonally adjusted trend of in the preceeding 20 quarters can be used as a satisfactory proxy for expected earnings.2 Then, unexpected earnings in the twenty-first quarter are the actual reported in that quarter minus the extrapolated earnings. The unexpected earnings so determined are deflated by the standard error of estimate of the trend fitting equation to get Standardized Unexpected Earnings (SUE) which we use as a measure of the informational content of the quarterly earnings.3