Negative Earnings Surprises Research Articles

Market segmentation and information values of earnings announcements: Some empirical evidence from an event study on the Chinese stock market

This paper investigates the trading activities of two distinct classes of shareholders, namely, the Chinese domestic investors and the foreign investors in the segmented Chinese A- and B-share markets, respectively. We conduct an event study on the annual earnings announcements based on two different accounting standards: International accounting standards (IAS) and PRC generally accepted accounting principles (PRC GAAP). The earnings announcements based on IAS and PRC GAAP are value relevant. The investors in the B-share market react to both the IAS and PRC GAAP earnings announcements, while the investors in the A-share market pay more attention to the PRC GAAP earnings reports. In the B-share market, positive abnormal returns are associated with positive earnings surprise and negative abnormal returns go with negative earnings surprise. We find preevent abnormal trading volumes without significant price changes for the A shares, which may be due to existing information in the A-share market prior to earnings announcements. The postevent abnormal trading volumes last for a longer period in the A-share market than in the B-share market.

Differential Persistence of Extremely Negative and Positive Earnings Surprises: Implications for the Post-Earnings-Announcement Drift

Consistent with prior studies, this study shows that extremely negative and extremely positive earnings surprises in the fourth quarter have lower levels of persistence than those in the first through third fiscal quarters. Furthermore, extremely negative earnings surprises in the fourth fiscal quarter have lower levels of persistence than extremely positive earnings surprises in that quarter. Similar to the patterns of persistence, the post-earnings-announcement drift in prices is declining through the four quarters of the fiscal year, with the smallest drift occurring after the announcement of the fourth fiscal quarter. The drift after the fourth quarter is virtually nonexistent for extremely negative earnings surprises and smaller than extremely positive surprises, in line with the differential persistence of these surprises. The combined evidence in the study is consistent with investors who under-react to extreme earnings surprises because they seek further information. When the new information confirms the initial surprise, prices move in the same direction, creating a drift. The results of the study are robust to earnings surprises based on time-series properties of earnings or analyst forecasts.

The Effect of Voluntary Disclosure and Preemptive Preannouncements on Earnings Response Coefficients (ERC) When Firms Manage Earnings

We study analytically the effect of preliminary voluntary disclosure and preemptive preannouncement on the slope of the regression of returns on earnings surprise—the earnings response coefficient (ERC). When firms do not manage earnings, additional disclosure has no effect, and the ERC is proportional to price/permanent earnings ratio. If they manage earnings by attempting to inflate them, the response to (100% credible) negative earnings surprise is stronger than the response to (less than 100% credible) positive surprise. To avert litigation, firms that manage earnings adopt a partial voluntary disclosure strategy—either public revelation of good news and withholding bad news, or public revelation of bad news and withholding good news. Voluntary disclosure affects ERC on positive earnings surprise only, depending on what the firm reveals: the good- news revealing ERC (GRC) is higher than the bad-news revealing ERC (BRC), because good news enhances the credibility of the positive earnings surprise, even though the market discounts good news. Furthermore, preemptive pre-announcements improve ERC accuracy by narrowing the scope of earnings management.

Management's Incentives to Avoid Negative Earnings Surprises

Recent reports in the business press allege that managers take actions to avoid negative earnings surprises. I hypothesize that certain firm characteristics are associated with greater incentives to avoid negative surprises. I find that firms with higher transient institutional ownership, greater reliance on implicit claims with their stakeholders, and higher value-relevance of earnings are more likely to meet or exceed expectations at the earnings announcement.I also examine whether firms manage earnings upward or guide analysts' forecasts downward to avoid missing expectations at the earnings announcement. I examine the relation between firm characteristics and the probability (conditional on meeting analysts' expectations) of having (1) positive abnormal accruals, and (2) forecasts that are lower than expected (using a model of prior earnings changes). Overall, the results suggest that both mechanisms play a role in avoiding negative earnings surprises.

Analysts' Reactions to Warnings of Negative Earnings Surprises

Analysts' Reactions to Warnings of Negative Earnings Surprises

Strategic Benchmarks in Earnings Announcements: The Selective Disclosure of Prior-Period Earnings Components

This paper provides evidence that managers strategically select the prior-period earnings amount that is used as a benchmark to evaluate current-period earnings in quarterly earnings announcements. Managers are more likely to separately announce a prior-period gain from the sale of property, plant, and equipment (PPE) than a loss. This strategy provides the lowest possible benchmark for evaluating current earnings, thereby allowing the manager to highlight the most favorable change in earnings. This strategic disclosure behavior is more likely to occur when it prevents a negative earnings surprise. The observed strategic disclosure decisions are consistent with a conjecture by managers that the nonrecurring nature of the prior-period gain/loss will be forgotten unless it is separately announced. Consistent with this conjecture, there is some evidence that equity investors, one potential target of strategic reporting, use the benchmark that managers provide in earnings announcements to evaluate current earnings, even when the components of this benchmark have different persistence. However, cross-sectional analyses provide no evidence that managers ex post exploit the equity mispricing that occurs between the earnings announcement date and the release of the financial statements.

Positive and Negative Earnings Surprises, Regulatory Climate, and Stock Returns*

AbstractThis study focuses on electric utilities in the United States to consider two related issues. First, the study tests for asymmetric price reactions to positive and negative earnings surprises (ES). Second, the study associates policy differences across jurisdictions with variations in the cash flow effects of positive and negative ES and then uses the framework to consider variations in price responses across regulatory climates. In the same context, the study investigates the effects of a utility's abnormal profits on the asymmetry of price reactions to positve and negative ES. The empirical predictions are motivated by the disparity between the principles and practices that underlie cost recovery for the utilities and the uneven effects of the cost‐recovery practies on the cash flows associated with positve and negative ES. The results show that the sign of ES and the climate in which a utility operates are related to the size of price reactions to ES. Furthermore, a utility's abnormal profit status has significant effects on the size of price reactions to ES. Only a modest price response asymmetry is indicated for manufacturing firms.

Discovering Interesting Patterns for Investment Decision Making with GLOWER x-A Genetic Learner Overlaid with Entropy Reduction

Prediction in financial domains is notoriously difficult for a number of reasons. First, theories tend to be weak or non-existent, which makes problem formulation open ended by forcing us to consider a large number of independent variables and thereby increasing the dimensionality of the search space. Second, the weak relationships among variables tend to be nonlinear, and may hold only in limited areas of the search space. Third, in financial practice, where analysts conduct extensive manual analysis of historically well performing indicators, a key is to find the hidden interactions among variables that perform well in combination. Unfortunately, these are exactly the patterns that the greedy search biases incorporated by many standard rule learning algorithms will miss. In this paper, we describe and evaluate several variations of a new genetic learning algorithm (GLOWER) on a variety of data sets. The design of GLOWER has been motivated by financial prediction problems, but incorporates successful ideas from tree induction and rule learning. We examine the performance of several GLOWER variants on two UCI data sets as well as on a standard financial prediction problem (S&P500 stock returns), using the results to identify one of the better variants for further comparisons. We introduce a new (to KDD) financial prediction problem (predicting positive and negative earnings surprises), and experiment with GLOWER, contrasting it with tree- and rule-induction approaches. Our results are encouraging, showing that GLOWER has the ability to uncover effective patterns for difficult problems that have weak structure and significant nonlinearities.

Analysts' Reactions to Warnings of Negative Earnings Surprises

Both the popular press and research literature report increasing use of short-horizon earnings guidance (referred to hereafter as warnings), primarily before negative earnings surprises.1 While it is claimed that investors and analysts have little tolerance for disappointments, feel misled by the failure to warn, lose confidence in management, and vote with their feet by selling off their shares in companies which do not warn, Kasznik and Lev [1995] reported findings suggesting the opposite. Specifically, they found that, controlling for the magnitude of the negative earnings surprise, firms that warn tend to experience more negative stock price reactions, and more negative analyst earnings forecast revisions, than those providing no warning. In this paper, we investigate analysts' reactions to qualitative warnings of adverse earnings and attempt to reconcile analysts' more negative forecast revisions, as documented by Kasznik and Lev [1995], and the apparently conflicting anecdotal evidence that suggests more positive responses