On the other hand, a higher portion of passive institutional investors investing in ETFs and Index funds reduce the informational efficiency of prices and accentuate Post Earnings Announcement Drift. According to the Journal of Behavioral and Experimental Finance by Josef Fink, high concentrations of institutional ownership can impede price adjustment. Small or individual traders form expectations different from sophisticated and institutional investors. There is a mixed conclusion over whether small investors cause Post Earnings Announcement Drift.
Scaled Earnings Surprise is a means of comparing the level of earnings surprise to the amount of disagreement between various analysts (since a wide range of expectations has different implications for what is “unexpected”). DCF analyses use future free cash flow projections and discount them via a required annual rate. If the value arrived at through the DCF is higher than the current cost of the investment, the opportunity could be a good one. Companies also release guidance to help analysts make accurate estimates, however, sometimes unexpected news or product demand will change the final outcome. Thus, SUE scores tend to discount surprises from companies with minuscule earnings, those covered by few analysts or those with forecasts all over the map.
5. Different earnings surprises measures: PEAD
- Then in accordance with the Efficient Market Hypothesis, we construct the revised market reaction (CAR_NEW) based on stock price jumps.
- On the other hand, we investigate PEAD strategies for different earnings surprise and find that the premium of PEAD constructed by FOM can fully explain that by ERROR.
- Many investors believe that combining earnings and revenue surprises are primarily for smaller companies and liquid stocks.
- In the A-share market, individual investors often display lagged responses and herd behavior, leading to post-earnings drift even months after the surprise.
An earnings surprise occurs when a company’s reported quarterly or annual profits are above or below analysts’ expectations. It describes the drift of a firm’s stock price in the direction of the firm’s earnings surprise for an extended period of time. Contrary to what the efficient market hypothesis predicts, an earnings surprise does not lead to a full, instantaneous adjustment of stock prices, but to a slow, predictable drift. Numerous studies have investigated the drift’s origins and properties, covering drivers such as insufficient risk adjustment of returns, trading frictions, or behavioral explanations.
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Conroy, Eades and Harris (2000) find that stockprices are significantly affected by earnings surprises in Japan. Hsu (2001) demonstrates that it isprofitable to take a long position in the portfolios with the highest earningssurprises and a short position in the portfolios with the lowest earningssurprises in the Asia/Pacific equity market. Levis and Liodakis (2001) concludethat positive and negative earnings surprises have an asymmetrical effect onthe returns of low- and high-rated stocks in the U.K. The objective of thisstudy is to contribute to the literature by adding this missing piece.
Only in the presence of an earnings information shock, EPS_PUB is positively correlated with the CAR, and the CAR can act as a proxy for the investor response. When there is no earnings information shock in the window, CAR may be interfered by financial anomalies, and the measurement of investors’ response is biased, which cannot effective proxy for investors’ reactions to earnings correction. It shows that when there is no earnings information shock in annual report announcement, the CAR is disturbed by other non-earnings information factors. Energy-services provider McDermott International Inc., for example, smashed analysts’ estimates with its quarterly results issued Oct. 30. Shares of gold-mining company Placer Dome Inc. have also languished despite recent upside surprises.
Thus, there exists a greater need for conducting an exhaustive analysis of the effectiveness of measuring earnings surprises in China’s stock market. Earnings surprises are widely used in the basic research on stock markets such as market efficiency and earning management. How to better measure earnings surprises is a core question in related empirical researches.
A substantial body of literature shows that analysts’ tendency to exhibit an optimistic bias in their earnings forecasts, revealing that the forecasts released by analysts are typically higher than the actual earnings 1–3. The overly optimistic forecasts not only suggest that analysts place excessive weight on their private information 4, but also withheld negative information causing lower pricing efficiency in the stock market 5. Nonetheless, analysts’ earnings forecasts remain an integral benchmark for current scholars to measure the market consensus 6. Much of the literature takes the average (the median or the latest) of analysts’ earnings forecasts before the earnings announcement as the market consensus, and then calculates earnings surprises. However, the overly optimistic forecasts may lead to the undervaluation of earnings shocks, which amplifies the investors’ sensitivity to earnings shocks. At the same time, due to a general short-selling restriction in China’s stock market, analysts are required to furnish a higher number of “buy” rating reports to enhance commission income, thereby leading to a stronger optimistic bias 7, 8.
Theres no earnings surprise when SUE equals zero; the actual earnings per share is in line with the consensus earnings estimate. While preliminary earnings constitute the primary unaudited operational data, their reliability remains consistently robust. Therefore, after the release of the preliminary earnings, investors take the earnings released by preliminary earnings as the expectation of the actual earnings. Subsequently, upon the issuance of annual report, EPS_PUB is a reasonable proxy for earnings surprises 20.
Stocks with positive earnings surprises tend to drift upward following the earnings announcement. Similarly, stocks with negative earnings surprises tend to drift downward after the announcement. Due to the unique performance disclosure mechanism of China’s stock market, some companies will release the earnings pre-announcement or the preliminary earnings, which precede the annual reports. Earnings pre-announcement typically provides a generalized earnings range, thereby offering a coarser granularity of earnings data 28. In order to avoid the early reaction of earnings information, we delete stocks that issued earnings pre-announcement within the year.
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In the A-share market, individual investors often display lagged responses and herd behavior, leading to post-earnings drift even months after the surprise. This asymmetry in information provides an opportunity for capturing considerable excess returns. Table 8 presents a significant positive correlation between FOM and investors’ active behavior.
Interestingly, earnings surprises can significantly influence a company’s stock price, often leading to increased volatility in the market following the announcement. Consistent trends in EPS are crucial; companies that frequently report positive surprises typically see rising stock prices, capturing optimistic investor sentiment. Interestingly, a study found that companies with a solid EPS growth rate often lead their industry peers in overall market performance. This post implements a strategy that standardizes the unexpected earnings of stocks and trades the top 5% of those standardized stocks. It is written based on a paper published in The Accounting Review by Foster, Olsen, and Shevlin (1984). Our implementation narrows down our universe to 1000 liquid assets based on daily trading volume and price, and the availability of fundamental data on the stocks in our data library.
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Leverage machine learning tools, such as the CatBoostClassifier, to identify data patterns and increase forecasting accuracy. Next we use a fine universe selection filter to extract quarterly EPS data and save it in a rolling window for each stock. We don’t trade during the first 36-month warm-up period because the window is not ready yet. After the warm-up period, we can calculate quarterly EPS change from four quarters ago and the standard deviation of the change over the prior eight quarters using historical EPS data saved in the rolling windows. By comparing projected earnings with reported earnings, stocks with positive surprises can be identified. According to Bernard & Thomas (1989), Post Earnings Announcement Drift patterns include two components.
Standardized Unexpected Earnings Strategy
The focus is on the U.S. technology sector as it has attracted significant public interest in recent years. This paper first examines if a trading strategy on the basis of earnings surprises worked in the U.S. tech sector. Next, include financial ratios like return on equity (ROE) and free cash flow per share; these are reliable indicators of potential surprises.
- We find that only when there are earnings shocks, there is a significant positive correlation between EPS_PUB and CAR, but when there is no earnings shock, the correlation is insignificant, and the coefficient of EPS_PUB declines by about 80%.
- Before the earnings release, the investors set an expectation while the company prepares its forward-looking statement (guidance).
- The unexpected earnings have been found to be useful in predicting abnormal stock returns.
- Earnings surprises, both good and bad, “are like cockroaches–you hardly ever get just one,” Abbott adds.
Learn accounting fundamentals and how to read financial statements with CFI’s free online accounting classes. Market dynamics are forces that will impact prices and the behaviors of producers and consumers. In a market, these forces create pricing signals which result from the fluctuation of supply and demand for a given product or service.
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SUE measures the earnings surprise in terms of the number of standard deviation above or below the consensus earnings estimate. The absolute value of SUE measures standardized earnings surprise the degree of unexpected earnings and the sign of SUE indicates whether the unexpected earnings are above or below the consensus estimate. That is, the greater the positive SUE the greater the earnings surprise above the earnings estimate while the smaller the negative SUE the greater the earnings surprise below the earnings estimate.
Unexpected earnings are an important component in the accounting/financial industry because of their potential significance for investors. Financial analysts create EPS estimates by analyzing previous earnings reports, current market trends, and company guidance. The standardized unexpected earnings (SUE) metric measures these surprises, offering insights into potential trading opportunities. The “surprise factor” is a commonly used fundamental factor to measure the difference between a company’s actual earnings and market expectations. If a company’s earnings exceed market expectations, it often results in earnings surprises, which can drive short-term stock price increases. Interestingly, over a period following the announcement, these companies tend to outperform their peers—this phenomenon is known as the Post-Earnings Announcement Drift (PEAD).
On average, the actual earnings are smaller than the analysts’ earnings forecasts, consistent with the analysts’ optimism bias 3, 15. The mean of FOM is -0.394, and the standard deviation is 0.651, which is less than the standard deviation of ERROR1 and ERROR2, indicating that FOM is less influenced by extreme values. The Earnings Surprise Indicator quantifies the gap between actual earnings per share (EPS) and projections made by analysts.
Forecasting price/earnings can be tricky, which means that unexpected earnings may be the result of inaccurate analyst estimates. However, when unexpected earnings – positive or negative – are the direct result of the company’s actions, they may offer important insights to investors about the future trajectory of the company’s stock. Our results differ from numerous studies documenting a positive relation between institutional demand and future returns.
The regression coefficients for earnings surprises are notably positive when each of the three earnings surprises measures are individually examined using CAR as an indicator of investors’ reactions to earnings information. Each earnings surprises measurement appears effective, the existing literature often does not differentiate between these three measurements in their detailed examinations of earnings surprises. For the variable ERROR1, representing the average of analysts’ earnings errors, the mean is -0.536, and the mean of ERROR2 is -0.155, the earnings surprises based on the latest value of analysts’ forecasts is smaller with that based on the average. This trend suggests that analysts’ forecasts tend to exhibit greater accuracy as the release of the annual report, the finding consistent with extant literature 16.
Excel Shortcuts PC Mac List of Excel Shortcuts Excel shortcuts – It may seem slower at first if you’re used to the mouse, but it’s worth the investment to take the time and… A company’s SUE score has nothing to do with the courtroom success of its lawyers. ☆The financial support of the Chicago Mercantile Exchange and the North Carolina Institute for Investments Research is gratefully acknowledged. Interestingly, research shows that a firm with less than five analysts covering it can see stock price movements twice as volatile compared to more widely followed firms. Standardized Unexpected Earnings, or SUE, provides insights into how actual earnings relate to consensus forecasts. By grasping these metrics, you can better predict how the market will react and make educated investment choices regarding earnings surprises. Expected earnings, as the name suggests, are the earnings a company is anticipated to generate.