Similarly, stocks with negative earnings surprises tend to drift downward after the announcement. 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. We calculate the unexpected earnings at the beginning of each month, standardize the unexpected earnings, go long on the top 5%, and rebalance the portfolio monthly.
Different classes of institutional investors have a different effect on Post Earnings Announcement Drift. On the other hand, occasional investors exploit the Post Earnings Announcement Drift and lower its occurrence. Active institutional ownership dilutes the impact of Post Earnings Announcement Drift. Small or individual traders form expectations different from sophisticated and institutional investors.
What Are Some Factors That Can Influence Post Earnings Announcement Drift Movements?
However, the team also found that earnings-surprise outperformance was higher in small- and mid-cap stocks in bear markets. As for large-cap stocks, the performance led by revenue surprises tends to be higher during bull markets. SUE measures the earnings surprise in terms of the number ofstandard deviation above or below the consensus earnings estimate.
How Do Investors Take Advantage of Post Earnings Announcement Drift?
Studies have shown that positive unexpected earnings can lead to an immediate increase in a stock’s price. If the actual earnings are greater than the expected earnings, then there positive unexpected earnings. As we mentioned, Post Earnings Announcement Drift is an inefficiency that investors can capitalize on if they buy stocks with high earnings surprises and hold them for nearly two months. The Open-Quant League is a quarterly competition between universities and investment clubs for the best-performing strategy. Having a data set with future expected earnings and earnings release dates is something I raised sometime ago but wasn’t seen as important.
THREE-MONTH HOLDING PERIOD RETURNS AND MEAN EXCESS RETURNS BY SUE CATEGORY, 5 � # OF ANALYSTS
- We observed a Sharpe ratio of 0.83 relative to SPY Sharpe of 0.88 using this implementation during the period of December 1, 2009 to September 1, 2019 in backtesting.
- That said, even with all these considerations, analysts can still make mistakes that result in unexpected earnings.
- It may help them in predicting when the price might fall or rise, and whether or not the rise/fall is within the standard deviation of the expected price.
- Standardized unexpected Earnings (SUE) is a momentum indicator that is positively related to subsequent stock returns.
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- 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.
The SUE explores the relationship between the performance of a business’s stock and its unexpected earnings. One of them is using the mathematical formula known as the standardized unexpected earnings or SUE. To determine a business or investment’s unexpected earnings, we can employ various techniques. Each period, analysts employ certain techniques to predict the expected earnings of a business or investment. Bartosiak also suggests investors look for stocks about which they can get an earnings tip-off even before the actual announcement.
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. This study is based upon a sampleof the U.S. tech firms with fiscal year ending in March, June, September orDecember compiled in I/B/E/S History database for the period 1994 � 2000. Toeliminate firms with inactive trading, the sample includes only those firmsfollowed by at least three financial analysts. The sample universe consists ofroughly 270 tech firms in 1994, growing to 500 firms in 2000, resulting in 7966stock-quarter observations for the analysis. It’s important to take note of unexpected earnings as they can hugely affect a business or investment’s stock price.
SUE QUARTER
Conroy, Eades and Harris (2000) find that stockprices are significantly affected by earnings surprises in Japan. 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. Thefocus is on the U.S. technology sector as it has attracted significant publicinterest in recent years.
This behavior of stock prices drifting upward after a positive announcement is referred to as the post-earnings announcement drift. Standardized unexpected Earnings (SUE) is a momentum indicator that is positively related to subsequent stock returns. A popular investment strategy based on SUE is the post earnings announcement drift trading strategy. This strategy exploits the observed phenomenon that the stock price tends to drift in the days after the earnings announcement. A strategy that buys stocks with a positive surprise and sells stocks with a negative surprise generally generates alpha. Stocks with positive earnings surprises tend to drift upward following the earnings announcement.
The estimation period is the time taken by the analyst to forecast the expected earnings. Financial analysts make mathematical standardized unexpected earnings and financial models of a company’s earnings from other accounting periods. They use the models to forecast what the company can reasonably expect to generate in earnings during the upcoming accounting period.
- Keep in mind that although we use quarterly EPS data, the portfolio rebalances monthly.
- The difference between the actual earnings and expected earnings is the business or investment’s unexpected earnings.
- Earnings and revenue are the two primary benchmarks that help the market gauge their financial health and ascertain if they are on their path to progress.
- This can result in unexpected earnings due to an inaccurate figure for expected earnings.
- SUE measures the earnings surprise in terms of the number ofstandard deviation above or below the consensus earnings estimate.
- Stocks with positive earnings surprises tend to drift upward following the earnings announcement.
Earnings surprise
It may help them in predicting when the price might fall or rise, and whether or not the rise/fall is within the standard deviation of the expected price. It’d be great if the earnings figure is greater than the expected amount, but there’s also the possibility of it being less than the expected amount. Join 1,400+ traders and investors discovering the secrets of legendary market wizards in a free weekly email. Copy this strategy code to your QuantConnect account and deploy it live with your brokerage. Join QuantConnect’s Discord server for real-time support, where a vibrant community of traders and developers awaits to help you with any of your QuantConnect needs. Upgrading to a paid membership gives you access to our extensive collection of plug-and-play Templates designed to power your performance—as well as CFI’s full course catalog and accredited Certification Programs.
We observed a Sharpe ratio of 0.83 relative to SPY Sharpe of 0.88 using this implementation during the period of December 1, 2009 to September 1, 2019 in backtesting. Many investors believe that combining earnings and revenue surprises are primarily for smaller companies and liquid stocks. Yet, researchers found that post-earnings announcement drift persists across all capitalization categories and trading-volume levels.