Finding Alpha in Earnings Surprises
The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. You should consult with an investment professional before making any investment decisions. The SUE explores the relationship between the performance of a business’s stock and its unexpected earnings. One of them Standardized Unexpected Earnings In The U S Technology Sector is using the mathematical formula known as the standardized unexpected earnings or SUE.
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The whole market reaction attributed to the earnings report, measured from 60 days before and after the earnings release, is estimated at 18%, which means that about a third of the whole market response is delayed. Naturally, analysts would want to eliminate “unexpected” earnings as much as possible as it means that they make accurate forecasts. Due to the unexpected nature, this difference is also referred to as an “earnings surprise”. But if it’s the other way around where the actual earnings are much less than the expected amount, then that is very unfortunate.
The study demonstrates that this trading strategy is most effective when fewer rather than more financial analysts follow the firms. Two cumulative abnormal return windows of a supplier’s returns—a 3-day window and a 60-day window—are regressed on the customer’s standardized unexpected earnings (SUE). SUE is a ranked variable that essentially measures a customer’s actual reported earnings per share (EPS) minus the median of the analysts’ forecasted EPS.
THREE-MONTH HOLDING PERIOD RETURNS AND MEAN EXCESS RETURNS BY SUE CATEGORY, 5 � # OF ANALYSTS
The limited investor attention hypothesis states that investors’ limited attention to the arrival of new information causes return anomalies. Linking exists when a customer accounts for more than 10% of a supplier’s total sales. High-frequency traders supply liquidity and mitigate market inefficiency, which implies the HFT actions lower the magnitude of the PEAD. 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 data you’re mentioning is not free; so we need to find a vendor who can let us use it for a reasonable price – in backtesting and live trading… The author is grateful for the contribution ofInstitutional Brokers Estimate System, Inc. for providing the earningsexpectations data used in this study. A�Stock transactions were made two monthsafter the end of the SUE quarter for the first three quarters and three monthsafter the end of the SUE quarter for the fourth quarter.
Financial Analysis
- Forecasting price/earnings can be tricky, which means that unexpected earnings may be the result of inaccurate analyst estimates.
- For example, Sultan (1994) finds that the unexpected earnings can beused as a discriminator between stocks that performed relatively well andstocks that performed relative poorly in Japan.
- For more Morgan Stanley Research on earnings surprises ask your Morgan Stanley representative or Financial Advisor for the full report, “Finding Alpha in Surprises” (Aug 6, 2020). Plus, more Ideas from Morgan Stanley’s thought leaders.
- 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.
- The whole market reaction attributed to the earnings report, measured from 60 days before and after the earnings release, is estimated at 18%, which means that about a third of the whole market response is delayed.
They use the models to forecast what the company can reasonably expect to generate in earnings during the upcoming accounting period. In other words, key customers’ earnings information is not fully incorporated into the suppliers’ outlook at the time of the surprise even though future returns are not entirely the result of limited investor attention. An earnings announcement is a piece of publicly available information, and the semi-strong form of market efficiency implies that the stock prices should immediately reflect this data. Any delay in such reflection or the ability to predict the stock price movement is an anomaly against a semi-strong form of efficiency. The post-earnings-announcement-drift, therefore, is termed an anomaly because its presence signifies market inefficiency. This tendency of a stock’s cumulative abnormal returns to drift towards earnings surprise is known as Post Earnings Announcement Drift or PEAD.
- Stocks with positive earnings surprises tend to drift upward following the earnings announcement.
- QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website.
- The study demonstrates that arbitrage profits could be generated if investors bought (short sold) the tech stocks with the highest earnings surprises (the lowest) two or three months after the end of the quarter.
- 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.
- That said, there’s no way to predict the exact amount but, with careful planning, businesses can usually forecast pretty accurately.
Post Earnings Announcement Drift (PEAD)
Analysts attribute it to the broader academic research in the field and broader recognition of the phenomenon among investors. The efficient market hypothesis (EMH) is that stocks reflect all available information. So while a positive surprise is always welcome, it’s still more comfortable if your business is earning within its expected amount. Finally, we update the next rebalance time to the beginning of the next calendar month. CFA Institute Research and Policy Center is transforming research insights into actions that strengthen markets, advance ethics, and improve investor outcomes for the ultimate benefit of society. Honestly, we do take your requests seriously and are all working 12 hours a day, 5-6 days a week, there’s just an enormous volume of basics to get right first before we extend deeper.
Regression results indicate a positive and significant relationship between suppliers’ abnormal returns and key customers’ earnings surprises surrounding and following the earnings announcement date. The economic rationale for using SUE is that earnings surprises are not immediately fully reflected in the stock price. This implies that investors can earn excess returns by buying stocks that have positive stock surprises. This behavior of stock prices drifting upward after a positive announcement is referred to as the post-earnings announcement drift. By studying the market price reaction of suppliers to the unexpected earnings announcements of key customers, the author examines the limited investor attention hypothesis. Her results indicate that suppliers’ abnormal returns are positively and significantly related to earnings surprises.
That said, even with all these considerations, analysts can still make mistakes that result in unexpected earnings. Analysts rely on several factors, such as the business or investment’s historical financial performance, or the current market condition. For example, an action that causes a public scandal will negatively affect a business’s prospective earnings, leading to negative unexpected earnings. When a business or an investment generates an earnings amount that is very different from what was expected, then it has “unexpected earnings”.
One of the most widely accepted explanations of PEAD is the investor’s underreaction to the earnings announcement. Heading into the first quarter, investors have underestimated the impact of COVID-19 on corporate bottom lines. Among the 1,500 largest companies in the Russell 3000, an index that represents about 98% of all U.S corporations, the number of companies missing first-quarter earnings estimates this year rose by 57% from the previous quarter. Relative strength indicators compare a stock’s price or return performance during a given time period with its own historical performance or with some group of peer stocks.
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. It’s often the case that an earnings surprise can be the product of cost-cutting, creative accounting and other quick fixes. As you can see there is a heavy focus on financial modeling, finance, Excel, business valuation, budgeting/forecasting, PowerPoint presentations, accounting and business strategy.
Yet, performance over the past 16 years has been more balanced across different size and liquidity cohorts. During the 2008 Financial Crisis, notably, investors disproportionately punished companies that disappointed on both revenue and earnings, while rewarding those that missed on earnings but beat on revenue. The SUE formula enables a trader or analyst to get an understanding of where the current pricing on a stock falls, whether it is within a single standard deviation of the expected price or not.
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. We observed a Sharpe ratio of 0.602 relative to SPY Sharpe of 0.43 using this implementation during the period of December 1, 2009 to September 1, 2019 in backtesting. A common belief among investors is that combining earnings and revenue surprises is most applicable to smaller companies—liquidity (i.e., how easy the stock is buy and sell quickly) being a key factor. Yet, in their analysis, the researchers found that post-announcement outperformance driven by earnings and revenue surprises tends to persist across all capitalization categories and trading-volume levels.