When a company announces earnings, the stock price doesn’t always adjust immediately. Instead, it often drifts in the direction of the earnings surprise for up to 60 days – a phenomenon called Post-Earnings Announcement Drift (PEAD). This market anomaly, studied since 1968, can provide traders with opportunities for above-average returns.
Here’s a quick breakdown of three strategies to capitalise on PEAD:
- Earnings Surprise Quantile Sorting: Rank stocks by earnings surprises (e.g., SUE or EAR metrics), buy top performers, and short underperformers. Holding for 60 days can generate annual returns of ~12.5%.
- Momentum with Volume Confirmation: Confirm earnings surprises with trading volume spikes. This reduces false signals and aligns trades with institutional activity, using stops and profit targets to manage risk.
- Value-Glamour Filtered PEAD: Focus on value stocks with positive earnings surprises and confirm with a three-day price reaction (EAAR). This approach yields annual returns of 16.6%–18.8%.
Each strategy has its strengths and trade-offs, depending on your risk tolerance and trading style. For instance, small-cap and illiquid stocks often show stronger drifts but can incur higher transaction costs. The key is systematic execution and disciplined risk management.
Example: In January 2026, SanDisk (SNDK) reported a 42% earnings beat, driving a 25% price jump. Traders who entered on Day 2 still saw a 48% gain over 60 days, showing the potential of these strategies.
Using Spreads to Trade the “P.E.A.D. Strategy” After Earnings | Long Verticals & Diagonals
1. Earnings Surprise Quantile Sorting
To analyse stocks based on earnings surprises, they are ranked into groups – usually deciles (10 groups) or quintiles (5 groups). The strategy involves buying stocks in the top group and selling those in the bottom group.
Earnings Surprise Metric Effectiveness
Different metrics are used to measure earnings surprises, each offering unique insights. A widely used metric is Standardised Unexpected Earnings (SUE), which calculates the difference between actual and expected earnings, adjusted for the standard deviation of past surprises. Another option is the Overnight Return Jump (ORJ), which measures the price change from the previous day’s close to the opening price after the announcement. For example, in the Chinese A-share market, an ORJ-based strategy delivered an average excess return of 6.78% per quarter.
The Earnings Announcement Return (EAR) is another popular metric, capturing the market’s reaction over a three-day period. Combining EAR with SUE has been shown to produce annual abnormal returns of about 12.5%. While these metrics are useful for identifying raw signals, they need to be paired with other factors to isolate trends that are likely to persist.
Signal Confirmation Factors
Not every earnings surprise translates into a lasting market impact. To distinguish meaningful signals, additional factors are considered. For instance, strong investor attention amplifies the price drift following positive surprises. On the other hand, delayed disclosures – when companies take longer to release full financial details – can lead to a 42% stronger subsequent drift.
Other indicators include higher trading volumes unrelated to prior activity, which suggest disagreement among investors, and increased dispersion in analyst forecasts, signalling that the surprise hasn’t been fully absorbed into the stock price.
Returns Amplification Through Filtering
Filtering stocks after signal confirmation further improves returns. For instance, illiquid stocks tend to show higher Post-Earnings Announcement Drift (PEAD) returns – ranging from 1.60% to 2.43% monthly – compared to liquid stocks, which only show returns of 0.04% to 0.14%. However, the downside is that transaction costs for illiquid stocks can offset 70% to 100% of these paper profits.
Another approach is to focus on stocks that consistently stay in their surprise quantile over multiple quarters, as they often experience sustained price momentum. Additionally, prioritising companies with high-quality earnings – those with steady cash flows and minimal one-off items – can make the drift more reliable.
2. Post-Announcement Momentum with Volume Confirmation
Instead of jumping into a trade right after an earnings announcement, this approach waits for the market to show clear signs of conviction through both price movement and trading volume. When an earnings surprise is substantial, institutional investors often drive up both price and volume. This combination acts as a filter, helping to distinguish real opportunities from market noise. By pairing volume confirmation with metric analysis, this strategy refines the earlier quantile sorting method, making it easier to identify genuine drift signals. Essentially, it adds a layer of scrutiny by requiring volume confirmation to validate price movements.
Earnings Surprise Metric Effectiveness
Metrics like the Overnight Return Jump (ORJ) are particularly effective for volume-confirmed momentum strategies because they capture the immediate reactions of institutional investors. Another useful metric is Standardised Unexpected Earnings based on Analyst Forecasts (SUEAF), which works well for identifying longer-term drift trends when combined with volume analysis. Together, these metrics enhance the ability to capitalise on post-announcement momentum.
Signal Confirmation Factors
A spike in trading volume is a strong indicator that a price move reflects actual investor conviction rather than speculative activity. Once metrics reveal a significant earnings surprise, volume analysis confirms if the price action is backed by institutional activity. For example, requiring the announcement-day volume to be at least 2.8 times the 30-day average is a solid signal of strong institutional interest. Both the high-volume return premium and post-earnings announcement drift (PEAD) provide valuable insights, each adding an extra layer of predictive power for post-announcement returns. As Amy Lyons from Financial Modelling Prep explains:
Buying after a confirmed positive surprise may miss some initial upside but aligns the trade with the observed drift, reducing the risk of being on the wrong side of a surprise.
Returns Amplification Through Filtering
Sophisticated strategies assign “drift scores” based on factors like the size of the earnings surprise, the extent of the volume spike, and how long excess returns persist. A common tactic is to enter the trade after a pullback, once the price breaks above the high of the trigger candle. Stops based on moving averages or ATR (Average True Range) are then used to secure gains. Interestingly, about 25% to 30% of post-earnings announcement drift tends to occur within the three-day windows surrounding the next three quarterly earnings announcements.
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3. Value-Glamour Filtered PEAD with Confirmation
Value stocks, known for their high book-to-market ratios, tend to show more subdued initial market reactions to earnings announcements compared to glamour stocks. However, their delayed price drifts are often stronger and more pronounced. This strategy takes a more refined approach by separating value stocks from glamour stocks to enhance signal precision.
Earnings Surprise Metric Effectiveness
The Earnings Announcement Abnormal Return (EAAR), which measures the three-day price movement following an earnings announcement, acts as a strong confirmation tool. The most robust drifts occur when the earnings surprise and the EAAR move in the same direction. For instance, a “double positive” scenario – where both the earnings surprise and the three-day EAAR are positive – validates a confident long position. Research has shown that focusing on value stocks with aligned positive signals while shorting glamour stocks with aligned negative signals can yield annual abnormal returns ranging from 16.6% to 18.8% before transaction costs.
Signal Confirmation Factors
Using the three-day EAAR to confirm the earnings surprise direction helps eliminate misleading signals. When the EAAR and earnings surprise diverge – such as a positive earnings surprise followed by a negative price reaction – the subsequent drift patterns become inconsistent and much weaker. Researchers Zhipeng Yan and Yan Zhao highlight this dynamic:
Value stocks have greater information uncertainty, show more muted initial market reactions to earnings surprises, and have better (more positive or less negative) post–earnings announcement drifts than do glamour stocks.
Returns Amplification Through Filtering
Focusing on stocks with higher illiquidity or zero leverage can significantly amplify returns by increasing information asymmetry. Liquidity risk alone accounts for 40% to 80% of the variation in PEAD portfolio returns across different stocks. This refined targeting aligns well with systematic strategies designed to capture consistent drift patterns. Notably, the PEAD effect in value stocks is primarily a long-side opportunity, allowing traders to benefit from the value premium without needing to short glamour stocks. Maintaining positions through the next three quarterly earnings announcements is recommended, as 25% to 30% of the total drift tends to occur around these future earnings dates.
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Strategy Comparison Tables
The table below summarises the key differences in execution and performance for three post-earnings drift strategies. Selecting the right approach depends on your risk tolerance, available capital, and preferred trading style. These strategies vary in their entry timing, holding periods, and overall performance.
Earnings Surprise Quantile Sorting involves entering on Day 2 to avoid initial volatility, with positions held for about 60 working days (one quarter). This method targets stocks in the top quintile for both SUE and EAR, achieving annual abnormal returns of approximately 12.5% when both metrics align. The delayed entry minimises event risk but may forgo the initial price movement.
Post-Announcement Momentum with Volume Confirmation takes a more aggressive stance. Entry occurs on Day 1 or 2 if the initial reaction is moderate but accompanied by a significant volume spike, as previously described. This strategy employs technical exits, such as a 10% profit target and a 5% stop-loss, to handle earnings-related volatility. A key feature is that higher volume levels tend to amplify post-event returns.
Value-Glamour Filtered PEAD focuses on high-SUE stocks meeting specific value criteria, such as firms with zero leverage or short-duration characteristics. Entry happens after confirming that the earnings surprise aligns with the three-day EAAR, and positions are held until the next earnings announcement. Research shows this strategy generates 16.6% to 18.8% annual abnormal returns, with the strongest gains coming from value stocks on the long side. Notably, 25% to 30% of the total drift typically occurs before the next earnings announcement.
| Strategy | Entry Timing | Exit Rule | Best For |
|---|---|---|---|
| Quantile Sorting (SUE/EAR) | Day 2 after announcement | Rebalance quarterly | Systematic traders seeking steady quarterly returns |
| Momentum + Volume | Day 1-2 if volume confirms | 10% profit target or 5% stop-loss | Active traders using technical exits |
| Value-Glamour Filtered | After EAAR confirmation | Hold until next earnings announcement | Long-term investors focusing on high-value stocks |
Interestingly, the EAR metric consistently outperforms traditional SUE strategies, delivering annual abnormal returns of 7.55%, compared to 6.25% for SUE. Additionally, EAR avoids the price reversal that often affects SUE strategies after three quarters. Across all three strategies, small-cap stocks play a crucial role in driving PEAD performance, as they tend to have higher information asymmetry and liquidity risks.
This breakdown highlights the unique strengths and trade-offs of each strategy, allowing traders to match their approach with their individual risk preferences and trading capabilities.
Conclusion
Post-earnings announcement drift (PEAD) continues to be a well-documented anomaly, offering traders the potential for quarterly returns ranging from 2.6% to 9.4% through strategies like Earnings Surprise Quantile Sorting, Volume-Confirmed Momentum, and Value-Glamour Filtering. Each method provides a unique approach to capitalising on this phenomenon, but consistent success requires systematic execution and disciplined risk management.
“The most important rule of trading is to play great defense, not great offence.” – Paul Tudor Jones, Hedge Fund Manager
Key to navigating this strategy is maintaining a structured workflow and adhering to strict risk controls. Position sizing plays a crucial role – limit your per-trade risk to 1–2% of your portfolio and cap your total exposure to earnings events at 5–10% to mitigate the risks tied to binary outcomes. Additionally, consider applying time stops – exit the trade if no drift occurs within 30 days or if the stock reverses its earnings-day move within five days.
Take, for example, SanDisk (SNDK). In January 2026, the company reported Q4 2025 earnings that exceeded consensus estimates by 42%, driven by AI-related storage demand. The stock surged 25% on the first day, but a systematic entry on Day 2 at $78 allowed traders to capture a further 48% gain as the stock climbed to $116 over the next 60 days. This demonstrates the power of disciplined, strategy-driven trading.
For traders looking to refine their skills, the Collin Seow Trading Academy offers a range of resources to master PEAD strategies. These include free e-courses like Market Timing 101 and Systematic Trading Profits, live webinars, and the Systematic Trader Programme – all designed to help traders remove emotions from their decisions. Visit https://collinseow.com for access to these courses, trading books, and video tutorials. With the right tools and mindset, traders can confidently navigate the complexities of post-earnings drift trading.
FAQs
How do I know if an earnings surprise is tradable or just noise?
An earnings surprise happens when a company’s financial results differ noticeably from what analysts had predicted. To figure out if this creates a trading opportunity, observe the market’s reaction. If the response is strong and continues over time, it may result in a post-earnings announcement drift (PEAD), which traders can potentially act on. However, if the price shifts are minor or fade quickly, it’s probably just market noise. Pay attention to lasting trends, as they suggest the market is digesting the surprise in a meaningful way.
Which PEAD strategy fits my risk level and time commitment?
PEAD strategies come with different levels of risk and time investment. If you’re looking for a lower-risk, less time-consuming option, consider systematic strategies that target short-term post-earnings drifts. These typically involve shorter holding periods and rely on automated signals, making them more manageable. On the other hand, if you’re an active trader willing to take on more risk, you might explore longer-term or multi-factor strategies. These require greater involvement but could potentially lead to higher returns. The best choice depends on your risk appetite and how much time you can commit.
How do I manage liquidity and transaction costs when trading PEAD?
Managing liquidity and transaction costs in post-earnings announcement drift (PEAD) trading requires a thoughtful approach. Start by prioritising liquid stocks, as these tend to have lower transaction and market impact costs, which helps protect your profits. Be mindful of trade sizes – keeping them controlled can prevent unnecessary market disruptions. Timing is also crucial; executing trades soon after earnings announcements can reduce costs, but it demands precise planning. By combining these strategies, you can make your PEAD trading more efficient while keeping expenses in check.
