Based on 142 post-earnings momentum setups, Communication Services averaged 10.58% MFE with just 3.26% MAE, Consumer Discretionary produced a 76.7% favorable next-day close rate, and Technology averaged an 11.48% MFE across 56 setups. In this study, we’ll compare market sectors by MFE, MAE, and next-day continuation to see which have produced the cleanest post-earnings momentum setups so far.
Earnings season produces some of the biggest short-term price moves in the market—but are there any stock market sectors that produce larger moves, cleaner trends, or higher volatility?
Using my post-earnings momentum data, I compared sector performance based on maximum favorable excursion (MFE), maximum adverse excursion (MAE), next-day directional performance, and exit strategy.
The interesting finding?
The sector producing the largest raw moves wasn’t necessarily the sector producing the cleanest trades.
In the following study, we’ll explore which sectors produce the cleanest post-earnings momentum, whether bigger moves actually mean better trades, and how traders and investors can apply these findings to their strategies.
Quick Answer: Which stock market sectors are best for day trading?
Communication Services and Consumer Discretionary produced the strongest post-earnings momentum results. Communication Services averaged 10.58% MFE, just 3.26% MAE, and 80% next-day EOD continuation, while Consumer Discretionary averaged 10.34% MFE, 3.85% MAE, and 76.7% EOD continuation. Technology generated the highest MFE of the three at 11.48%, but with 6.39% MAE and 53.6% EOD continuation.
| Sector | Avg. MFE | Avg. MAE | Favorable Next-Day EOD |
|---|---|---|---|
| Communication Services | 10.58% | 3.26% | 80.0% |
| Consumer Discretionary | 10.34% | 3.85% | 76.7% |
| Technology | 11.48% | 6.39% | 53.6% |
| Healthcare | 18.91% | 7.11% | 66.7% |
| Industrials | 8.15% | 5.37% | 53.3% |
| Materials | 12.44% | 2.27% | 50.0% |
| Financials | 4.18% | 8.14% | 20.0% |
Key Statistics — Best Sectors for Post-Earnings Momentum
- Communication Services: Cleanest overall results with 10.58% average MFE, just 3.26% MAE, and 80% favorable next-day EOD continuation.
- Consumer Discretionary: Strong across all three measures with 10.34% MFE, 3.85% MAE, and 76.7% EOD continuation.
- Technology: Produced a higher 11.48% average MFE, with 6.39% MAE and 53.6% EOD continuation.
- Best +9% target rate: Consumer Discretionary reached +9% before -5% in 60% of setups, versus 53.3% for Communication Services and 42.9% for Technology.
Communication Services Produced the Cleanest Price Action
Communication Services stands out immediately when MFE and MAE are considered together. Across 15 completed setups, stocks in this sector produced an average MFE of 10.58% compared with average MAE of only 3.26%.
That’s approximately 3.25 percentage points of favorable movement for every percentage point of adverse movement—the strongest MFE/MAE relationship among sectors with meaningful sample sizes.
Even more interesting was what happened by the end of the following trading day.
A full 80% of Communication Services setups finished the next day moving in the expected direction. That’s the highest rate among the five sectors in the dataset with at least 10 observations.
The +9%/-5% exit test tells a similar story. 53.3% of Communication Services setups reached a +9% favorable move before suffering a -5% adverse move.
These stocks weren’t necessarily producing the biggest post-earnings moves.
Instead, they tended to produce something potentially more valuable to a momentum trader: directional efficiency.
The initial earnings reaction was comparatively likely to continue without requiring the trade to survive a huge move in the opposite direction first.
Consumer Discretionary May Be the Best Sector to Actually Trade
If Communication Services produced the cleanest price action, Consumer Discretionary may have produced the most practically tradable setups.
This result is particularly interesting because the sample is twice as large.
Across 30 Consumer Discretionary setups, average MFE reached 10.34%, while average MAE was only 3.85%.
That’s an MFE-to-MAE ratio of approximately 2.69-to-1.
But the strongest result comes from applying a hypothetical +9% profit target and -5% stop loss. Exactly 60% of Consumer Discretionary setups reached +9% before falling -5%.
That was the highest success rate among every sector with at least 10 observations. Next-day directional performance was similarly strong. 76.7% of setups finished the following trading day in the expected direction.
Put these numbers together and Consumer Discretionary begins to look particularly interesting.
The sector didn’t produce spectacularly larger MFEs than the rest of the dataset. Instead, it repeatedly generated enough movement to reach a relatively ambitious profit target while keeping average adverse movement below 4%.
For an actual trading strategy, that combination may be more useful than simply identifying the sector capable of producing the biggest individual moves.
Technology Produced Strong MFE but Weaker Continuation
Technology presents almost the opposite lesson.
First, it’s important to acknowledge that Technology dominates the dataset. With 56 completed setups, it accounts for nearly 40% of all observations in this study.
That makes its results considerably harder to dismiss as random noise.
Technology stocks produced an impressive 11.48% average MFE, higher than both Communication Services and Consumer Discretionary.
But average MAE was also 6.39%.
That gives Technology an MFE-to-MAE relationship of only about 1.80-to-1, substantially below Communication Services’ 3.25-to-1 and Consumer Discretionary’s 2.69-to-1.
The difference becomes even clearer when looking at the +9%/-5% test.
Only 42.9% of Technology setups reached +9% before -5%. And just 53.6% finished the following trading day in the expected direction.
Technology stocks therefore appear very capable of producing large post-earnings price swings. The problem is that those swings aren’t always particularly clean.
A Technology stock might ultimately offer 10%, 15%, or even greater favorable excursion while also producing enough volatility in the opposite direction to stop out a trader long before the full move develops.
That leads to one of the most important findings from this study:
Technology produced larger average opportunities, but Consumer Discretionary and Communication Services produced cleaner, more directional post-earnings momentum.
For momentum traders, the distinction matters. Maximum opportunity and realistic tradeability aren’t necessarily the same thing.
Additional Findings and Limitations
There are several reasons these results should be treated as exploratory rather than definitive. The biggest limitation is simply our post-earnings momentum sample size.
The study contains 142 completed setups, but once they’re divided across sectors, the individual samples become considerably smaller. Technology has a relatively strong 56 observations and Consumer Discretionary has 30, but Communication Services and Industrials contain only 15 each, while Healthcare contains 12.
Several other sectors contain fewer than 10 observations.
Materials, for example, generated a remarkable 12.44% average MFE against only 2.27% average MAE, and 100% of its setups reached +9% before -5%. Unfortunately, there were only two observations, making the result virtually meaningless for drawing broader conclusions.
Financials were at the other extreme. Across five observations, average MFE was only 4.18% compared with 8.14% MAE, while none reached +9% before -5%.
Again, however, five trades aren’t enough to confidently conclude that Financials are inherently poor post-earnings momentum candidates.
Healthcare provides another warning about relying exclusively on averages.
Its 18.91% average MFE was easily the highest among sectors with at least 10 observations. At first glance, that might make Healthcare look like the clear winner.
But one setup generated an enormous 95.17% MFE, substantially pulling the sector average upward. Meanwhile, only 33.3% of Healthcare setups reached +9% before -5%, and average MAE was a relatively high 7.11%.
That’s precisely why looking only at average MFE can be misleading.
There are also potential confounding variables.
Sector membership isn’t the only thing separating these trades. First-hour candle size, market capitalization, short interest, earnings surprise, guidance, liquidity, breakout structure, and whether the setup was bullish or bearish could all influence the results.
Conclusion – Sector Vs. Momentum Performance
The early evidence suggests that the sectors producing the biggest post-earnings moves aren’t necessarily producing the best momentum trades.
Technology illustrates this perfectly.
Across 56 setups, Technology generated a strong 11.48% average MFE, but traders also faced 6.39% average MAE.
Communication Services and Consumer Discretionary told a different story.
Communication Services produced 10.58% average MFE against just 3.26% MAE, while 80% of setups finished the next day moving in the expected direction.
Consumer Discretionary produced similarly clean numbers across a larger sample of 30 setups, including a 60% probability of reaching +9% before -5% and a 76.7% favorable next-day close rate.
For now, that makes Consumer Discretionary particularly compelling from a trading perspective, while Communication Services takes the title for the cleanest overall price action.
But perhaps the broader lesson is more useful than the sector rankings themselves.
When evaluating post-earnings momentum chart setups, the size of the potential move is only half the equation.
How much adverse movement occurs along the way—and how consistently the stock actually continues in the expected direction—may matter just as much.
While my dataset may still be relatively small, for now, the data points to Communication Services and Consumer Discretionary as the sectors most likely to deliver the combination momentum traders want: strong MFE, limited MAE, and reliable next-day continuation.
If you want to go deeper:
- Explore the Trading Statistics Hub to understand how different sectors behave across market cycles
- Study real setups inside the Trade Reviews section
- Learn the framework behind high-probability setups in the Post-Earnings Momentum Strategy
This is how you turn raw market data into repeatable trading edge.
More Trading Statistics…
Frequently Asked Questions
Which sector produced the cleanest post-earnings momentum setups?
Communication Services produced the cleanest overall price action in this study. Across 15 setups, the sector averaged 10.58% MFE versus just 3.26% MAE, while 80% of setups finished the following trading day in the expected direction.
Which sector had the best next-day continuation rate?
Among sectors with at least 10 observations, Communication Services ranked first with an 80% favorable next-day EOD continuation rate. Consumer Discretionary was close behind at 76.7%, followed by Healthcare at 66.7%, Technology at 53.6%, and Industrials at 53.3%.
Which sector had the highest average MFE?
Healthcare recorded the highest average MFE at 18.91%, although this figure was heavily influenced by a single setup that reached a 95.17% MFE. Among the three largest and most closely examined groups, Technology had the highest average MFE at 11.48%.
Which sector had the lowest average MAE?
Communication Services had an average MAE of just 3.26%, while Consumer Discretionary averaged 3.85%. Materials recorded an even lower 2.27% MAE, but the sector contained only two observations and therefore isn’t yet a meaningful comparison.
Which sector performed best with a +9% profit target and -5% stop loss?
Consumer Discretionary produced the strongest result among sectors with at least 10 observations. Exactly 60% of its 30 setups reached +9% before -5%, compared with 53.3% for Communication Services and 42.9% for Technology.
How did Technology stocks perform after earnings?
Across 56 Technology setups, average MFE was 11.48% and average MAE was 6.39%. Technology setups finished the following trading day in the expected direction 53.6% of the time, while 42.9% reached +9% before -5%.
How large is the dataset used in this study?
The study includes 142 completed post-earnings momentum setups. Technology represents the largest individual sector with 56 observations, followed by Consumer Discretionary with 30. Several sectors have much smaller samples, so these findings should be considered preliminary.
Does sector alone determine whether a post-earnings momentum setup will work?
No. Sector is only one variable. First-hour price movement, earnings surprise, guidance, short interest, liquidity, market capitalization, breakout structure, and trade direction may also affect post-earnings momentum. The sector results are best treated as another piece of information for evaluating a setup rather than a standalone trading signal.
References
Laforest, J. (2026). Post-earnings momentum database. Paper Trading Journal. https://papertradingjournal.com/post-earnings-momentum-database/
Laforest, J. (2026, August 19). How much does a stock’s first-hour earnings reaction tell us about what happens next? Paper Trading Journal. https://papertradingjournal.com/2026/08/19/how-much-does-a-stocks-first-hour-earnings-reaction-tell-us-about-what-happens-next/
Laforest, J. (2026, August 18). Do bigger EPS and revenue beats lead to bigger post-earnings momentum moves? Paper Trading Journal. https://papertradingjournal.com/2026/08/18/do-bigger-eps-and-revenue-beats-lead-to-bigger-post-earnings-momentum-moves/
Laforest, J. (2026, August 11). How to identify the strongest post-earnings momentum setups. Paper Trading Journal. https://papertradingjournal.com/2026/08/11/how-to-identify-the-strongest-post-earnings-momentum-setups/
Laforest, J. (2026, August 10). Does high short interest create stronger post-earnings momentum setups? Paper Trading Journal. https://papertradingjournal.com/2026/08/10/does-high-short-interest-create-stronger-post-earnings-momentum-setups/
Laforest, J. (2026, July 13). Is it better to trade long or short? Paper Trading Journal. https://papertradingjournal.com/2026/07/13/is-it-better-to-trade-long-or-short/
Laforest, J. (2026, July 12). How to improve trading exit strategy. Paper Trading Journal. https://papertradingjournal.com/2026/07/12/how-to-improve-trading-exit-strategy/
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