This study examines market cap vs. MFE across 206 post-earnings momentum setups to see whether company size affects how far stocks move after earnings. You’ll learn which market-cap groups produced the largest next-day maximum favorable excursions, how those gains compared with maximum adverse excursion (MAE), why smaller stocks were more likely to reach large MFE targets, and whether market cap actually helped predict where stocks finished by the closing bell.
Throughout 2026, I’ve written dozens of studies about stock market statistics, which setups produce the cleanest trends, differences between sectors, and even if bigger EPS and revenue beats lead to bigger post-earnings momentum moves.
Now, after adding a new variable to my dataset, I’ve come up with a new question to study:
Do smaller stocks produce larger post-earnings momentum moves than large-cap stocks?
I analyzed 206 completed post-earnings momentum setups and compared company market capitalization with next-day maximum favorable excursion (MFE), maximum adverse excursion (MAE), and EOD closing performance.
One of my biggest findings:
Stocks with a smaller market were more than three times as likely to reach a 15% favorable excursion during the next trading session when compared with medium, large and mega-cap stocks.
But there is a catch…
The same small-cap stocks that produced the biggest opportunities also produced some of the largest adverse moves.
Here’s what the full 206-setup study found.
Quick Answer: What does market cap actually tell you about post-earnings momentum trading?
Across 206 completed post-earnings momentum setups, smaller-cap stocks produced much larger next-day price excursions than large-cap stocks. Companies below $1 billion averaged a 15.07% MFE, compared with just 6.30% for stocks worth more than $100 billion, but they also carried more downside volatility, with 8.74% average MAE versus 3.94% for $100B+ companies. Overall, market cap appears to be more useful for estimating how far a stock may move after earnings in either direction than for predicting whether the trade will ultimately succeed.
Key Statistics
Smaller companies produced substantially larger next-day maximum favorable excursions in this 206-setup study.
of sub-$1B setups reached at least a +9% MFE, compared with only 20.8% of $100B+ setups.
of sub-$1B setups reached a +15% MFE.
of $100B+ setups reached a +20% MFE.
Market cap had a statistically significant negative relationship with next-day MFE.
How Market Cap Affects Post-Earnings Momentum?
The relationship between market cap and post-earnings momentum was one of the clearest patterns in my dataset.
As company size increased, next-day maximum favorable excursion generally declined, suggesting that smaller stocks tend to offer much greater post-earnings movement than their large-cap counterparts.
Next-Day MFE Falls as Market Cap Rises
Average and median MFE across 206 completed post-earnings momentum setups.
Smaller-cap stocks produced substantially larger next-day favorable excursions, with both average and median MFE declining as market capitalization increased.
Smaller Stocks Produced the Largest Post-Earnings Moves
The decline in MFE across market-cap groups was surprisingly orderly.
Stocks valued below $1 billion averaged a 15.07% next-day MFE, followed by 12.45% for $1B to $5B stocks, 8.66% for $5B to $20B, 8.09% for $20B to $100B, and just 6.30% for companies worth more than $100 billion.
That means the smallest stocks in the study generated roughly 2.4 times the average favorable excursion of the largest companies.
The difference becomes even more dramatic when looking at the median rather than the average.
Sub-$1B stocks posted a 15.57% median MFE, compared with only 5.03% among $100B+ companies.
| Market Cap | Setups | Average MFE | Median MFE |
|---|---|---|---|
| <$1B | 23 | 15.07% | 15.57% |
| $1B–$5B | 52 | 12.45% | 9.72% |
| $5B–$20B | 60 | 8.66% | 6.63% |
| $20B–$100B | 47 | 8.09% | 7.27% |
| $100B+ | 24 | 6.30% | 5.03% |
In other words, the gap was not simply caused by a few explosive small-cap outliers. A typical sub-$1B setup still traveled roughly three times farther in the favorable direction than a typical mega-cap setup.
The pattern does not mean every small stock will explode after earnings, or that every large-cap stock will stall.
But across these 206 setups, the data points to a clear trend:
The smaller the company, the greater the potential size of the next-day post-earnings move.
Small Caps Were More Likely to Reach Large MFE Targets
Average MFE tells us that smaller stocks tended to travel farther after earnings, but hit rates make the difference much more practical for traders.
Instead of asking how far the average stock moved, I looked at how often each market-cap group actually reached +9%, +15%, and +20% maximum favorable excursion during the following session.
The contrast was substantial.
Among stocks valued below $1 billion, 65.2% reached at least +9% MFE, compared with only 20.8% of $100B+ companies.
More than half of the sub-$1B setups even reached +15%, while none of the $100B+ setups in the study reached +20%.
How Often Did Each Market-Cap Group Reach Large MFE Targets?
Percentage of 206 post-earnings setups that reached at least +9%, +15%, or +20% MFE during the following trading session.
| Market Cap | +9% MFE | +15% MFE | +20% MFE |
|---|---|---|---|
| <$1B | 65.2% | 52.2% | 26.1% |
| $1B-$5B | 55.8% | 23.1% | 13.5% |
| $5B-$20B | 41.7% | 13.3% | 6.7% |
| $20B-$100B | 38.3% | 12.8% | 2.1% |
| $100B+ | 20.8% | 8.3% | 0.0% |
What stands out is that the relationship isn’t limited to one arbitrary target.
The probability of reaching increasingly large favorable excursions generally declined as market cap increased. Sub-$1B stocks reached +15% MFE in 52.2% of setups and +20% in 26.1%, compared with just 8.3% and 0%, respectively, among $100B+ companies.
For a post-earnings momentum trader, that distinction may be more useful than average MFE alone. An average can be distorted by a handful of huge movers, but these hit rates tell us how frequently meaningful opportunities actually appeared.
In this dataset, large post-earnings extensions were not merely bigger among smaller companies.
They also happened much more often.
Smaller Stocks Also Had Much Larger Adverse Excursions
The larger MFE numbers come with an important catch:
Smaller stocks also tended to move much farther against the original earnings direction.
In other words, the same volatility that created larger post-earnings opportunities also created considerably more downside risk.
Stocks valued below $1 billion averaged a 15.07% MFE, but they also experienced an 8.74% average MAE. At the opposite end of the spectrum, $100B+ companies averaged only 6.30% MFE, while their average adverse excursion was just 3.94%.
That broad pattern is visible across the market-cap groups:
Average MFE vs. MAE by Market Cap
Smaller stocks offered more favorable movement after earnings, but traders also had to tolerate larger adverse excursions.
| Market Cap | Average MFE | Average MAE |
|---|---|---|
| <$1B | 15.07% | 8.74% |
| $1B-$5B | 12.45% | 6.28% |
| $5B-$20B | 8.66% | 6.37% |
| $20B-$100B | 8.09% | 4.70% |
| $100B+ | 6.30% | 3.94% |
The difference at the extremes is substantial. Sub-$1B stocks experienced more than twice the average adverse excursion of $100B+ companies, 8.74% versus 3.94%.
That helps explain why simply chasing the market-cap group with the highest MFE would be an incomplete way to interpret the results.
For post-earnings momentum traders, this is an important distinction. Smaller stocks offered substantially more opportunity, but they demanded substantially more tolerance for volatility along the way.
A setup capable of moving 15% or 20% in your favor is also more capable of producing a deep pullback, reversal, or stop-out before that opportunity develops.
So the lesson from the data isn’t that smaller is automatically better.
It’s that market cap appears to help describe the size of the battlefield: smaller companies tended to produce wider post-earnings swings in both directions, while larger companies generally produced more contained moves.
More opportunity does not necessarily mean less risk.
The $1B–$5B Range May Offer an Interesting Middle Ground
The $1B–$5B market-cap group stood out as a potential middle ground between explosive small-cap movement and lower large-cap volatility.
These stocks averaged a 12.45% MFE and 6.28% MAE, producing an average MFE-to-MAE ratio of about 1.98:1.
That was better than the sub-$1B group, which produced higher MFE but also substantially larger adverse excursions.
$1B–$5B Post-Earnings Setups
I would still treat this as an interesting dataset observation, not evidence that $1B–$5B is the optimal market-cap range.
But it is definitely a segment worth watching as my post-earnings momentum setup database grows.
The Relationship Between Market Cap & MFE Was Statistically Significant
The decline in MFE as market cap increased was NOT just something that appeared in the market-cap buckets.
When I tested the relationship across all 206 individual setups, the data showed a statistically significant negative correlation between company size and next-day maximum favorable excursion.
Using a Spearman correlation, market cap versus MFE produced:
Spearman ρ = −0.270, p < 0.001
Market Cap and MFE Showed a Statistically Significant Relationship
The pattern was not just visible in the market-cap buckets. It also held up when tested across all 206 individual setups.
This indicates a statistically significant negative relationship between market cap and next-day MFE.
In plain English, the negative correlation means that as market capitalization increased, next-day MFE generally decreased.
The relationship is not strong enough to suggest market cap can predict an individual stock’s MFE on its own, but it is strong enough to show that the broader pattern in the dataset is unlikely to be random.
The very small p-value is important here.
A result below 0.001 means there is very strong statistical evidence that market cap and MFE are related within this sample.
I also tested whether a handful of extreme stocks were creating the result.
After removing the smallest companies, the negative relationship remained. Removing the single largest MFE outlier also produced nearly the same result.
That makes the finding much harder to dismiss as a few explosive microcaps skewing the averages. Across the dataset as a whole, smaller companies consistently tended to generate larger next-day favorable excursions after earnings.
Bigger First-Hour Earnings Moves Don’t Fully Explain the Result
Bigger initial earnings reactions could have explained why smaller stocks produced larger next-day MFEs, but the relationship remained even after accounting for the size of the first-hour move.
The partial correlation between market cap and next-day MFE was still about ρ = -0.277, suggesting that company size may contain information about post-earnings excursion beyond simply measuring how large the original earnings reaction was.
Market Cap Did Not Predict Where Stocks Closed
Similarly, market cap had essentially no relationship with next-day EOD return.
The correlation was just ρ = -0.002, p = 0.974, which is effectively zero.
Smaller stocks tended to travel much farther during the session, but they were not meaningfully more likely to finish with a better closing return at the end of the next trading session.
That reinforces an important distinction:
Market cap appears to influence intraday excursion far more than closing direction.
Final Takeaway – Market Cap Vs. MFE
Market cap clearly mattered in this 206-setup study, but not in the way many traders might expect.
Smaller stocks produced much larger next-day favorable excursions, they also experienced larger adverse moves, and market cap had virtually no relationship with next-day closing return.
Final Takeaway
Across 206 completed post-earnings momentum setups, market cap helped explain how far stocks tended to move after earnings, but not where they ultimately closed.
In other words, market cap appears to be more useful for estimating how much a stock may move after earnings than for predicting whether it will actually finish the session higher in the original direction.
The data doesn’t say smaller stocks are safer or better. It says that when post-earnings momentum shows up in smaller companies, the battlefield is simply bigger.
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…
FAQ
Do small-cap stocks move more after earnings?
In this study, yes. Stocks valued below $1 billion produced a 15.07% average next-day MFE, compared with just 6.30% for stocks worth more than $100 billion. Smaller stocks also reached large MFE thresholds much more frequently.
Does market cap affect post-earnings momentum?
The data suggests that market cap affects the size of post-earnings price movement more than the final direction of the trade. As market cap increased, next-day MFE generally declined, with a statistically significant negative relationship between company size and favorable excursion.
What market cap had the highest average MFE?
Stocks with a market cap below $1 billion had the highest average MFE at 15.07%. They also posted a 15.57% median MFE, the highest of any market-cap group in the study.
What market cap produced the best MFE-to-MAE ratio?
The $1 billion to $5 billion group produced the strongest average MFE-to-MAE ratio at approximately 1.98:1. These stocks averaged 12.45% MFE and 6.28% MAE, making the group an interesting middle ground between upside potential and adverse volatility.
Are small-cap stocks riskier to trade after earnings?
They were more volatile in this dataset. Sub-$1B stocks averaged 8.74% MAE, compared with only 3.94% for $100B+ companies, meaning smaller stocks tended to move farther both in favor of and against the original earnings direction.
Do large-cap stocks have lower post-earnings volatility?
Generally, yes. The largest companies in the study produced both lower MFE and lower MAE, suggesting their next-day post-earnings moves were typically more contained than those of smaller companies.
What is maximum favorable excursion (MFE)?
Maximum favorable excursion, or MFE, measures the greatest unrealized gain a trade could have achieved after entry before the measurement period ended. In this study, MFE shows how far each stock moved in the original post-earnings direction during the following trading session.
What is maximum adverse excursion (MAE)?
Maximum adverse excursion, or MAE, measures the largest move against a trade after entry. It helps show how much drawdown or adverse volatility a trader may have needed to tolerate before the trade ended.
Does market cap predict whether a stock will go up after earnings?
Not reliably. Market cap had essentially zero correlation with next-day EOD return in this dataset, meaning smaller stocks were not necessarily more likely to finish with a better closing result. Market cap was much more informative about how far the stock moved intraday.
What market cap is best for momentum trading?
This study does not prove that one market-cap range is universally best. Sub-$1B stocks produced the largest MFEs, while the $1B to $5B group offered the strongest average MFE-to-MAE ratio, making it an interesting range to watch as the dataset grows.
References
The Paper Trading Journal. (n.d.). Post-earnings momentum database. Retrieved September 10, 2026, from https://papertradingjournal.com/post-earnings-momentum-database/
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