Does a bigger earnings beat or miss lead to a bigger post-earnings momentum move? I analyzed 44 earnings setups from my post-earnings momentum database to compare EPS and revenue surprise magnitude with next-day maximum favorable excursion (MFE). Below, we explore the results which show virtually no correlation between EPS surprise size and MFE (r = +0.048) and only a weak relationship for revenue (r = +0.215)—suggesting that how the market reacts to earnings may matter more for momentum traders than the size of the surprise itself.
It seems intuitive that the size of an earnings surprise should matter. But honestly, nothing much happens from day to day on the stock market that’s inherently intuitive.
If a company beats EPS estimates by 50% instead of 5%, or reports revenue 10% above expectations instead of barely scraping past consensus, traders might reasonably expect a larger post-earnings move.
The same logic should theoretically apply in reverse, where a large EPS or revenue miss should create stronger bearish momentum than a minor disappointment.
But does the data actually support that assumption?
To find out, I analyzed 44 post-earnings momentum setups from my trading dataset. I analyzed both short and long setups, as well as the underlying company’s EPS and revenue beat or miss to determine any potential correlation between variables.
The results were surprisingly weak.
Finding: Revenue surprise showed more correlation with next-day MFE than EPS surprise, but neither relationship was statistically significant.
Quick Answer: Which Is More Important for Post-Earnings Momentum Trading, EPS or Revenue?
Based on my dataset, revenue appears slightly more informative than EPS, but neither reliably predicts the size of the next-day momentum move. Across 44 setups, the absolute magnitude of EPS surprises had virtually no correlation with next-day MFE (Pearson r = +0.048; Spearman ρ = +0.103), while revenue surprises showed a weak positive relationship (Pearson r = +0.215; Spearman ρ = +0.256). Larger revenue beats therefore showed somewhat more evidence of being associated with stronger momentum than larger EPS beats, but the relationship was still too weak to use revenue surprise magnitude as a standalone trading signal.
Key Statistics – EPS & Revenue Vs. MFE
- 44 post-earnings setups had complete EPS surprise, revenue surprise and next-day MFE data.
- EPS surprise size showed virtually no correlation with next-day momentum: Pearson r = +0.048 and Spearman ρ = +0.103.
- Revenue surprise showed a slightly stronger—but still weak—relationship with MFE: Pearson r = +0.215 and Spearman ρ = +0.256.
- Neither relationship was statistically significant: EPS p ≈ 0.76 and revenue p ≈ 0.16.
- Bigger EPS beats did not produce progressively bigger moves. EPS beats of 10–25% had a 7.80% median MFE, versus only 4.43% for beats above 100%.
- Larger revenue beats showed more promise. Revenue beats of 5–10% produced a 16.96% median MFE, the strongest revenue-surprise bucket.
- Misses created substantial bearish opportunities: EPS misses averaged 11.96% MFE, while revenue misses averaged 13.89% MFE.
- Fundamental/price alignment stood out more than surprise magnitude. When fundamentals and the initial market reaction agreed, median MFE was 9.00%, versus just 3.30% when they disagreed.
- Bottom line: The size of an EPS or revenue surprise alone was a poor predictor of how much post-earnings momentum remained.
What Does an Earnings (EPS) Surprise Size Actually Tell Us?
EPS Surprise Had Almost No Correlation With Next-Day Momentum
The clearest finding from the study was also one of the most surprising: the magnitude of the EPS surprise provided almost no information about the size of the subsequent favorable move.
Using the absolute EPS surprise allowed positive beats and negative misses to be evaluated based on magnitude rather than direction. If the intuitive hypothesis were correct, increasingly large surprises should generally have been associated with increasingly large MFEs.
Instead:
Absolute EPS surprise vs. MFE
- Pearson correlation: +0.048
- Spearman correlation: +0.103
Both are extremely weak correlations, but the Pearson result is particularly striking.
A correlation of +1 would represent a perfect positive linear relationship, while zero represents essentially no linear relationship.
At +0.048, EPS surprise magnitude was effectively unrelated to next-day MFE within this sample.
The Spearman correlation tells a similar story. Even when comparing the rank order of earnings surprises rather than allowing extreme observations to dominate the calculation, larger EPS surprises still did not consistently rank alongside larger MFEs.
Bigger EPS Beats Didn’t Produce Progressively Bigger Moves
Breaking the results into buckets makes the lack of a clear relationship easier to see.
Finding: Larger EPS beats did not produce progressively larger next-day MFEs. The 10–25% beat group recorded a 7.80% median MFE, compared with just 4.43% for EPS beats above 100%.
If surprise magnitude were strongly predictive, this table should form something resembling a staircase: larger beats followed by progressively larger MFEs.
It doesn’t.
The 10–25% EPS beat group actually produced a substantially higher median MFE than the 100%+ group. Even the EPS-miss group produced an 11.96% average MFE.
That does NOT mean EPS results don’t matter.
Rather, the data suggests that the magnitude of the EPS surprise alone isn’t enough to estimate how much post-earnings momentum remains after the initial reaction.
Revenue Surprise Showed More Signal — But Not Much
Revenue produced a somewhat different result.
Absolute revenue surprise vs. MFE:
- Pearson correlation: +0.215
- Spearman correlation: +0.256
Those numbers aren’t strong enough to establish a reliable predictive relationship, but they’re noticeably higher than the EPS correlations.
Revenue surprise magnitude therefore appears to contain some information about subsequent momentum, although this dataset doesn’t provide enough evidence to conclude that increasingly large revenue surprises reliably produce increasingly large moves.
The bucket analysis is particularly interesting:
Finding: Revenue showed more evidence of a relationship with next-day momentum than EPS. Revenue beats above 5% averaged MFEs above 13%, although small sample sizes mean the results should be treated as an interesting signal rather than a trading rule.
There is at least a hint of a pattern here.
Revenue beats below 5% generated average MFEs of roughly 8%, while beats above 5% produced average MFEs above 13%.
But sample sizes become small quickly, and the medians aren’t perfectly progressive. This should therefore be treated as an interesting signal worth monitoring rather than a trading rule.
Earnings Misses Can Produce Some of the Strongest Momentum
One of the most important distinctions in this study is that MFE is directional.
I’m not measuring whether a stock went higher after earnings. I’m measuring how far it moved favorably relative to the direction of the post-earnings momentum setup.
That means an earnings miss followed by a 15% breakdown can be every bit as successful as a bullish setup followed by a 15% rally.
This helps explain an otherwise strange-looking result: EPS misses averaged an 11.96% MFE and revenue misses averaged 13.89%.
A 15% selloff can be just as valuable to a short setup as a 15% rally is to a long setup.
11.96%
Average MFE
13.89%
Average MFE
Some of the strongest momentum opportunities in the dataset came from companies disappointing the market.
This reinforces an important distinction between investing and momentum trading.
A momentum trader doesn’t necessarily need good earnings. The trader needs a strong market reaction with sufficient continuation after the initial earnings move.
Massive Beats Don’t Necessarily Produce Massive Continuation
Some of the clearest examples of this weak correlation can be found in stocks I’ve already examined in individual post-earnings case studies.
RBLX is perhaps the best example. Roblox beat EPS estimates by 21.00%, but missed revenue estimates by 7.54%. Despite the EPS beat, shares initially fell 11.67% following earnings and subsequently produced another 21.40% MFE in the bearish direction.
The important number wasn’t necessarily the 21% EPS beat. The market had already decided that the overall earnings report warranted selling.
PLTR provides a very different example. Palantir beat EPS estimates by 17.14% and revenue estimates by 7.18%, while also issuing strongly bullish guidance. Shares initially rallied 12.05%, followed by another 16.68% MFE the next day.
BLMN produced an even larger EPS surprise. Bloomin’ Brands beat EPS estimates by 39.28%, but revenue by a comparatively modest 2.09%. Its initial earnings move was +11.78%, followed by an impressive 24.97% next-day MFE.
Then there’s APPS, which beat EPS estimates by 35.71% and revenue estimates by 10.80%. Digital Turbine (APPS) initially rallied 15.85% and subsequently produced a 27.80% MFE, making it one of the strongest bullish continuation setups in the dataset.
These are all substantial earnings surprises, but the relationship isn’t proportional:
- RBLX: +21.00% EPS / -7.54% revenue → 21.40% bearish MFE
- PLTR: +17.14% EPS / +7.18% revenue → 16.68% bullish MFE
- BLMN: +39.28% EPS / +2.09% revenue → 24.97% bullish MFE
- APPS: +35.71% EPS / +10.80% revenue → 27.80% bullish MFE
And RDDT adds perhaps the most interesting counterexample. Reddit beat EPS estimates by 26.26% and revenue estimates by 8.04% while issuing strongly bullish guidance. Yet shares initially sold off 8.05%, and that bearish move still produced 17.55% MFE before eventually reversing higher.
That’s an important distinction for momentum traders.
The question isn’t simply whether a company beat or missed estimates—or even how badly it did so. Fundamentals matter, but price action is ultimately a real-time representation of how the market is interpreting the news.
The market can sell a substantial beat, rally a relatively modest beat, or completely reverse its initial reaction as investors digest guidance, valuation and the rest of the earnings report.
The size of the surprise tells us what happened relative to analyst estimates. The price reaction tells us how the market actually interpreted it.
Why Doesn’t a Bigger Earnings Surprise Guarantee a Bigger Move?
Earnings Expectations Are More Complicated Than Consensus Estimates
An EPS or revenue surprise is generally calculated relative to published analyst consensus. But the market’s expectations aren’t necessarily identical to that consensus number.
Positioning, whisper numbers, previous guidance, valuation, recent price performance, institutional expectations and countless other variables can influence how investors interpret exactly the same earnings result.
A 20% EPS beat can therefore disappoint a market that was positioned for something spectacular, while a modest 5% beat can trigger a major repricing if expectations were low enough.
The percentage surprise tells us what happened relative to one benchmark.
But… Price tells us how the market interpreted it.
Fundamentals and Price Reaction Agreeing May Matter More
One of the most interesting findings came from comparing setups where the fundamentals agreed with the direction of the initial earnings move.
Among the 44 observations:
Finding: When fundamentals and the initial price reaction agreed, median MFE reached 9.00%—nearly three times the 3.30% median MFE recorded when they disagreed.
This difference is considerably more interesting from a momentum-trading perspective than the EPS correlation.
When fundamentals and the market’s reaction agreed, median MFE reached 9.00%.
When they disagreed, median MFE fell to just 3.30%.
That’s nearly a threefold difference. It suggests that asking “How large was the EPS beat?” may be less useful than asking:
What did the company report, and does price agree with that story?
A Bigger Initial Earnings Candle Doesn’t Guarantee More Continuation Either
There’s another important wrinkle. If the magnitude of the earnings surprise doesn’t predict MFE, perhaps the magnitude of the initial earnings candle does.
The larger dataset doesn’t strongly support that hypothesis either.
Across 112 observations with initial hourly earnings-move and MFE data:
- Pearson correlation: -0.118
- Spearman correlation: -0.110
In other words, a stock jumping 20% immediately after earnings doesn’t necessarily have more momentum remaining than one initially moving only a mere 8%.
This distinction matters.
Market reaction may matter without the raw magnitude of that reaction being predictive.
For a momentum trader, the useful information may instead come from the quality of that reaction: direction, breakout structure, volume, candle structure, fundamental alignment and whether price subsequently holds the move.
Where Does Earnings Guidance Fit Into Post-Earnings Momentum?
EPS and revenue results are fundamentally backward-looking. They tell us what happened during a quarter that has already ended.
Guidance is different.
Management guidance provides information about what the company expects to happen during upcoming quarters or the remainder of the fiscal year.
Because stock prices are ultimately based on expectations about future cash flows and business performance, guidance can potentially change the market’s valuation of a company more dramatically than an impressive backward-looking earnings result.
This study doesn’t contain enough standardized guidance data to calculate a clean correlation between guidance magnitude and MFE, so it would be inappropriate to claim that the dataset proves guidance is more important than EPS or revenue.
But several observations suggest it deserves consideration alongside the headline numbers.
A company can crush EPS estimates while lowering future revenue expectations. Another can report relatively ordinary quarterly numbers while dramatically raising its outlook.
Those two reports may create completely different market reactions.
This could also help explain why raw EPS and revenue surprise percentages perform poorly as standalone predictors of next-day momentum.
The market isn’t only asking: “What just happened?”
It’s asking: “What does this tell us about what happens next?”
Conclusion — What This Means for Post-Earnings Momentum Traders
The takeaway isn’t that EPS and revenue surprises should be ignored.
But treating surprise magnitude as a momentum score—assuming a 50% EPS beat automatically creates a better setup than a 10% beat—doesn’t appear justified by this dataset.
Instead, traders may be better served considering the complete setup: EPS and revenue direction, guidance, the initial price reaction, fundamental alignment, technical structure and risk/reward.
Most notably, setups where fundamentals and price reaction agreed produced a 9.00% median MFE, compared with just 3.30% when they disagreed.
A massive earnings surprise looks impressive, but markets trade expectations and what comes next.
The earnings surprise tells us what happened. The market’s reaction tells us what investors are actually doing with that information—and for momentum traders, that may matter more.
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
Do bigger EPS beats lead to bigger post-earnings stock moves?
Not consistently. In this dataset, the absolute magnitude of EPS surprises had a Pearson correlation of only +0.048 with next-day MFE, indicating virtually no linear relationship between the size of the EPS surprise and subsequent favorable momentum.
Is EPS or revenue more important for post-earnings momentum?
Revenue showed a stronger relationship with next-day MFE than EPS. Absolute revenue surprise had a +0.215 Pearson correlation, compared with just +0.048 for EPS. However, the revenue relationship was still weak and shouldn’t be interpreted as a reliable standalone signal.
Can earnings misses create strong momentum trades?
Yes. Momentum trading can work in either direction. EPS misses in this sample generated an 11.96% average MFE, while revenue misses averaged 13.89%, demonstrating that negative earnings reactions can create substantial bearish momentum opportunities.
Does a huge earnings beat guarantee a stock will continue higher?
No. Some of the largest EPS beats in the dataset produced relatively modest continuation, while several comparatively small beats produced very large MFEs. The 100%+ EPS-beat group produced a median MFE of only 4.43%.
Does a larger initial post-earnings move predict more next-day momentum?
Not in this dataset. Across 112 observations, the absolute size of the initial hourly earnings move had a -0.118 Pearson correlation with next-day MFE, suggesting that unusually large initial moves did not reliably lead to greater continuation.
Does earnings guidance matter for post-earnings momentum?
Potentially, but this dataset doesn’t yet contain enough standardized guidance data to isolate its effect statistically. Guidance is particularly important conceptually because it deals with future expectations, while reported EPS and revenue primarily describe the quarter that has already occurred.
What appears to matter most for post-earnings momentum?
One of the strongest findings in this analysis was alignment between fundamentals and price reaction. Setups where the two agreed produced a 9.00% median MFE, compared with 3.30% when they disagreed. This suggests that the market’s interpretation of an earnings report may be more useful than simply ranking setups by the size of their EPS or revenue surprise.
References
Laforest, J. (2026). Post-earnings momentum database. Paper Trading Journal. https://papertradingjournal.com/post-earnings-momentum-database/
National Institute of Standards and Technology. (2022). NIST/SEMATECH e-Handbook of statistical methods. U.S. Department of Commerce. https://doi.org/10.18434/M32189
National Institute of Standards and Technology. (n.d.). Rank correlation. U.S. Department of Commerce. https://www.itl.nist.gov/div898/software/dataplot/refman2/ch2/rankcorr.pdf
U.S. Securities and Exchange Commission. (n.d.). Earnings guidance. Investor.gov. https://www.investor.gov/introduction-investing/investing-basics/glossary/earnings-guidance
Zar, J. H. (2014). Spearman rank correlation: Overview. In Wiley StatsRef: Statistics Reference Online. Wiley. https://doi.org/10.1002/9781118445112.stat05964
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