In this guide, you’ll learn what post-earnings momentum trading is, why stocks can continue moving after earnings, and how traders identify potential setups using fundamental and technical analysis. We’ll also examine key findings from our 150-setup database, academic research on post-earnings announcement drift (PEAD), and real-world case studies showing both successful long and short momentum trades.
Whether you’re new to the stock market or an experience trader or investor, earnings announcements can create some of the largest short-term price movements in the stock market.
When a company reports earnings, traders aren’t simply reacting to whether EPS beat estimates—they’re simultaneously digesting revenue, guidance, margins, growth rates, management commentary, and what all of that information means for the company’s valuation.
The result can be explosive volatility.
And importantly for momentum traders, the initial earnings reaction doesn’t always end when the first candle closes.
In my growing database of 150 post-earnings momentum setups, stocks produced an average maximum favorable excursion (MFE) of approximately 11.0% after the initial hourly earnings candle closed.
Some individual setups went substantially further, including 43.2% for ACH, 39.1% for APPS, 34.2% for DOMO, and 26.4% for WIX. These are the types of moves post-earnings momentum trading attempts to capture.
Quick Answer: What Is Post-Earnings Momentum Trading?
Post-earnings momentum trading is a high-risk, high-reward strategy that attempts to profit from continued price movement after a stock reports earnings. Similar to post-earnings announcement drift (PEAD), it is based on the idea that an earnings reaction may continue after the initial move. Traders combine fundamental analysis of earnings and guidance with technical analysis of price action and breakouts to identify opportunities, but disciplined risk management is essential because even seemingly A+ setups can quickly fail or reverse.
Biggest Post-Earnings Momentum Winners & Losers
| Stock | Setup | 1-Hour Move | Next-Day EOD | Momentum Outcome |
|---|---|---|---|---|
| ACH | Short | -19.76% | -36.13% | +36.13% |
| DOMO | Short | -0.05% | -32.97% | +32.97% |
| APPS | Long | +12.68% | +21.94% | +21.94% |
| RNG | Long | +2.96% | +21.75% | +21.75% |
| WIX | Short | -8.35% | -20.00% | +20.00% |
| MDB | Long | +22.07% | -16.68% | -16.68% |
| EGHT | Long | +13.16% | -17.50% | -17.50% |
| CNXC | Short | -24.94% | +19.64% | -19.64% |
| DOCS | Long | +68.37% | -21.45% | -21.45% |
Source: The Paper Trading Journal Post-Earnings Momentum Database. Momentum outcome measures the next-day closing move from the initial hourly candle close, adjusted for the direction of the setup.
Want to dig into the numbers yourself? Explore our full Post-Earnings Momentum Database to see every setup, including first-hour moves, MFE, MAE, next-day performance, earnings results, guidance, technical breakouts, and more.
Key Post-Earnings Momentum Trading Statistics
- 150 setups analyzed in our post-earnings momentum dataset.
- 11.0% average MFE across 144 setups with complete next-day data.
- 43.2% largest MFE recorded in the dataset, produced by ACH.
- 41% of setups reached a +9% profit target before a -5% stop.
- 13.56% average MFE for stocks with initial earnings moves below 5%.
- 9.34% average MAE for stocks that moved 20%+ initially, versus just 1.61% for sub-5% moves.
- 6%+ excess return over 60 days was found in one Canadian academic study of post-earnings announcement drift.
- 70–100% of theoretical PEAD profits could be consumed by transaction costs in illiquid stocks, according to one academic study.
5 Examples of Post-Earnings Momentum Trades
The easiest way to understand post-earnings momentum trading is to look at actual setups.
These five case studies from our dataset demonstrate that the strategy can work in both directions—and that the relationship between fundamentals and price isn’t always straightforward.
TWLO: Bullish Fundamentals + Bullish Momentum
Twilio (TWLO) produced a classic bullish post-earnings momentum setup.
The stock’s first hourly earnings candle gained 16.67% after the company reported an approximately 66.7% EPS beat and 5.6% revenue beat, accompanied by bullish EPS and revenue guidance.
Fundamentals and price action therefore pointed in the same direction.
Instead of exhausting the move, TWLO subsequently reached another 12.9% MFE from the hourly close while experiencing only approximately 1% MAE. It finished the following session another 7.23% higher.
ETON: A 20.7% Earnings Move Wasn’t the End
ETON Pharmaceuticals (ETON) provides an even more dramatic example.
Its initial hourly earnings reaction gained 20.7%, supported by strong reported results and revenue guidance that was approximately 20% above expectations.
Despite already moving more than 20%, ETON subsequently reached another 22.05% MFE while experiencing only 2.04% MAE.
By the following close, the stock was another 19.47% higher than the hourly entry point.
BLMN: Technical Confirmation and Continued Strength
Bloomin’ Brands (BLMN) gained 11.78% during its initial earnings reaction, accompanied by an EPS beat, revenue beat and bullish full-year guidance.
Unlike TWLO and ETON, BLMN also produced both hourly and 4-hour technical breakouts.
The stock subsequently reached a 24.97% MFE, experienced just 0.5% MAE, and finished the following session approximately 17.47% above the hourly earnings candle close.
It’s an excellent example of fundamental and technical confirmation appearing simultaneously.
RDDT: When Price and Fundamentals Disagree
Reddit (RDDT) demonstrates why traders shouldn’t assume good earnings automatically mean a stock should go higher. It’s also a good example because it demonstrates that post-earnings momentum trades don’t only work on the long side.
RDDT reported an approximately 26.3% EPS beat, 8.0% revenue beat and strong bullish guidance.
Yet the market sold the stock.
Its initial hourly earnings candle fell 8.05%, creating a bearish momentum setup despite fundamentally positive results.
The bearish move subsequently reached a 17.55% MFE and closed the following session another 14.23% lower.
It’s a useful reminder that traders aren’t trading the earnings report itself—they’re trading the market’s reaction to the earnings report.
RBLX: A Powerful Bearish Continuation
Roblox (RBLX) provides another example from the short side. Its first-hour earnings candle fell 11.67%, producing an hourly breakdown despite a more mixed fundamental picture.
But even after a nearly 12% move, the bearish momentum didn’t stop.
RBLX subsequently reached a 21.4% MFE without registering any meaningful adverse excursion and finished the following session another 17.51% lower than the initial hourly candle close.
For a momentum trader, the direction of the opportunity doesn’t matter nearly as much as identifying whether price has begun establishing a persistent directional move.
Conclusion – How To Trade Post-Earnings Momentum
Post-earnings momentum trading attempts to capitalize on a simple observation: the first reaction to an earnings announcement isn’t always the last one.
Decades of academic research into post-earnings-announcement drift suggest that markets don’t always immediately incorporate earnings information into stock prices.
My own trading strategy is based on that exact concept, except we attempt to exploit the phenomenon on a much shorter timescale.
Across more than 150 setups, stocks have reached an average 11.0% MFE after the initial hourly earnings candle closed, with individual setups producing continuation moves exceeding 20%, 30% and occasionally 40%.
But those potential rewards come with substantial risk.
Post-earnings stocks are volatile. Breakouts fail. Strong earnings can sell off. Weak earnings can reverse higher. Slippage can turn a manageable loss into a larger one, and even seemingly perfect technical and fundamental setups can completely reverse.
That’s why identifying the setup is only half of the strategy. The other half is managing the trade when you’re wrong.
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
What is post-earnings momentum?
Post-earnings momentum is the tendency for a stock to continue moving after its initial reaction to an earnings announcement. Momentum can be bullish following a positive reaction or bearish following a negative reaction.
What is post-earnings-announcement drift?
Post-earnings-announcement drift, or PEAD, is a well-documented market phenomenon in which stock prices continue moving in the direction associated with an earnings surprise after the announcement. Academic studies have documented the effect across multiple markets and time periods.
Is post-earnings momentum trading the same as PEAD?
Not exactly. Traditional PEAD research generally examines returns over weeks or months following earnings announcements. Our post-earnings momentum strategy focuses primarily on much shorter-term continuation immediately following the initial earnings reaction.
Can you trade both bullish and bearish earnings momentum?
Yes. Traders can potentially go long when a bullish earnings reaction shows signs of continuing or short when a bearish reaction continues lower. Our dataset contains successful examples in both directions.
Do good earnings always cause a stock to go up?
No. Earnings reactions depend on expectations rather than simply whether a company reports “good” numbers. A company can beat EPS and revenue expectations and still fall if guidance disappoints, expectations were higher, or investors focus on another part of the report.
RDDT is a good example from our dataset: despite beating EPS and revenue estimates and providing bullish guidance, the initial reaction was bearish and the stock continued another 14.23% lower by the following close.
How risky is post-earnings momentum trading?
Very. Earnings announcements can create unusually high volatility, overnight gaps, wide spreads and sudden reversals. Even setups with strong fundamentals and technical confirmation can fail, making strict position sizing and predefined risk management especially important.
What should traders look for after an earnings announcement?
Potential factors include the initial price reaction, EPS and revenue surprises, forward guidance, trading volume, hourly and higher-timeframe breakouts, candle structure, support and resistance levels, liquidity, short interest and whether the fundamental story agrees with the market’s reaction.
No individual variable guarantees continuation, which is why post-earnings momentum trading generally works best as a combination of fundamental analysis, technical analysis and disciplined risk management.
References
Bernard, V. L., & Thomas, J. K. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27, 1–36.
Chordia, T., Goyal, A., Sadka, G., Sadka, R., & Shivakumar, L. (2009). Liquidity and the post-earnings-announcement drift. Financial Analysts Journal, 65(4), 18–32.
Dou, P., Truong, C., & Veeraraghavan, M. (2016). Individualism, uncertainty avoidance, and earnings momentum in international markets. Contemporary Accounting Research, 33(2), 851–881.
Foster, G., Olsen, C., & Shevlin, T. (1984). Earnings releases, anomalies, and the behavior of security returns. The Accounting Review, 59(4), 574–603.
Kothari, S. P. (2001). Capital markets research in accounting. Journal of Accounting and Economics, 31(1–3), 105–231.
Mendenhall, R. R. (2004). Arbitrage risk and post-earnings-announcement drift. Journal of Business, 77(4), 875–894.
Ng, J., Rusticus, T. O., & Verdi, R. S. (2008). Implications of transaction costs for the post-earnings announcement drift. Journal of Accounting Research, 46(3), 661–696.
Sadka, R. (2006). Momentum and post-earnings-announcement drift anomalies: The role of liquidity risk. Journal of Financial Economics, 80(2), 309–349.
The Paper Trading Journal. (2026). Stock chart setup case studies. https://papertradingjournal.com/stock-chart-setup-case-studies/
The Paper Trading Journal. (2026). Post-earnings momentum database [Data set]. https://papertradingjournal.com/post-earnings-momentum-database/
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