How Will Shopify Stock React To Its Upcoming Earnings?
Shopify (NASDAQ:SHOP) is set to report its earnings on Tuesday, May 5, 2026. The company has $166 Bil in current market capitalization. Revenue over the last twelve months was $12 Bil, and it was operationally profitable with $1.9 Bil in operating profits and net income of $1.2 Bil. While a lot will depend on how results stack up against consensus and expectations, understanding historical patterns might just turn the odds in your favor if you are an event-driven trader.
There are two ways to do that: understand the historical odds and position yourself prior to the earnings release, or look at the correlation between immediate and medium-term returns post earnings and position yourself accordingly after the earnings are released.
See earnings reaction history of all stocks
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Shopify’s Historical Odds Of Positive Post-Earnings Return
Some observations on one-day (1D) post-earnings returns:
- There are 5 earnings data points recorded over the last five years, with 2 positive and 3 negative one-day (1D) returns observed. In summary, positive 1D returns were seen about 40% of the time.
- The percentage remains the same at 40% if we consider data for the last 3 years instead of 5.
- Median of the 2 positive returns = 13%, and median of the 3 negative returns = -6.7%
Additional data for observed 5-Day (5D) and 21-Day (21D) returns post earnings are summarized along with the statistics in the table below.
| Forward Returns | |||
|---|---|---|---|
| Earnings Date | 1D | 5D | 21D |
| 2/11/2026 | -6.7% | -4.4% | -0.8% |
| 11/4/2025 | -6.9% | -8.1% | -6.1% |
| 8/6/2025 | 22.0% | 17.6% | 14.3% |
| 5/8/2025 | -0.5% | 17.9% | 17.9% |
| 2/11/2025 | 3.1% | 7.8% | -19.5% |
| SUMMARY STATS | |||
| # Positive | 2 | 3 | 2 |
| # Negative | 3 | 2 | 3 |
| Median Positive | 12.5% | 17.6% | 16.1% |
| Median Negative | -6.7% | -6.3% | -6.1% |
| Max Positive | 22.0% | 17.9% | 17.9% |
| Max Negative | -6.9% | -8.1% | -19.5% |
Correlation Between 1D, 5D and 21D Historical Returns
A relatively less risky strategy (though not useful if the correlation is low) is to understand the correlation between short-term and medium-term returns post earnings, find a pair that has the highest correlation, and execute the appropriate trade. For example, if 1D and 5D show the highest correlation, a trader can position themselves “long” for the next 5 days if the 1D post-earnings return is positive. Here is some correlation data based on a 5-year and a 3-year (more recent) history. Note that the correlation 1D_5D refers to the correlation between 1D post-earnings returns and subsequent 5D returns.
| History | 1D_5D | 1D_21D | 5D_21D |
|---|---|---|---|
| 5Y History | -34.9% | -27.6% | -40.6% |
| 3Y History | -34.9% | -27.6% | -40.6% |
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