How Will MongoDB Stock React To Its Upcoming Earnings

MongoDB (NASDAQ:MDB) is set to report its earnings on Tuesday, September 1, 2026. The company has $36 billion in current market capitalization. Revenue over the last twelve months was $2.6 billion, and it was operationally loss-making with an operating loss of $108 million and a net loss of $29 million. 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.

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MongoDB's Historical Odds Of Positive Post-Earnings Return

Some observations on one-day (1D) post-earnings returns:

• There are 20 earnings data points recorded over the last five years, with 12 positive and 8 negative one-day (1D) returns observed. In summary, positive 1D returns were seen about 60% of the time.
• However, this percentage decreases to 50% if we consider data for the last 3 years instead of 5.
• Median of the 12 positive returns = 18%, and median of the 8 negative returns = -20%

Additional data for observed 5-Day (5D) and 21-Day (21D) returns post earnings are summarized along with the statistics in the table below.

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, 1D_21D shows the strongest correlation here: if the 1D post-earnings return is positive, a trader can position themselves in the same direction over the following 21D window. Here is some correlation data based on a 5-year and a 3-year (more recent) history. Note that these correlations are between subsequent windows, not the cumulative columns above: 1D_5D is the correlation between the 1D post-earnings return and the subsequent return from day 1 through day 5, 1D_21D is between the 1D return and the subsequent return from day 1 through day 21, and 5D_21D is between the 5D return and the subsequent return from day 5 through day 21.

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