Correlation Between Datadog and MongoDB

Can any of the company-specific risk be diversified away by investing in both Datadog and MongoDB at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Datadog and MongoDB into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between Datadog and MongoDB, you can compare the effects of market volatilities on Datadog and MongoDB and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Datadog with a short position of MongoDB. Check out your portfolio center. Please also check ongoing floating volatility patterns of Datadog and MongoDB.

Diversification Opportunities for Datadog and MongoDB

0.75

Correlation Coefficient

Datadog  MongoDB

Poor diversification

The 3 months correlation between Datadog and MongoDB is 0.75. Overlapping area represents the amount of risk that can be diversified away by holding Datadog and MongoDB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MongoDB and Datadog is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Datadog are associated (or correlated) with MongoDB. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MongoDB has no effect on the direction of Datadog i.e., Datadog and MongoDB go up and down completely randomly.

Pair Corralation between Datadog and MongoDB

Given the investment horizon of 90 days Datadog is expected to generate 1.54 times less return on investment than MongoDB. But when comparing it to its historical volatility, Datadog is 1.09 times less risky than MongoDB. It trades about 0.06 of its potential returns per unit of risk. MongoDB is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest  18,901  in MongoDB on May 19, 2025 and sell it today you would earn a total of  2,925  from holding MongoDB or generate 15.48% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	100.0%
Values	Daily Returns

Datadog  vs.  MongoDB

Datadog

Risk-Adjusted Performance

Mild

Compared to the overall equity markets, risk-adjusted returns on investments in Datadog are ranked lower than 5 (%) of all global equities and portfolios over the last 90 days. Despite nearly weak basic indicators, Datadog may actually be approaching a critical reversion point that can send shares even higher in September 2025.

MongoDB

Risk-Adjusted Performance

Fair

Compared to the overall equity markets, risk-adjusted returns on investments in MongoDB are ranked lower than 7 (%) of all global equities and portfolios over the last 90 days. Despite somewhat uncertain fundamental indicators, MongoDB sustained solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with Datadog and MongoDB

The main advantage of trading using opposite Datadog and MongoDB positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Datadog position performs unexpectedly, MongoDB can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in MongoDB will offset losses from the drop in MongoDB's long position.

The idea behind Datadog and MongoDB pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Pair Correlation module to compare performance and examine fundamental relationship between any two equity instruments.