Correlation Between MongoDB and Snowflake

Can any of the company-specific risk be diversified away by investing in both MongoDB and Snowflake 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 MongoDB and Snowflake into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between MongoDB and Snowflake, you can compare the effects of market volatilities on MongoDB and Snowflake 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 MongoDB with a short position of Snowflake. Check out your portfolio center. Please also check ongoing floating volatility patterns of MongoDB and Snowflake.

Diversification Opportunities for MongoDB and Snowflake

0.86

Correlation Coefficient

MongoDB  Snowflake

Very poor diversification

The 3 months correlation between MongoDB and Snowflake is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding MongoDB and Snowflake in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Snowflake and MongoDB 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 MongoDB are associated (or correlated) with Snowflake. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Snowflake has no effect on the direction of MongoDB i.e., MongoDB and Snowflake go up and down completely randomly.

Pair Corralation between MongoDB and Snowflake

Considering the 90-day investment horizon MongoDB is expected to generate 1.14 times more return on investment than Snowflake. However, MongoDB is 1.14 times more volatile than Snowflake. It trades about 0.23 of its potential returns per unit of risk. Snowflake is currently generating about 0.23 per unit of risk. If you would invest  17,469  in MongoDB on April 29, 2025 and sell it today you would earn a total of  6,972  from holding MongoDB or generate 39.91% return on investment over 90 days.

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

MongoDB  vs.  Snowflake

MongoDB

Risk-Adjusted Performance

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in MongoDB are ranked lower than 17 (%) 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.

Snowflake

Risk-Adjusted Performance

Solid

Compared to the overall equity markets, risk-adjusted returns on investments in Snowflake are ranked lower than 18 (%) of all global equities and portfolios over the last 90 days. In spite of fairly unfluctuating basic indicators, Snowflake showed solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with MongoDB and Snowflake

The main advantage of trading using opposite MongoDB and Snowflake positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MongoDB position performs unexpectedly, Snowflake 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 Snowflake will offset losses from the drop in Snowflake's long position.

The idea behind MongoDB and Snowflake 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 Crypto Correlations module to use cryptocurrency correlation module to diversify your cryptocurrency portfolio across multiple coins.