Correlation Between Salesforce and MongoDB

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

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

Diversification Opportunities for Salesforce and MongoDB

-0.51

Correlation Coefficient

Salesforce  MongoDB

Excellent diversification

The 3 months correlation between Salesforce and MongoDB is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding Salesforce and MongoDB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MongoDB and Salesforce 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 Salesforce 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 Salesforce i.e., Salesforce and MongoDB go up and down completely randomly.

Pair Corralation between Salesforce and MongoDB

Considering the 90-day investment horizon Salesforce is expected to under-perform the MongoDB. But the stock apears to be less risky and, when comparing its historical volatility, Salesforce is 1.79 times less risky than MongoDB. The stock trades about -0.1 of its potential returns per unit of risk. The MongoDB is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest  17,854  in MongoDB on May 9, 2025 and sell it today you would earn a total of  5,728  from holding MongoDB or generate 32.08% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Very Weak
Accuracy	100.0%
Values	Daily Returns

Salesforce  vs.  MongoDB

Salesforce

Risk-Adjusted Performance

Weakest

Over the last 90 days Salesforce has generated negative risk-adjusted returns adding no value to investors with long positions. In spite of latest unfluctuating performance, the Stock's basic indicators remain healthy and the recent disarray on Wall Street may also be a sign of long period gains for the firm investors.

MongoDB

Risk-Adjusted Performance

Good

Compared to the overall equity markets, risk-adjusted returns on investments in MongoDB are ranked lower than 13 (%) 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 Salesforce and MongoDB

The main advantage of trading using opposite Salesforce and MongoDB positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Salesforce 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 Salesforce 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 Piotroski F Score module to get Piotroski F Score based on the binary analysis strategy of nine different fundamentals.