Correlation Between Regions Financial and MongoDB

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

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

Diversification Opportunities for Regions Financial and MongoDB

0.8

Correlation Coefficient

Regions Financial  MongoDB

Very poor diversification

The 3 months correlation between Regions and MongoDB is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Regions Financial and MongoDB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MongoDB and Regions Financial 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 Regions Financial 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 Regions Financial i.e., Regions Financial and MongoDB go up and down completely randomly.

Pair Corralation between Regions Financial and MongoDB

Assuming the 90 days horizon Regions Financial is expected to generate 1.77 times less return on investment than MongoDB. But when comparing it to its historical volatility, Regions Financial is 1.81 times less risky than MongoDB. It trades about 0.03 of its potential returns per unit of risk. MongoDB is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest  18,246  in MongoDB on October 4, 2024 and sell it today you would earn a total of  4,259  from holding MongoDB or generate 23.34% return on investment over 90 days.

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

Regions Financial  vs.  MongoDB

Regions Financial

Risk-Adjusted Performance

8 of 100

OK

Compared to the overall equity markets, risk-adjusted returns on investments in Regions Financial are ranked lower than 8 (%) of all global equities and portfolios over the last 90 days. Despite nearly fragile basic indicators, Regions Financial reported solid returns over the last few months and may actually be approaching a breakup point.

MongoDB

Risk-Adjusted Performance

0 of 100

Very Weak

Over the last 90 days MongoDB has generated negative risk-adjusted returns adding no value to investors with long positions. Despite nearly stable basic indicators, MongoDB is not utilizing all of its potentials. The current stock price disturbance, may contribute to mid-run losses for the stockholders.

Pair Trading with Regions Financial and MongoDB

The main advantage of trading using opposite Regions Financial and MongoDB positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Regions Financial 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 Regions Financial 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.

Check out your portfolio center.

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 Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.