Correlation Between MongoDB and Bakkt Holdings
Can any of the company-specific risk be diversified away by investing in both MongoDB and Bakkt Holdings 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 Bakkt Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MongoDB and Bakkt Holdings, you can compare the effects of market volatilities on MongoDB and Bakkt Holdings 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 Bakkt Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of MongoDB and Bakkt Holdings.
Diversification Opportunities for MongoDB and Bakkt Holdings
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between MongoDB and Bakkt is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding MongoDB and Bakkt Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bakkt Holdings 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 Bakkt Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bakkt Holdings has no effect on the direction of MongoDB i.e., MongoDB and Bakkt Holdings go up and down completely randomly.
Pair Corralation between MongoDB and Bakkt Holdings
Considering the 90-day investment horizon MongoDB is expected to generate 9.44 times less return on investment than Bakkt Holdings. But when comparing it to its historical volatility, MongoDB is 9.95 times less risky than Bakkt Holdings. It trades about 0.25 of its potential returns per unit of risk. Bakkt Holdings is currently generating about 0.24 of returns per unit of risk over similar time horizon. If you would invest 953.00 in Bakkt Holdings on September 1, 2024 and sell it today you would earn a total of 1,832 from holding Bakkt Holdings or generate 192.24% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
MongoDB vs. Bakkt Holdings
Performance |
| Timeline |
| MongoDB |
| Bakkt Holdings |
MongoDB and Bakkt Holdings Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with MongoDB and Bakkt Holdings
The main advantage of trading using opposite MongoDB and Bakkt Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MongoDB position performs unexpectedly, Bakkt Holdings 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 Bakkt Holdings will offset losses from the drop in Bakkt Holdings' long position.| MongoDB vs. Crowdstrike Holdings | MongoDB vs. Okta Inc | MongoDB vs. Cloudflare | MongoDB vs. Palo Alto Networks |
| Bakkt Holdings vs. Arqit Quantum | Bakkt Holdings vs. Alarum Technologies | Bakkt Holdings vs. GigaCloud Technology Class | Bakkt Holdings vs. Pagaya Technologies |
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 Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
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