Correlation Between Federal Home and MongoDB

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

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

Diversification Opportunities for Federal Home and MongoDB

0.4

Correlation Coefficient

Federal Home  MongoDB

Very weak diversification

The 3 months correlation between Federal and MongoDB is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Federal Home Loan and MongoDB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MongoDB and Federal Home 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 Federal Home Loan 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 Federal Home i.e., Federal Home and MongoDB go up and down completely randomly.

Pair Corralation between Federal Home and MongoDB

Assuming the 90 days horizon Federal Home Loan is expected to generate 2.15 times more return on investment than MongoDB. However, Federal Home is 2.15 times more volatile than MongoDB. It trades about 0.18 of its potential returns per unit of risk. MongoDB is currently generating about -0.07 per unit of risk. If you would invest  236.00  in Federal Home Loan on December 30, 2024 and sell it today you would earn a total of  294.00  from holding Federal Home Loan or generate 124.58% return on investment over 90 days.

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

Federal Home Loan  vs.  MongoDB

Federal Home Loan

Risk-Adjusted Performance

Good

Compared to the overall equity markets, risk-adjusted returns on investments in Federal Home Loan are ranked lower than 14 (%) of all global equities and portfolios over the last 90 days. Despite nearly fragile basic indicators, Federal Home reported solid returns over the last few months and may actually be approaching a breakup point.

MongoDB

Risk-Adjusted Performance

Very Weak

Over the last 90 days MongoDB has generated negative risk-adjusted returns adding no value to investors with long positions. Despite fragile performance in the last few months, the Stock's basic indicators remain nearly stable which may send shares a bit higher in April 2025. The current disturbance may also be a sign of long-run up-swing for the company stockholders.

Pair Trading with Federal Home and MongoDB

The main advantage of trading using opposite Federal Home and MongoDB positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Federal Home 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 Federal Home Loan 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.