Correlation Between Mercury Systems and General Dynamics
Can any of the company-specific risk be diversified away by investing in both Mercury Systems and General Dynamics 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 Mercury Systems and General Dynamics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mercury Systems and General Dynamics, you can compare the effects of market volatilities on Mercury Systems and General Dynamics 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 Mercury Systems with a short position of General Dynamics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mercury Systems and General Dynamics.
Diversification Opportunities for Mercury Systems and General Dynamics
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between Mercury and General is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding Mercury Systems and General Dynamics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on General Dynamics and Mercury Systems 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 Mercury Systems are associated (or correlated) with General Dynamics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of General Dynamics has no effect on the direction of Mercury Systems i.e., Mercury Systems and General Dynamics go up and down completely randomly.
Pair Corralation between Mercury Systems and General Dynamics
Given the investment horizon of 90 days Mercury Systems is expected to generate 2.45 times more return on investment than General Dynamics. However, Mercury Systems is 2.45 times more volatile than General Dynamics. It trades about 0.06 of its potential returns per unit of risk. General Dynamics is currently generating about -0.03 per unit of risk. If you would invest 3,719 in Mercury Systems on September 2, 2024 and sell it today you would earn a total of 394.00 from holding Mercury Systems or generate 10.59% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Mercury Systems vs. General Dynamics
Performance |
Timeline |
Mercury Systems |
General Dynamics |
Mercury Systems and General Dynamics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mercury Systems and General Dynamics
The main advantage of trading using opposite Mercury Systems and General Dynamics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mercury Systems position performs unexpectedly, General Dynamics 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 General Dynamics will offset losses from the drop in General Dynamics' long position.Mercury Systems vs. Archer Aviation | Mercury Systems vs. Rocket Lab USA | Mercury Systems vs. Lilium NV | Mercury Systems vs. HEICO |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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