Correlation Between Lockheed Martin and Intuitive Machines
Can any of the company-specific risk be diversified away by investing in both Lockheed Martin and Intuitive Machines 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 Lockheed Martin and Intuitive Machines into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lockheed Martin and Intuitive Machines, you can compare the effects of market volatilities on Lockheed Martin and Intuitive Machines 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 Lockheed Martin with a short position of Intuitive Machines. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lockheed Martin and Intuitive Machines.
Diversification Opportunities for Lockheed Martin and Intuitive Machines
-0.29 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Lockheed and Intuitive is -0.29. Overlapping area represents the amount of risk that can be diversified away by holding Lockheed Martin and Intuitive Machines in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Intuitive Machines and Lockheed Martin 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 Lockheed Martin are associated (or correlated) with Intuitive Machines. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Intuitive Machines has no effect on the direction of Lockheed Martin i.e., Lockheed Martin and Intuitive Machines go up and down completely randomly.
Pair Corralation between Lockheed Martin and Intuitive Machines
Considering the 90-day investment horizon Lockheed Martin is expected to generate 0.09 times more return on investment than Intuitive Machines. However, Lockheed Martin is 11.05 times less risky than Intuitive Machines. It trades about -0.06 of its potential returns per unit of risk. Intuitive Machines is currently generating about -0.15 per unit of risk. If you would invest 47,983 in Lockheed Martin on December 30, 2024 and sell it today you would lose (3,834) from holding Lockheed Martin or give up 7.99% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 74.19% |
Values | Daily Returns |
Lockheed Martin vs. Intuitive Machines
Performance |
Timeline |
Lockheed Martin |
Intuitive Machines |
Risk-Adjusted Performance
Very Weak
Weak | Strong |
Lockheed Martin and Intuitive Machines Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lockheed Martin and Intuitive Machines
The main advantage of trading using opposite Lockheed Martin and Intuitive Machines positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lockheed Martin position performs unexpectedly, Intuitive Machines 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 Intuitive Machines will offset losses from the drop in Intuitive Machines' long position.Lockheed Martin vs. Northrop Grumman | Lockheed Martin vs. General Dynamics | Lockheed Martin vs. L3Harris Technologies | Lockheed Martin vs. The Boeing |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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