Correlation Between Lockheed Martin and Goldman Sachs
Can any of the company-specific risk be diversified away by investing in both Lockheed Martin and Goldman Sachs 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 Goldman Sachs into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lockheed Martin and The Goldman Sachs, you can compare the effects of market volatilities on Lockheed Martin and Goldman Sachs 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 Goldman Sachs. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lockheed Martin and Goldman Sachs.
Diversification Opportunities for Lockheed Martin and Goldman Sachs
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Lockheed and Goldman is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Lockheed Martin and The Goldman Sachs in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Goldman Sachs 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 Goldman Sachs. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Goldman Sachs has no effect on the direction of Lockheed Martin i.e., Lockheed Martin and Goldman Sachs go up and down completely randomly.
Pair Corralation between Lockheed Martin and Goldman Sachs
Assuming the 90 days trading horizon Lockheed Martin is expected to generate 2.27 times less return on investment than Goldman Sachs. But when comparing it to its historical volatility, Lockheed Martin is 1.25 times less risky than Goldman Sachs. It trades about 0.09 of its potential returns per unit of risk. The Goldman Sachs is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 565,603 in The Goldman Sachs on September 14, 2024 and sell it today you would earn a total of 623,293 from holding The Goldman Sachs or generate 110.2% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Lockheed Martin vs. The Goldman Sachs
Performance |
Timeline |
Lockheed Martin |
Goldman Sachs |
Lockheed Martin and Goldman Sachs Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lockheed Martin and Goldman Sachs
The main advantage of trading using opposite Lockheed Martin and Goldman Sachs positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lockheed Martin position performs unexpectedly, Goldman Sachs 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 Goldman Sachs will offset losses from the drop in Goldman Sachs' long position.Lockheed Martin vs. The Boeing | Lockheed Martin vs. General Dynamics | Lockheed Martin vs. Textron | Lockheed Martin vs. Netflix |
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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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