Correlation Between Mercury Systems and Curtiss Wright
Can any of the company-specific risk be diversified away by investing in both Mercury Systems and Curtiss Wright 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 Curtiss Wright into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mercury Systems and Curtiss Wright, you can compare the effects of market volatilities on Mercury Systems and Curtiss Wright 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 Curtiss Wright. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mercury Systems and Curtiss Wright.
Diversification Opportunities for Mercury Systems and Curtiss Wright
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Mercury and Curtiss is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Mercury Systems and Curtiss Wright in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Curtiss Wright 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 Curtiss Wright. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Curtiss Wright has no effect on the direction of Mercury Systems i.e., Mercury Systems and Curtiss Wright go up and down completely randomly.
Pair Corralation between Mercury Systems and Curtiss Wright
Given the investment horizon of 90 days Mercury Systems is expected to generate 2.2 times more return on investment than Curtiss Wright. However, Mercury Systems is 2.2 times more volatile than Curtiss Wright. It trades about 0.09 of its potential returns per unit of risk. Curtiss Wright is currently generating about 0.18 per unit of risk. If you would invest 3,620 in Mercury Systems on August 26, 2024 and sell it today you would earn a total of 474.00 from holding Mercury Systems or generate 13.09% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Mercury Systems vs. Curtiss Wright
Performance |
| Timeline |
| Mercury Systems |
| Curtiss Wright |
Mercury Systems and Curtiss Wright Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Mercury Systems and Curtiss Wright
The main advantage of trading using opposite Mercury Systems and Curtiss Wright positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mercury Systems position performs unexpectedly, Curtiss Wright 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 Curtiss Wright will offset losses from the drop in Curtiss Wright's long position.| Mercury Systems vs. Curtiss Wright | Mercury Systems vs. Hexcel | Mercury Systems vs. Ducommun Incorporated | Mercury Systems vs. Woodward |
| Curtiss Wright vs. Mercury Systems | Curtiss Wright vs. AAR Corp | Curtiss Wright vs. Ducommun Incorporated | Curtiss Wright vs. Moog Inc |
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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