Correlation Between Archer Aviation and Huntington Ingalls
Can any of the company-specific risk be diversified away by investing in both Archer Aviation and Huntington Ingalls 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 Archer Aviation and Huntington Ingalls into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Archer Aviation and Huntington Ingalls Industries, you can compare the effects of market volatilities on Archer Aviation and Huntington Ingalls 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 Archer Aviation with a short position of Huntington Ingalls. Check out your portfolio center. Please also check ongoing floating volatility patterns of Archer Aviation and Huntington Ingalls.
Diversification Opportunities for Archer Aviation and Huntington Ingalls
-0.57 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Archer and Huntington is -0.57. Overlapping area represents the amount of risk that can be diversified away by holding Archer Aviation and Huntington Ingalls Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Huntington Ingalls and Archer Aviation 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 Archer Aviation are associated (or correlated) with Huntington Ingalls. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Huntington Ingalls has no effect on the direction of Archer Aviation i.e., Archer Aviation and Huntington Ingalls go up and down completely randomly.
Pair Corralation between Archer Aviation and Huntington Ingalls
Given the investment horizon of 90 days Archer Aviation is expected to generate 1.15 times more return on investment than Huntington Ingalls. However, Archer Aviation is 1.15 times more volatile than Huntington Ingalls Industries. It trades about 0.48 of its potential returns per unit of risk. Huntington Ingalls Industries is currently generating about -0.15 per unit of risk. If you would invest 309.00 in Archer Aviation on August 25, 2024 and sell it today you would earn a total of 295.00 from holding Archer Aviation or generate 95.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Archer Aviation vs. Huntington Ingalls Industries
Performance |
Timeline |
Archer Aviation |
Huntington Ingalls |
Archer Aviation and Huntington Ingalls Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Archer Aviation and Huntington Ingalls
The main advantage of trading using opposite Archer Aviation and Huntington Ingalls positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Archer Aviation position performs unexpectedly, Huntington Ingalls 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 Huntington Ingalls will offset losses from the drop in Huntington Ingalls' long position.Archer Aviation vs. Vertical Aerospace | Archer Aviation vs. Ehang Holdings | Archer Aviation vs. Rocket Lab USA | Archer Aviation vs. Lilium NV |
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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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