Correlation Between Steel Dynamics and United Airlines
Can any of the company-specific risk be diversified away by investing in both Steel Dynamics and United Airlines 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 Steel Dynamics and United Airlines into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Steel Dynamics and United Airlines Holdings, you can compare the effects of market volatilities on Steel Dynamics and United Airlines 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 Steel Dynamics with a short position of United Airlines. Check out your portfolio center. Please also check ongoing floating volatility patterns of Steel Dynamics and United Airlines.
Diversification Opportunities for Steel Dynamics and United Airlines
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Steel and United is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Steel Dynamics and United Airlines Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on United Airlines Holdings and Steel Dynamics 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 Steel Dynamics are associated (or correlated) with United Airlines. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of United Airlines Holdings has no effect on the direction of Steel Dynamics i.e., Steel Dynamics and United Airlines go up and down completely randomly.
Pair Corralation between Steel Dynamics and United Airlines
Assuming the 90 days trading horizon Steel Dynamics is expected to generate 4.18 times less return on investment than United Airlines. But when comparing it to its historical volatility, Steel Dynamics is 34.74 times less risky than United Airlines. It trades about 0.22 of its potential returns per unit of risk. United Airlines Holdings is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 199,497 in United Airlines Holdings on October 4, 2024 and sell it today you would earn a total of 1,503 from holding United Airlines Holdings or generate 0.75% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Steel Dynamics vs. United Airlines Holdings
Performance |
Timeline |
Steel Dynamics |
United Airlines Holdings |
Steel Dynamics and United Airlines Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Steel Dynamics and United Airlines
The main advantage of trading using opposite Steel Dynamics and United Airlines positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Steel Dynamics position performs unexpectedly, United Airlines 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 United Airlines will offset losses from the drop in United Airlines' long position.Steel Dynamics vs. Promotora y Operadora | Steel Dynamics vs. Vanguard World | Steel Dynamics vs. FibroGen | Steel Dynamics vs. Grupo Hotelero Santa |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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