Correlation Between Air Transport and Gossan Resources
Can any of the company-specific risk be diversified away by investing in both Air Transport and Gossan Resources 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 Air Transport and Gossan Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Air Transport Services and Gossan Resources, you can compare the effects of market volatilities on Air Transport and Gossan Resources 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 Air Transport with a short position of Gossan Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Air Transport and Gossan Resources.
Diversification Opportunities for Air Transport and Gossan Resources
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Air and Gossan is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Air Transport Services and Gossan Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gossan Resources and Air Transport 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 Air Transport Services are associated (or correlated) with Gossan Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gossan Resources has no effect on the direction of Air Transport i.e., Air Transport and Gossan Resources go up and down completely randomly.
Pair Corralation between Air Transport and Gossan Resources
Assuming the 90 days horizon Air Transport is expected to generate 33.66 times less return on investment than Gossan Resources. But when comparing it to its historical volatility, Air Transport Services is 22.58 times less risky than Gossan Resources. It trades about 0.06 of its potential returns per unit of risk. Gossan Resources is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 1.05 in Gossan Resources on September 14, 2024 and sell it today you would earn a total of 0.05 from holding Gossan Resources or generate 4.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Air Transport Services vs. Gossan Resources
Performance |
Timeline |
Air Transport Services |
Gossan Resources |
Air Transport and Gossan Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Air Transport and Gossan Resources
The main advantage of trading using opposite Air Transport and Gossan Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Air Transport position performs unexpectedly, Gossan Resources 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 Gossan Resources will offset losses from the drop in Gossan Resources' long position.Air Transport vs. Aena SME SA | Air Transport vs. Superior Plus Corp | Air Transport vs. SIVERS SEMICONDUCTORS AB | Air Transport vs. Norsk Hydro ASA |
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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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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