Correlation Between Arbor Metals and UnitedHealth Group
Can any of the company-specific risk be diversified away by investing in both Arbor Metals and UnitedHealth Group 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 Arbor Metals and UnitedHealth Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Arbor Metals Corp and UnitedHealth Group CDR, you can compare the effects of market volatilities on Arbor Metals and UnitedHealth Group 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 Arbor Metals with a short position of UnitedHealth Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Arbor Metals and UnitedHealth Group.
Diversification Opportunities for Arbor Metals and UnitedHealth Group
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Arbor and UnitedHealth is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Arbor Metals Corp and UnitedHealth Group CDR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UnitedHealth Group CDR and Arbor Metals 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 Arbor Metals Corp are associated (or correlated) with UnitedHealth Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UnitedHealth Group CDR has no effect on the direction of Arbor Metals i.e., Arbor Metals and UnitedHealth Group go up and down completely randomly.
Pair Corralation between Arbor Metals and UnitedHealth Group
Assuming the 90 days horizon Arbor Metals Corp is expected to under-perform the UnitedHealth Group. In addition to that, Arbor Metals is 1.5 times more volatile than UnitedHealth Group CDR. It trades about -0.23 of its total potential returns per unit of risk. UnitedHealth Group CDR is currently generating about -0.09 per unit of volatility. If you would invest 2,790 in UnitedHealth Group CDR on September 29, 2024 and sell it today you would lose (359.00) from holding UnitedHealth Group CDR or give up 12.87% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Arbor Metals Corp vs. UnitedHealth Group CDR
Performance |
Timeline |
Arbor Metals Corp |
UnitedHealth Group CDR |
Arbor Metals and UnitedHealth Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Arbor Metals and UnitedHealth Group
The main advantage of trading using opposite Arbor Metals and UnitedHealth Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Arbor Metals position performs unexpectedly, UnitedHealth Group 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 UnitedHealth Group will offset losses from the drop in UnitedHealth Group's long position.Arbor Metals vs. Monarca Minerals | Arbor Metals vs. Outcrop Gold Corp | Arbor Metals vs. Grande Portage Resources | Arbor Metals vs. Klondike Silver Corp |
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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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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