Correlation Between Amg Managers and Ubs Ultra
Can any of the company-specific risk be diversified away by investing in both Amg Managers and Ubs Ultra 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 Amg Managers and Ubs Ultra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Amg Managers Centersquare and Ubs Ultra Short, you can compare the effects of market volatilities on Amg Managers and Ubs Ultra 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 Amg Managers with a short position of Ubs Ultra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amg Managers and Ubs Ultra.
Diversification Opportunities for Amg Managers and Ubs Ultra
-0.12 | Correlation Coefficient |
Good diversification
The 3 months correlation between Amg and Ubs is -0.12. Overlapping area represents the amount of risk that can be diversified away by holding Amg Managers Centersquare and Ubs Ultra Short in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ubs Ultra Short and Amg Managers 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 Amg Managers Centersquare are associated (or correlated) with Ubs Ultra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ubs Ultra Short has no effect on the direction of Amg Managers i.e., Amg Managers and Ubs Ultra go up and down completely randomly.
Pair Corralation between Amg Managers and Ubs Ultra
Assuming the 90 days horizon Amg Managers Centersquare is expected to generate 12.15 times more return on investment than Ubs Ultra. However, Amg Managers is 12.15 times more volatile than Ubs Ultra Short. It trades about 0.04 of its potential returns per unit of risk. Ubs Ultra Short is currently generating about 0.22 per unit of risk. If you would invest 990.00 in Amg Managers Centersquare on September 2, 2024 and sell it today you would earn a total of 250.00 from holding Amg Managers Centersquare or generate 25.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Amg Managers Centersquare vs. Ubs Ultra Short
Performance |
| Timeline |
| Amg Managers Centersquare |
| Ubs Ultra Short |
Amg Managers and Ubs Ultra Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Amg Managers and Ubs Ultra
The main advantage of trading using opposite Amg Managers and Ubs Ultra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amg Managers position performs unexpectedly, Ubs Ultra 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 Ubs Ultra will offset losses from the drop in Ubs Ultra's long position.| Amg Managers vs. Fidelity Series 1000 | Amg Managers vs. Qs Large Cap | Amg Managers vs. John Hancock Investment | Amg Managers vs. Large Cap Growth Profund |
| Ubs Ultra vs. Pace Smallmedium Value | Ubs Ultra vs. Pace International Equity | Ubs Ultra vs. Pace International Equity | Ubs Ultra vs. Ubs Allocation Fund |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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