Correlation Between Mirova Global and Guggenheim Managed
Can any of the company-specific risk be diversified away by investing in both Mirova Global and Guggenheim Managed 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 Mirova Global and Guggenheim Managed into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mirova Global Green and Guggenheim Managed Futures, you can compare the effects of market volatilities on Mirova Global and Guggenheim Managed 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 Mirova Global with a short position of Guggenheim Managed. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mirova Global and Guggenheim Managed.
Diversification Opportunities for Mirova Global and Guggenheim Managed
-0.03 | Correlation Coefficient |
Good diversification
The 3 months correlation between Mirova and Guggenheim is -0.03. Overlapping area represents the amount of risk that can be diversified away by holding Mirova Global Green and Guggenheim Managed Futures in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guggenheim Managed and Mirova Global 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 Mirova Global Green are associated (or correlated) with Guggenheim Managed. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guggenheim Managed has no effect on the direction of Mirova Global i.e., Mirova Global and Guggenheim Managed go up and down completely randomly.
Pair Corralation between Mirova Global and Guggenheim Managed
Assuming the 90 days horizon Mirova Global Green is expected to generate 0.42 times more return on investment than Guggenheim Managed. However, Mirova Global Green is 2.41 times less risky than Guggenheim Managed. It trades about 0.05 of its potential returns per unit of risk. Guggenheim Managed Futures is currently generating about 0.01 per unit of risk. If you would invest 789.00 in Mirova Global Green on November 2, 2024 and sell it today you would earn a total of 68.00 from holding Mirova Global Green or generate 8.62% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 99.8% |
| Values | Daily Returns |
Mirova Global Green vs. Guggenheim Managed Futures
Performance |
| Timeline |
| Mirova Global Green |
| Guggenheim Managed |
Mirova Global and Guggenheim Managed Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Mirova Global and Guggenheim Managed
The main advantage of trading using opposite Mirova Global and Guggenheim Managed positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mirova Global position performs unexpectedly, Guggenheim Managed 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 Guggenheim Managed will offset losses from the drop in Guggenheim Managed's long position.| Mirova Global vs. T Rowe Price | Mirova Global vs. Enhanced Fixed Income | Mirova Global vs. Us Vector Equity | Mirova Global vs. The Growth Equity |
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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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