Correlation Between Asg Managed and Loomis Sayles
Can any of the company-specific risk be diversified away by investing in both Asg Managed and Loomis Sayles 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 Asg Managed and Loomis Sayles into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Asg Managed Futures and Loomis Sayles Limited, you can compare the effects of market volatilities on Asg Managed and Loomis Sayles 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 Asg Managed with a short position of Loomis Sayles. Check out your portfolio center. Please also check ongoing floating volatility patterns of Asg Managed and Loomis Sayles.
Diversification Opportunities for Asg Managed and Loomis Sayles
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Asg and Loomis is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Asg Managed Futures and Loomis Sayles Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Loomis Sayles Limited and Asg Managed 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 Asg Managed Futures are associated (or correlated) with Loomis Sayles. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Loomis Sayles Limited has no effect on the direction of Asg Managed i.e., Asg Managed and Loomis Sayles go up and down completely randomly.
Pair Corralation between Asg Managed and Loomis Sayles
Assuming the 90 days horizon Asg Managed Futures is expected to generate 6.29 times more return on investment than Loomis Sayles. However, Asg Managed is 6.29 times more volatile than Loomis Sayles Limited. It trades about 0.04 of its potential returns per unit of risk. Loomis Sayles Limited is currently generating about 0.04 per unit of risk. If you would invest 863.00 in Asg Managed Futures on August 31, 2024 and sell it today you would earn a total of 5.00 from holding Asg Managed Futures or generate 0.58% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Asg Managed Futures vs. Loomis Sayles Limited
Performance |
| Timeline |
| Asg Managed Futures |
| Loomis Sayles Limited |
Asg Managed and Loomis Sayles Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Asg Managed and Loomis Sayles
The main advantage of trading using opposite Asg Managed and Loomis Sayles positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Asg Managed position performs unexpectedly, Loomis Sayles 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 Loomis Sayles will offset losses from the drop in Loomis Sayles' long position.| Asg Managed vs. Aqr Managed Futures | Asg Managed vs. Pimco Trends Managed | Asg Managed vs. Pimco Trends Managed | Asg Managed vs. American Beacon Ahl |
| Loomis Sayles vs. Goldman Sachs Large | Loomis Sayles vs. Legg Mason Bw | Loomis Sayles vs. Qs Large Cap | Loomis Sayles vs. T Rowe Price |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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