Correlation Between Loomis Sayles and Loomis Sayles
Can any of the company-specific risk be diversified away by investing in both Loomis Sayles 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 Loomis Sayles and Loomis Sayles into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Loomis Sayles Inflation and Loomis Sayles Smallmid, you can compare the effects of market volatilities on Loomis Sayles 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 Loomis Sayles with a short position of Loomis Sayles. Check out your portfolio center. Please also check ongoing floating volatility patterns of Loomis Sayles and Loomis Sayles.
Diversification Opportunities for Loomis Sayles and Loomis Sayles
-0.56 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Loomis and Loomis is -0.56. Overlapping area represents the amount of risk that can be diversified away by holding Loomis Sayles Inflation and Loomis Sayles Smallmid in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Loomis Sayles Smallmid and Loomis Sayles 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 Loomis Sayles Inflation 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 Smallmid has no effect on the direction of Loomis Sayles i.e., Loomis Sayles and Loomis Sayles go up and down completely randomly.
Pair Corralation between Loomis Sayles and Loomis Sayles
Assuming the 90 days horizon Loomis Sayles is expected to generate 5.07 times less return on investment than Loomis Sayles. But when comparing it to its historical volatility, Loomis Sayles Inflation is 2.67 times less risky than Loomis Sayles. It trades about 0.03 of its potential returns per unit of risk. Loomis Sayles Smallmid is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 1,132 in Loomis Sayles Smallmid on September 3, 2024 and sell it today you would earn a total of 330.00 from holding Loomis Sayles Smallmid or generate 29.15% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Loomis Sayles Inflation vs. Loomis Sayles Smallmid
Performance |
| Timeline |
| Loomis Sayles Inflation |
| Loomis Sayles Smallmid |
Loomis Sayles and Loomis Sayles Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Loomis Sayles and Loomis Sayles
The main advantage of trading using opposite Loomis Sayles and Loomis Sayles positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Loomis Sayles 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.| Loomis Sayles vs. Artisan High Income | Loomis Sayles vs. Ultra Short Fixed Income | Loomis Sayles vs. Gmo High Yield | Loomis Sayles vs. Multisector Bond Sma |
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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 Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
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