Correlation Between Ab Bond and Loomis Sayles
Can any of the company-specific risk be diversified away by investing in both Ab Bond 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 Ab Bond and Loomis Sayles into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ab Bond Inflation and Loomis Sayles Inflation, you can compare the effects of market volatilities on Ab Bond 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 Ab Bond with a short position of Loomis Sayles. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ab Bond and Loomis Sayles.
Diversification Opportunities for Ab Bond and Loomis Sayles
0.97 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between ABNCX and Loomis is 0.97. Overlapping area represents the amount of risk that can be diversified away by holding Ab Bond Inflation and Loomis Sayles Inflation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Loomis Sayles Inflation and Ab Bond 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 Ab Bond 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 Inflation has no effect on the direction of Ab Bond i.e., Ab Bond and Loomis Sayles go up and down completely randomly.
Pair Corralation between Ab Bond and Loomis Sayles
Assuming the 90 days horizon Ab Bond Inflation is expected to generate 0.73 times more return on investment than Loomis Sayles. However, Ab Bond Inflation is 1.38 times less risky than Loomis Sayles. It trades about 0.27 of its potential returns per unit of risk. Loomis Sayles Inflation is currently generating about 0.16 per unit of risk. If you would invest 991.00 in Ab Bond Inflation on October 22, 2024 and sell it today you would earn a total of 9.00 from holding Ab Bond Inflation or generate 0.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ab Bond Inflation vs. Loomis Sayles Inflation
Performance |
| Timeline |
| Ab Bond Inflation |
| Loomis Sayles Inflation |
Ab Bond and Loomis Sayles Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ab Bond and Loomis Sayles
The main advantage of trading using opposite Ab Bond and Loomis Sayles positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ab Bond 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.| Ab Bond vs. Simt Multi Asset Inflation | Ab Bond vs. Asg Managed Futures | Ab Bond vs. Guidepath Managed Futures | Ab Bond vs. Ab Bond Inflation |
| Loomis Sayles vs. Prudential Financial Services | Loomis Sayles vs. Davis Financial Fund | Loomis Sayles vs. Financial Industries Fund | Loomis Sayles vs. Goldman Sachs Trust |
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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