Correlation Between Loomis Sayles and Ab Bond
Can any of the company-specific risk be diversified away by investing in both Loomis Sayles and Ab Bond 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 Ab Bond 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 Ab Bond Inflation, you can compare the effects of market volatilities on Loomis Sayles and Ab Bond 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 Ab Bond. Check out your portfolio center. Please also check ongoing floating volatility patterns of Loomis Sayles and Ab Bond.
Diversification Opportunities for Loomis Sayles and Ab Bond
0.97 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Loomis and ABNCX is 0.97. Overlapping area represents the amount of risk that can be diversified away by holding Loomis Sayles Inflation and Ab Bond Inflation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ab Bond Inflation 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 Ab Bond. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ab Bond Inflation has no effect on the direction of Loomis Sayles i.e., Loomis Sayles and Ab Bond go up and down completely randomly.
Pair Corralation between Loomis Sayles and Ab Bond
Assuming the 90 days horizon Loomis Sayles is expected to generate 1.17 times less return on investment than Ab Bond. In addition to that, Loomis Sayles is 1.36 times more volatile than Ab Bond Inflation. It trades about 0.05 of its total potential returns per unit of risk. Ab Bond Inflation is currently generating about 0.09 per unit of volatility. If you would invest 960.00 in Ab Bond Inflation on October 22, 2024 and sell it today you would earn a total of 40.00 from holding Ab Bond Inflation or generate 4.17% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Loomis Sayles Inflation vs. Ab Bond Inflation
Performance |
| Timeline |
| Loomis Sayles Inflation |
| Ab Bond Inflation |
Loomis Sayles and Ab Bond Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Loomis Sayles and Ab Bond
The main advantage of trading using opposite Loomis Sayles and Ab Bond positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Loomis Sayles position performs unexpectedly, Ab Bond 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 Ab Bond will offset losses from the drop in Ab Bond's long position.| Loomis Sayles vs. Prudential Financial Services | Loomis Sayles vs. Davis Financial Fund | Loomis Sayles vs. Financial Industries Fund | Loomis Sayles vs. Goldman Sachs Trust |
| 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 |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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