Correlation Between Blackrock and Loomis Sayles
Can any of the company-specific risk be diversified away by investing in both Blackrock 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 Blackrock and Loomis Sayles into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Blackrock Hi Yld and Loomis Sayles Institutional, you can compare the effects of market volatilities on Blackrock 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 Blackrock with a short position of Loomis Sayles. Check out your portfolio center. Please also check ongoing floating volatility patterns of Blackrock and Loomis Sayles.
Diversification Opportunities for Blackrock and Loomis Sayles
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Blackrock and Loomis is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Blackrock Hi Yld and Loomis Sayles Institutional in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Loomis Sayles Instit and Blackrock 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 Blackrock Hi Yld 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 Instit has no effect on the direction of Blackrock i.e., Blackrock and Loomis Sayles go up and down completely randomly.
Pair Corralation between Blackrock and Loomis Sayles
Assuming the 90 days horizon Blackrock is expected to generate 1.43 times less return on investment than Loomis Sayles. But when comparing it to its historical volatility, Blackrock Hi Yld is 1.11 times less risky than Loomis Sayles. It trades about 0.26 of its potential returns per unit of risk. Loomis Sayles Institutional is currently generating about 0.33 of returns per unit of risk over similar time horizon. If you would invest 593.00 in Loomis Sayles Institutional on August 29, 2024 and sell it today you would earn a total of 8.00 from holding Loomis Sayles Institutional or generate 1.35% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 95.65% |
| Values | Daily Returns |
Blackrock Hi Yld vs. Loomis Sayles Institutional
Performance |
| Timeline |
| Blackrock Hi Yld |
| Loomis Sayles Instit |
Blackrock and Loomis Sayles Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Blackrock and Loomis Sayles
The main advantage of trading using opposite Blackrock and Loomis Sayles positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Blackrock 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.| Blackrock vs. Vanguard Short Term Investment Grade | Blackrock vs. Vanguard Inflation Protected Securities | Blackrock vs. Vanguard Gnma Fund | Blackrock vs. Vanguard Intermediate Term Investment Grade |
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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 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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