Correlation Between Loomis Sayles and John Hancock
Can any of the company-specific risk be diversified away by investing in both Loomis Sayles and John Hancock 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 John Hancock into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Loomis Sayles E and John Hancock Financial, you can compare the effects of market volatilities on Loomis Sayles and John Hancock 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 John Hancock. Check out your portfolio center. Please also check ongoing floating volatility patterns of Loomis Sayles and John Hancock.
Diversification Opportunities for Loomis Sayles and John Hancock
-0.29 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Loomis and John is -0.29. Overlapping area represents the amount of risk that can be diversified away by holding Loomis Sayles E and John Hancock Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on John Hancock Financial 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 E are associated (or correlated) with John Hancock. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of John Hancock Financial has no effect on the direction of Loomis Sayles i.e., Loomis Sayles and John Hancock go up and down completely randomly.
Pair Corralation between Loomis Sayles and John Hancock
Assuming the 90 days horizon Loomis Sayles is expected to generate 49.57 times less return on investment than John Hancock. But when comparing it to its historical volatility, Loomis Sayles E is 4.22 times less risky than John Hancock. It trades about 0.01 of its potential returns per unit of risk. John Hancock Financial is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 2,814 in John Hancock Financial on October 7, 2024 and sell it today you would earn a total of 726.00 from holding John Hancock Financial or generate 25.8% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Loomis Sayles E vs. John Hancock Financial
Performance |
Timeline |
Loomis Sayles E |
John Hancock Financial |
Loomis Sayles and John Hancock Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Loomis Sayles and John Hancock
The main advantage of trading using opposite Loomis Sayles and John Hancock positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Loomis Sayles position performs unexpectedly, John Hancock 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 John Hancock will offset losses from the drop in John Hancock's long position.Loomis Sayles vs. Rbc Ultra Short Fixed | Loomis Sayles vs. California Bond Fund | Loomis Sayles vs. Siit High Yield | Loomis Sayles vs. Alliancebernstein Bond |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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