Correlation Between John Hancock and Mfs Value
Can any of the company-specific risk be diversified away by investing in both John Hancock and Mfs Value 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 John Hancock and Mfs Value into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between John Hancock Disciplined and Mfs Value Fund, you can compare the effects of market volatilities on John Hancock and Mfs Value 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 John Hancock with a short position of Mfs Value. Check out your portfolio center. Please also check ongoing floating volatility patterns of John Hancock and Mfs Value.
Diversification Opportunities for John Hancock and Mfs Value
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between JOHN and Mfs is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding John Hancock Disciplined and Mfs Value Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Value Fund and John Hancock 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 John Hancock Disciplined are associated (or correlated) with Mfs Value. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Value Fund has no effect on the direction of John Hancock i.e., John Hancock and Mfs Value go up and down completely randomly.
Pair Corralation between John Hancock and Mfs Value
Assuming the 90 days horizon John Hancock Disciplined is expected to generate 1.24 times more return on investment than Mfs Value. However, John Hancock is 1.24 times more volatile than Mfs Value Fund. It trades about 0.12 of its potential returns per unit of risk. Mfs Value Fund is currently generating about 0.12 per unit of risk. If you would invest 2,217 in John Hancock Disciplined on August 25, 2024 and sell it today you would earn a total of 501.00 from holding John Hancock Disciplined or generate 22.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
John Hancock Disciplined vs. Mfs Value Fund
Performance |
| Timeline |
| John Hancock Disciplined |
| Mfs Value Fund |
John Hancock and Mfs Value Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with John Hancock and Mfs Value
The main advantage of trading using opposite John Hancock and Mfs Value positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if John Hancock position performs unexpectedly, Mfs Value 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 Mfs Value will offset losses from the drop in Mfs Value's long position.| John Hancock vs. Multimanager Lifestyle Moderate | John Hancock vs. Multimanager Lifestyle Balanced | John Hancock vs. Multimanager Lifestyle Servative | John Hancock vs. Regional Bank Fund |
| Mfs Value vs. Mfs Prudent Investor | Mfs Value vs. Mfs Prudent Investor | Mfs Value vs. Mfs Prudent Investor | Mfs Value vs. Mfs Prudent Investor |
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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