Correlation Between Mfs Intermediate and Cm Modity
Can any of the company-specific risk be diversified away by investing in both Mfs Intermediate and Cm Modity 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 Mfs Intermediate and Cm Modity into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mfs Intermediate High and Cm Modity Index, you can compare the effects of market volatilities on Mfs Intermediate and Cm Modity 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 Mfs Intermediate with a short position of Cm Modity. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Intermediate and Cm Modity.
Diversification Opportunities for Mfs Intermediate and Cm Modity
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mfs and COMIX is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Intermediate High and Cm Modity Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cm Modity Index and Mfs Intermediate 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 Mfs Intermediate High are associated (or correlated) with Cm Modity. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cm Modity Index has no effect on the direction of Mfs Intermediate i.e., Mfs Intermediate and Cm Modity go up and down completely randomly.
Pair Corralation between Mfs Intermediate and Cm Modity
Considering the 90-day investment horizon Mfs Intermediate High is expected to generate 0.94 times more return on investment than Cm Modity. However, Mfs Intermediate High is 1.06 times less risky than Cm Modity. It trades about 0.17 of its potential returns per unit of risk. Cm Modity Index is currently generating about 0.07 per unit of risk. If you would invest 163.00 in Mfs Intermediate High on April 28, 2025 and sell it today you would earn a total of 12.00 from holding Mfs Intermediate High or generate 7.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Mfs Intermediate High vs. Cm Modity Index
Performance |
Timeline |
Mfs Intermediate High |
Cm Modity Index |
Mfs Intermediate and Cm Modity Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Intermediate and Cm Modity
The main advantage of trading using opposite Mfs Intermediate and Cm Modity positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Intermediate position performs unexpectedly, Cm Modity 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 Cm Modity will offset losses from the drop in Cm Modity's long position.Mfs Intermediate vs. BNY Mellon High | Mfs Intermediate vs. MFS High Yield | Mfs Intermediate vs. MFS Government Markets | Mfs Intermediate vs. MFS High Income |
Cm Modity vs. Vanguard Financials Index | Cm Modity vs. John Hancock Financial | Cm Modity vs. Fidelity Advisor Financial | Cm Modity vs. Rmb Mendon Financial |
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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