Correlation Between Mfs Intrinsic and Mfs Series
Can any of the company-specific risk be diversified away by investing in both Mfs Intrinsic and Mfs Series 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 Intrinsic and Mfs Series into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mfs Intrinsic Value and Mfs Series Trust, you can compare the effects of market volatilities on Mfs Intrinsic and Mfs Series 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 Intrinsic with a short position of Mfs Series. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mfs Intrinsic and Mfs Series.
Diversification Opportunities for Mfs Intrinsic and Mfs Series
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mfs and Mfs is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Mfs Intrinsic Value and Mfs Series Trust in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Series Trust and Mfs Intrinsic 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 Intrinsic Value are associated (or correlated) with Mfs Series. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Series Trust has no effect on the direction of Mfs Intrinsic i.e., Mfs Intrinsic and Mfs Series go up and down completely randomly.
Pair Corralation between Mfs Intrinsic and Mfs Series
Assuming the 90 days horizon Mfs Intrinsic Value is expected to generate 1.96 times more return on investment than Mfs Series. However, Mfs Intrinsic is 1.96 times more volatile than Mfs Series Trust. It trades about 0.06 of its potential returns per unit of risk. Mfs Series Trust is currently generating about 0.12 per unit of risk. If you would invest 1,236 in Mfs Intrinsic Value on September 15, 2024 and sell it today you would earn a total of 10.00 from holding Mfs Intrinsic Value or generate 0.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Mfs Intrinsic Value vs. Mfs Series Trust
Performance |
Timeline |
Mfs Intrinsic Value |
Mfs Series Trust |
Mfs Intrinsic and Mfs Series Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mfs Intrinsic and Mfs Series
The main advantage of trading using opposite Mfs Intrinsic and Mfs Series positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mfs Intrinsic position performs unexpectedly, Mfs Series 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 Series will offset losses from the drop in Mfs Series' long position.Mfs Intrinsic vs. Mfs Prudent Investor | Mfs Intrinsic vs. Mfs Prudent Investor | Mfs Intrinsic vs. Mfs Prudent Investor | Mfs Intrinsic vs. Mfs Prudent Investor |
Mfs Series vs. Mfs Prudent Investor | Mfs Series vs. Mfs Prudent Investor | Mfs Series vs. Mfs Prudent Investor | Mfs Series 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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