Correlation Between MFS High and Putnam Master
Can any of the company-specific risk be diversified away by investing in both MFS High and Putnam Master 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 High and Putnam Master into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MFS High Income and Putnam Master Intermediate, you can compare the effects of market volatilities on MFS High and Putnam Master 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 High with a short position of Putnam Master. Check out your portfolio center. Please also check ongoing floating volatility patterns of MFS High and Putnam Master.
Diversification Opportunities for MFS High and Putnam Master
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between MFS and Putnam is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding MFS High Income and Putnam Master Intermediate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Master Interm and MFS High 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 High Income are associated (or correlated) with Putnam Master. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Putnam Master Interm has no effect on the direction of MFS High i.e., MFS High and Putnam Master go up and down completely randomly.
Pair Corralation between MFS High and Putnam Master
Considering the 90-day investment horizon MFS High Income is expected to generate 1.92 times more return on investment than Putnam Master. However, MFS High is 1.92 times more volatile than Putnam Master Intermediate. It trades about 0.14 of its potential returns per unit of risk. Putnam Master Intermediate is currently generating about 0.13 per unit of risk. If you would invest 366.00 in MFS High Income on November 5, 2024 and sell it today you would earn a total of 9.00 from holding MFS High Income or generate 2.46% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
MFS High Income vs. Putnam Master Intermediate
Performance |
| Timeline |
| MFS High Income |
| Putnam Master Interm |
MFS High and Putnam Master Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with MFS High and Putnam Master
The main advantage of trading using opposite MFS High and Putnam Master positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MFS High position performs unexpectedly, Putnam Master 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 Putnam Master will offset losses from the drop in Putnam Master's long position.| MFS High vs. MFS Investment Grade | MFS High vs. Eaton Vance National | MFS High vs. Blackrock Muniholdings Ny | MFS High vs. Nuveen California Select |
| Putnam Master vs. MFS High Income | Putnam Master vs. MFS Investment Grade | Putnam Master vs. Eaton Vance National | Putnam Master vs. MFS High Yield |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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