Correlation Between DTF Tax and MFS Government
Can any of the company-specific risk be diversified away by investing in both DTF Tax and MFS Government 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 DTF Tax and MFS Government into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DTF Tax Free and MFS Government Markets, you can compare the effects of market volatilities on DTF Tax and MFS Government 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 DTF Tax with a short position of MFS Government. Check out your portfolio center. Please also check ongoing floating volatility patterns of DTF Tax and MFS Government.
Diversification Opportunities for DTF Tax and MFS Government
-0.16 | Correlation Coefficient |
Good diversification
The 3 months correlation between DTF and MFS is -0.16. Overlapping area represents the amount of risk that can be diversified away by holding DTF Tax Free and MFS Government Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MFS Government Markets and DTF Tax 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 DTF Tax Free are associated (or correlated) with MFS Government. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MFS Government Markets has no effect on the direction of DTF Tax i.e., DTF Tax and MFS Government go up and down completely randomly.
Pair Corralation between DTF Tax and MFS Government
Considering the 90-day investment horizon DTF Tax Free is expected to generate 0.68 times more return on investment than MFS Government. However, DTF Tax Free is 1.48 times less risky than MFS Government. It trades about 0.09 of its potential returns per unit of risk. MFS Government Markets is currently generating about -0.11 per unit of risk. If you would invest 1,117 in DTF Tax Free on August 27, 2024 and sell it today you would earn a total of 9.00 from holding DTF Tax Free or generate 0.81% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
DTF Tax Free vs. MFS Government Markets
Performance |
| Timeline |
| DTF Tax Free |
| MFS Government Markets |
DTF Tax and MFS Government Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DTF Tax and MFS Government
The main advantage of trading using opposite DTF Tax and MFS Government positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DTF Tax position performs unexpectedly, MFS Government 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 Government will offset losses from the drop in MFS Government's long position.| DTF Tax vs. PowerUp Acquisition Corp | DTF Tax vs. Aurora Innovation | DTF Tax vs. HUMANA INC | DTF Tax vs. Aquagold International |
| MFS Government vs. MFS Investment Grade | MFS Government vs. Invesco High Income | MFS Government vs. Eaton Vance National | MFS Government vs. Nuveen California Select |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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