Correlation Between Franklin Utilities and Mfs Utilities
Can any of the company-specific risk be diversified away by investing in both Franklin Utilities and Mfs Utilities 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 Franklin Utilities and Mfs Utilities into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin Utilities Fund and Mfs Utilities Fund, you can compare the effects of market volatilities on Franklin Utilities and Mfs Utilities 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 Franklin Utilities with a short position of Mfs Utilities. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin Utilities and Mfs Utilities.
Diversification Opportunities for Franklin Utilities and Mfs Utilities
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Franklin and MFS is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Franklin Utilities Fund and Mfs Utilities Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Utilities and Franklin Utilities 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 Franklin Utilities Fund are associated (or correlated) with Mfs Utilities. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Utilities has no effect on the direction of Franklin Utilities i.e., Franklin Utilities and Mfs Utilities go up and down completely randomly.
Pair Corralation between Franklin Utilities and Mfs Utilities
Assuming the 90 days horizon Franklin Utilities Fund is expected to generate 1.03 times more return on investment than Mfs Utilities. However, Franklin Utilities is 1.03 times more volatile than Mfs Utilities Fund. It trades about 0.19 of its potential returns per unit of risk. Mfs Utilities Fund is currently generating about 0.11 per unit of risk. If you would invest 2,367 in Franklin Utilities Fund on August 31, 2024 and sell it today you would earn a total of 258.00 from holding Franklin Utilities Fund or generate 10.9% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Franklin Utilities Fund vs. Mfs Utilities Fund
Performance |
Timeline |
Franklin Utilities |
Mfs Utilities |
Franklin Utilities and Mfs Utilities Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Franklin Utilities and Mfs Utilities
The main advantage of trading using opposite Franklin Utilities and Mfs Utilities positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin Utilities position performs unexpectedly, Mfs Utilities 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 Utilities will offset losses from the drop in Mfs Utilities' long position.Franklin Utilities vs. Legg Mason Bw | Franklin Utilities vs. American Mutual Fund | Franklin Utilities vs. Touchstone Large Cap | Franklin Utilities vs. Americafirst Large Cap |
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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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