Correlation Between Hawaiian Electric and Mfs Utilities
Can any of the company-specific risk be diversified away by investing in both Hawaiian Electric 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 Hawaiian Electric and Mfs Utilities into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hawaiian Electric Industries and Mfs Utilities Fund, you can compare the effects of market volatilities on Hawaiian Electric 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 Hawaiian Electric with a short position of Mfs Utilities. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hawaiian Electric and Mfs Utilities.
Diversification Opportunities for Hawaiian Electric and Mfs Utilities
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hawaiian and Mfs is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Hawaiian Electric Industries and Mfs Utilities Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Utilities and Hawaiian Electric 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 Hawaiian Electric Industries 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 Hawaiian Electric i.e., Hawaiian Electric and Mfs Utilities go up and down completely randomly.
Pair Corralation between Hawaiian Electric and Mfs Utilities
Allowing for the 90-day total investment horizon Hawaiian Electric Industries is expected to generate 2.73 times more return on investment than Mfs Utilities. However, Hawaiian Electric is 2.73 times more volatile than Mfs Utilities Fund. It trades about 0.03 of its potential returns per unit of risk. Mfs Utilities Fund is currently generating about -0.13 per unit of risk. If you would invest 1,039 in Hawaiian Electric Industries on November 29, 2024 and sell it today you would earn a total of 33.00 from holding Hawaiian Electric Industries or generate 3.18% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hawaiian Electric Industries vs. Mfs Utilities Fund
Performance |
Timeline |
Hawaiian Electric |
Mfs Utilities |
Hawaiian Electric and Mfs Utilities Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hawaiian Electric and Mfs Utilities
The main advantage of trading using opposite Hawaiian Electric and Mfs Utilities positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hawaiian Electric 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.Hawaiian Electric vs. DTE Energy | Hawaiian Electric vs. Alliant Energy Corp | Hawaiian Electric vs. Ameren Corp | Hawaiian Electric vs. CenterPoint Energy |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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