Correlation Between NYSE Composite and Mfs High
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and Mfs High 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 NYSE Composite and Mfs High into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and Mfs High Yield, you can compare the effects of market volatilities on NYSE Composite and Mfs High 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 NYSE Composite with a short position of Mfs High. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and Mfs High.
Diversification Opportunities for NYSE Composite and Mfs High
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NYSE and Mfs is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and Mfs High Yield in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs High Yield and NYSE Composite 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 NYSE Composite are associated (or correlated) with Mfs High. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs High Yield has no effect on the direction of NYSE Composite i.e., NYSE Composite and Mfs High go up and down completely randomly.
Pair Corralation between NYSE Composite and Mfs High
Assuming the 90 days trading horizon NYSE Composite is expected to generate 3.83 times more return on investment than Mfs High. However, NYSE Composite is 3.83 times more volatile than Mfs High Yield. It trades about 0.38 of its potential returns per unit of risk. Mfs High Yield is currently generating about 0.12 per unit of risk. If you would invest 1,924,339 in NYSE Composite on September 4, 2024 and sell it today you would earn a total of 96,983 from holding NYSE Composite or generate 5.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 90.48% |
| Values | Daily Returns |
NYSE Composite vs. Mfs High Yield
Performance |
| Timeline |
NYSE Composite and Mfs High Volatility Contrast
Predicted Return Density |
| Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
Mfs High Yield
Pair trading matchups for Mfs High
Pair Trading with NYSE Composite and Mfs High
The main advantage of trading using opposite NYSE Composite and Mfs High positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, Mfs High 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 High will offset losses from the drop in Mfs High's long position.| NYSE Composite vs. Kite Realty Group | NYSE Composite vs. Tradeweb Markets | NYSE Composite vs. Meiwu Technology Co | NYSE Composite vs. Uber Technologies |
| Mfs High vs. Mfs Prudent Investor | Mfs High vs. Mfs Prudent Investor | Mfs High vs. Mfs Prudent Investor | Mfs High 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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