Correlation Between Guggenheim High and Mfs Growth
Can any of the company-specific risk be diversified away by investing in both Guggenheim High and Mfs Growth 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 Guggenheim High and Mfs Growth into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Guggenheim High Yield and Mfs Growth Fund, you can compare the effects of market volatilities on Guggenheim High and Mfs Growth 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 Guggenheim High with a short position of Mfs Growth. Check out your portfolio center. Please also check ongoing floating volatility patterns of Guggenheim High and Mfs Growth.
Diversification Opportunities for Guggenheim High and Mfs Growth
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Guggenheim and Mfs is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Guggenheim High Yield and Mfs Growth Fund in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mfs Growth Fund and Guggenheim 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 Guggenheim High Yield are associated (or correlated) with Mfs Growth. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mfs Growth Fund has no effect on the direction of Guggenheim High i.e., Guggenheim High and Mfs Growth go up and down completely randomly.
Pair Corralation between Guggenheim High and Mfs Growth
Assuming the 90 days horizon Guggenheim High is expected to generate 3.28 times less return on investment than Mfs Growth. But when comparing it to its historical volatility, Guggenheim High Yield is 4.18 times less risky than Mfs Growth. It trades about 0.13 of its potential returns per unit of risk. Mfs Growth Fund is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 9,107 in Mfs Growth Fund on September 12, 2024 and sell it today you would earn a total of 6,255 from holding Mfs Growth Fund or generate 68.68% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Guggenheim High Yield vs. Mfs Growth Fund
Performance |
| Timeline |
| Guggenheim High Yield |
| Mfs Growth Fund |
Guggenheim High and Mfs Growth Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Guggenheim High and Mfs Growth
The main advantage of trading using opposite Guggenheim High and Mfs Growth positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Guggenheim High position performs unexpectedly, Mfs Growth 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 Growth will offset losses from the drop in Mfs Growth's long position.The idea behind Guggenheim High Yield and Mfs Growth Fund pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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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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