Correlation Between Shelton Funds and Mainstay Cushing
Can any of the company-specific risk be diversified away by investing in both Shelton Funds and Mainstay Cushing 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 Shelton Funds and Mainstay Cushing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shelton Funds and Mainstay Cushing Mlp, you can compare the effects of market volatilities on Shelton Funds and Mainstay Cushing 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 Shelton Funds with a short position of Mainstay Cushing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shelton Funds and Mainstay Cushing.
Diversification Opportunities for Shelton Funds and Mainstay Cushing
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Shelton and Mainstay is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Shelton Funds and Mainstay Cushing Mlp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mainstay Cushing Mlp and Shelton Funds 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 Shelton Funds are associated (or correlated) with Mainstay Cushing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mainstay Cushing Mlp has no effect on the direction of Shelton Funds i.e., Shelton Funds and Mainstay Cushing go up and down completely randomly.
Pair Corralation between Shelton Funds and Mainstay Cushing
Assuming the 90 days horizon Shelton Funds is expected to generate 1.02 times less return on investment than Mainstay Cushing. In addition to that, Shelton Funds is 1.24 times more volatile than Mainstay Cushing Mlp. It trades about 0.1 of its total potential returns per unit of risk. Mainstay Cushing Mlp is currently generating about 0.12 per unit of volatility. If you would invest 695.00 in Mainstay Cushing Mlp on August 30, 2024 and sell it today you would earn a total of 523.00 from holding Mainstay Cushing Mlp or generate 75.25% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Shelton Funds vs. Mainstay Cushing Mlp
Performance |
Timeline |
Shelton Funds |
Mainstay Cushing Mlp |
Shelton Funds and Mainstay Cushing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shelton Funds and Mainstay Cushing
The main advantage of trading using opposite Shelton Funds and Mainstay Cushing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shelton Funds position performs unexpectedly, Mainstay Cushing 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 Mainstay Cushing will offset losses from the drop in Mainstay Cushing's long position.Shelton Funds vs. Gamco Global Gold | Shelton Funds vs. Fidelity Advisor Gold | Shelton Funds vs. First Eagle Gold | Shelton Funds vs. Goldman Sachs Centrated |
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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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