Correlation Between Sarofim Equity and Federated Strategic
Can any of the company-specific risk be diversified away by investing in both Sarofim Equity and Federated Strategic 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 Sarofim Equity and Federated Strategic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sarofim Equity and Federated Strategic Income, you can compare the effects of market volatilities on Sarofim Equity and Federated Strategic 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 Sarofim Equity with a short position of Federated Strategic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sarofim Equity and Federated Strategic.
Diversification Opportunities for Sarofim Equity and Federated Strategic
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Sarofim and Federated is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Sarofim Equity and Federated Strategic Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Strategic and Sarofim Equity 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 Sarofim Equity are associated (or correlated) with Federated Strategic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Strategic has no effect on the direction of Sarofim Equity i.e., Sarofim Equity and Federated Strategic go up and down completely randomly.
Pair Corralation between Sarofim Equity and Federated Strategic
Assuming the 90 days horizon Sarofim Equity is expected to under-perform the Federated Strategic. In addition to that, Sarofim Equity is 3.51 times more volatile than Federated Strategic Income. It trades about -0.01 of its total potential returns per unit of risk. Federated Strategic Income is currently generating about 0.09 per unit of volatility. If you would invest 735.00 in Federated Strategic Income on October 3, 2024 and sell it today you would earn a total of 81.00 from holding Federated Strategic Income or generate 11.02% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Sarofim Equity vs. Federated Strategic Income
Performance |
Timeline |
Sarofim Equity |
Federated Strategic |
Sarofim Equity and Federated Strategic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sarofim Equity and Federated Strategic
The main advantage of trading using opposite Sarofim Equity and Federated Strategic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sarofim Equity position performs unexpectedly, Federated Strategic 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 Federated Strategic will offset losses from the drop in Federated Strategic's long position.Sarofim Equity vs. Versatile Bond Portfolio | Sarofim Equity vs. Nuveen Arizona Municipal | Sarofim Equity vs. Oklahoma Municipal Fund | Sarofim Equity vs. Ft 7934 Corporate |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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