Correlation Between Franklin Fund and Federated Hermes
Can any of the company-specific risk be diversified away by investing in both Franklin Fund and Federated Hermes 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 Franklin Fund and Federated Hermes into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin Fund Allocator and Federated Hermes Inflation, you can compare the effects of market volatilities on Franklin Fund and Federated Hermes 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 Franklin Fund with a short position of Federated Hermes. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin Fund and Federated Hermes.
Diversification Opportunities for Franklin Fund and Federated Hermes
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Franklin and Federated is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Franklin Fund Allocator and Federated Hermes Inflation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Federated Hermes Inf and Franklin Fund 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 Franklin Fund Allocator are associated (or correlated) with Federated Hermes. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Federated Hermes Inf has no effect on the direction of Franklin Fund i.e., Franklin Fund and Federated Hermes go up and down completely randomly.
Pair Corralation between Franklin Fund and Federated Hermes
Assuming the 90 days horizon Franklin Fund Allocator is expected to generate 2.27 times more return on investment than Federated Hermes. However, Franklin Fund is 2.27 times more volatile than Federated Hermes Inflation. It trades about 0.04 of its potential returns per unit of risk. Federated Hermes Inflation is currently generating about 0.01 per unit of risk. If you would invest 883.00 in Franklin Fund Allocator on October 4, 2024 and sell it today you would earn a total of 130.00 from holding Franklin Fund Allocator or generate 14.72% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Franklin Fund Allocator vs. Federated Hermes Inflation
Performance |
Timeline |
Franklin Fund Allocator |
Federated Hermes Inf |
Franklin Fund and Federated Hermes Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Franklin Fund and Federated Hermes
The main advantage of trading using opposite Franklin Fund and Federated Hermes positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin Fund position performs unexpectedly, Federated Hermes 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 Hermes will offset losses from the drop in Federated Hermes' long position.Franklin Fund vs. Baird Short Term Bond | Franklin Fund vs. Astor Longshort Fund | Franklin Fund vs. Quantitative Longshort Equity | Franklin Fund vs. Touchstone Ultra Short |
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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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