Correlation Between First Eagle and Power Floating
Can any of the company-specific risk be diversified away by investing in both First Eagle and Power Floating 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 First Eagle and Power Floating into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Eagle Smid and Power Floating Rate, you can compare the effects of market volatilities on First Eagle and Power Floating 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 First Eagle with a short position of Power Floating. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Eagle and Power Floating.
Diversification Opportunities for First Eagle and Power Floating
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between First and Power is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding First Eagle Smid and Power Floating Rate in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Power Floating Rate and First Eagle 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 First Eagle Smid are associated (or correlated) with Power Floating. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Power Floating Rate has no effect on the direction of First Eagle i.e., First Eagle and Power Floating go up and down completely randomly.
Pair Corralation between First Eagle and Power Floating
Assuming the 90 days horizon First Eagle Smid is expected to generate about the same return on investment as Power Floating Rate. However, First Eagle is 15.11 times more volatile than Power Floating Rate. It trades about 0.02 of its potential returns per unit of risk. Power Floating Rate is currently producing about 0.33 per unit of risk. If you would invest 950.00 in Power Floating Rate on September 19, 2024 and sell it today you would earn a total of 12.00 from holding Power Floating Rate or generate 1.26% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
First Eagle Smid vs. Power Floating Rate
Performance |
Timeline |
First Eagle Smid |
Power Floating Rate |
First Eagle and Power Floating Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Eagle and Power Floating
The main advantage of trading using opposite First Eagle and Power Floating positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Eagle position performs unexpectedly, Power Floating 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 Power Floating will offset losses from the drop in Power Floating's long position.First Eagle vs. First Eagle Global | First Eagle vs. First Eagle Global | First Eagle vs. First Eagle Global | First Eagle vs. First Eagle Fund |
Power Floating vs. Power Global Tactical | Power Floating vs. Power Floating Rate | Power Floating vs. Prudential Jennison International | Power Floating vs. Fidelity New Markets |
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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