Correlation Between Freedom Day and FFEM
Can any of the company-specific risk be diversified away by investing in both Freedom Day and FFEM 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 Freedom Day and FFEM into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Freedom Day Dividend and FFEM, you can compare the effects of market volatilities on Freedom Day and FFEM 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 Freedom Day with a short position of FFEM. Check out your portfolio center. Please also check ongoing floating volatility patterns of Freedom Day and FFEM.
Diversification Opportunities for Freedom Day and FFEM
-0.72 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Freedom and FFEM is -0.72. Overlapping area represents the amount of risk that can be diversified away by holding Freedom Day Dividend and FFEM in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FFEM and Freedom Day 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 Freedom Day Dividend are associated (or correlated) with FFEM. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FFEM has no effect on the direction of Freedom Day i.e., Freedom Day and FFEM go up and down completely randomly.
Pair Corralation between Freedom Day and FFEM
Given the investment horizon of 90 days Freedom Day Dividend is expected to generate 2.15 times more return on investment than FFEM. However, Freedom Day is 2.15 times more volatile than FFEM. It trades about 0.11 of its potential returns per unit of risk. FFEM is currently generating about 0.11 per unit of risk. If you would invest 2,580 in Freedom Day Dividend on September 12, 2024 and sell it today you would earn a total of 836.00 from holding Freedom Day Dividend or generate 32.4% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 4.55% |
| Values | Daily Returns |
Freedom Day Dividend vs. FFEM
Performance |
| Timeline |
| Freedom Day Dividend |
| FFEM |
Freedom Day and FFEM Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Freedom Day and FFEM
The main advantage of trading using opposite Freedom Day and FFEM positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Freedom Day position performs unexpectedly, FFEM 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 FFEM will offset losses from the drop in FFEM's long position.The idea behind Freedom Day Dividend and FFEM 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.| FFEM vs. Freedom Day Dividend | FFEM vs. Franklin Templeton ETF | FFEM vs. iShares MSCI China | FFEM vs. Tidal Trust II |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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