Correlation Between EVS Broadcast and Fannie Mae
Can any of the company-specific risk be diversified away by investing in both EVS Broadcast and Fannie Mae 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 EVS Broadcast and Fannie Mae into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EVS Broadcast Equipment and Fannie Mae, you can compare the effects of market volatilities on EVS Broadcast and Fannie Mae 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 EVS Broadcast with a short position of Fannie Mae. Check out your portfolio center. Please also check ongoing floating volatility patterns of EVS Broadcast and Fannie Mae.
Diversification Opportunities for EVS Broadcast and Fannie Mae
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between EVS and Fannie is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding EVS Broadcast Equipment and Fannie Mae in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fannie Mae and EVS Broadcast 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 EVS Broadcast Equipment are associated (or correlated) with Fannie Mae. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fannie Mae has no effect on the direction of EVS Broadcast i.e., EVS Broadcast and Fannie Mae go up and down completely randomly.
Pair Corralation between EVS Broadcast and Fannie Mae
Assuming the 90 days trading horizon EVS Broadcast is expected to generate 18.66 times less return on investment than Fannie Mae. But when comparing it to its historical volatility, EVS Broadcast Equipment is 7.13 times less risky than Fannie Mae. It trades about 0.09 of its potential returns per unit of risk. Fannie Mae is currently generating about 0.22 of returns per unit of risk over similar time horizon. If you would invest 121.00 in Fannie Mae on September 14, 2024 and sell it today you would earn a total of 154.00 from holding Fannie Mae or generate 127.27% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 75.0% |
Values | Daily Returns |
EVS Broadcast Equipment vs. Fannie Mae
Performance |
Timeline |
EVS Broadcast Equipment |
Fannie Mae |
EVS Broadcast and Fannie Mae Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with EVS Broadcast and Fannie Mae
The main advantage of trading using opposite EVS Broadcast and Fannie Mae positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EVS Broadcast position performs unexpectedly, Fannie Mae 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 Fannie Mae will offset losses from the drop in Fannie Mae's long position.EVS Broadcast vs. Samsung Electronics Co | EVS Broadcast vs. Samsung Electronics Co | EVS Broadcast vs. Hyundai Motor | EVS Broadcast vs. Reliance Industries Ltd |
Fannie Mae vs. Premier Foods PLC | Fannie Mae vs. Taiwan Semiconductor Manufacturing | Fannie Mae vs. Gaztransport et Technigaz | Fannie Mae vs. EVS Broadcast Equipment |
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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