Correlation Between Vivendi SE and Franklin Street
Can any of the company-specific risk be diversified away by investing in both Vivendi SE and Franklin Street 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 Vivendi SE and Franklin Street into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vivendi SE and Franklin Street Properties, you can compare the effects of market volatilities on Vivendi SE and Franklin Street 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 Vivendi SE with a short position of Franklin Street. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vivendi SE and Franklin Street.
Diversification Opportunities for Vivendi SE and Franklin Street
-0.51 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Vivendi and Franklin is -0.51. Overlapping area represents the amount of risk that can be diversified away by holding Vivendi SE and Franklin Street Properties in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Franklin Street Prop and Vivendi SE 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 Vivendi SE are associated (or correlated) with Franklin Street. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Franklin Street Prop has no effect on the direction of Vivendi SE i.e., Vivendi SE and Franklin Street go up and down completely randomly.
Pair Corralation between Vivendi SE and Franklin Street
Assuming the 90 days horizon Vivendi SE is expected to generate 19.59 times more return on investment than Franklin Street. However, Vivendi SE is 19.59 times more volatile than Franklin Street Properties. It trades about 0.17 of its potential returns per unit of risk. Franklin Street Properties is currently generating about -0.01 per unit of risk. If you would invest 925.00 in Vivendi SE on September 27, 2024 and sell it today you would lose (325.00) from holding Vivendi SE or give up 35.14% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Vivendi SE vs. Franklin Street Properties
Performance |
Timeline |
Vivendi SE |
Franklin Street Prop |
Vivendi SE and Franklin Street Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Vivendi SE and Franklin Street
The main advantage of trading using opposite Vivendi SE and Franklin Street positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vivendi SE position performs unexpectedly, Franklin Street 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 Franklin Street will offset losses from the drop in Franklin Street's long position.Vivendi SE vs. Legacy Education | Vivendi SE vs. Apple Inc | Vivendi SE vs. NVIDIA | Vivendi SE vs. Microsoft |
Franklin Street vs. Cousins Properties Incorporated | Franklin Street vs. Creative Media Community | Franklin Street vs. Highwoods Properties | Franklin Street vs. Douglas Emmett |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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