Correlation Between GM and Vivendi SE
Can any of the company-specific risk be diversified away by investing in both GM and Vivendi SE 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 GM and Vivendi SE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Vivendi SE, you can compare the effects of market volatilities on GM and Vivendi SE 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 GM with a short position of Vivendi SE. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Vivendi SE.
Diversification Opportunities for GM and Vivendi SE
-0.22 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GM and Vivendi is -0.22. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Vivendi SE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Vivendi SE and GM 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 General Motors are associated (or correlated) with Vivendi SE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Vivendi SE has no effect on the direction of GM i.e., GM and Vivendi SE go up and down completely randomly.
Pair Corralation between GM and Vivendi SE
Allowing for the 90-day total investment horizon General Motors is expected to generate 0.07 times more return on investment than Vivendi SE. However, General Motors is 13.93 times less risky than Vivendi SE. It trades about -0.06 of its potential returns per unit of risk. Vivendi SE is currently generating about -0.17 per unit of risk. If you would invest 5,538 in General Motors on September 28, 2024 and sell it today you would lose (109.00) from holding General Motors or give up 1.97% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.24% |
Values | Daily Returns |
General Motors vs. Vivendi SE
Performance |
Timeline |
General Motors |
Vivendi SE |
GM and Vivendi SE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Vivendi SE
The main advantage of trading using opposite GM and Vivendi SE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Vivendi SE 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 Vivendi SE will offset losses from the drop in Vivendi SE's long position.The idea behind General Motors and Vivendi SE 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.Vivendi SE vs. The Walt Disney | Vivendi SE vs. Charter Communications | Vivendi SE vs. Warner Music Group | Vivendi SE vs. ViacomCBS |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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