Correlation Between GM and Stellantis
Can any of the company-specific risk be diversified away by investing in both GM and Stellantis 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 Stellantis into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Stellantis NV, you can compare the effects of market volatilities on GM and Stellantis 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 Stellantis. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Stellantis.
Diversification Opportunities for GM and Stellantis
-0.43 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GM and Stellantis is -0.43. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Stellantis NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Stellantis NV 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 Stellantis. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Stellantis NV has no effect on the direction of GM i.e., GM and Stellantis go up and down completely randomly.
Pair Corralation between GM and Stellantis
Allowing for the 90-day total investment horizon General Motors is expected to generate 1.14 times more return on investment than Stellantis. However, GM is 1.14 times more volatile than Stellantis NV. It trades about 0.26 of its potential returns per unit of risk. Stellantis NV is currently generating about -0.13 per unit of risk. If you would invest 5,273 in General Motors on August 27, 2024 and sell it today you would earn a total of 580.00 from holding General Motors or generate 11.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
General Motors vs. Stellantis NV
Performance |
| Timeline |
| General Motors |
| Stellantis NV |
GM and Stellantis Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Stellantis
The main advantage of trading using opposite GM and Stellantis positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Stellantis 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 Stellantis will offset losses from the drop in Stellantis' long position.The idea behind General Motors and Stellantis NV 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.| Stellantis vs. Porsche Automobile Holding | Stellantis vs. Toyota Motor | Stellantis vs. Honda Motor Co | Stellantis vs. General Motors |
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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