Correlation Between Ferrari NV and Rivian Automotive
Can any of the company-specific risk be diversified away by investing in both Ferrari NV and Rivian Automotive 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 Ferrari NV and Rivian Automotive into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ferrari NV and Rivian Automotive, you can compare the effects of market volatilities on Ferrari NV and Rivian Automotive 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 Ferrari NV with a short position of Rivian Automotive. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ferrari NV and Rivian Automotive.
Diversification Opportunities for Ferrari NV and Rivian Automotive
-0.49 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ferrari and Rivian is -0.49. Overlapping area represents the amount of risk that can be diversified away by holding Ferrari NV and Rivian Automotive in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Rivian Automotive and Ferrari NV 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 Ferrari NV are associated (or correlated) with Rivian Automotive. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Rivian Automotive has no effect on the direction of Ferrari NV i.e., Ferrari NV and Rivian Automotive go up and down completely randomly.
Pair Corralation between Ferrari NV and Rivian Automotive
Given the investment horizon of 90 days Ferrari NV is expected to generate 0.33 times more return on investment than Rivian Automotive. However, Ferrari NV is 3.01 times less risky than Rivian Automotive. It trades about 0.08 of its potential returns per unit of risk. Rivian Automotive is currently generating about 0.02 per unit of risk. If you would invest 25,655 in Ferrari NV on November 1, 2024 and sell it today you would earn a total of 17,540 from holding Ferrari NV or generate 68.37% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ferrari NV vs. Rivian Automotive
Performance |
| Timeline |
| Ferrari NV |
| Rivian Automotive |
Ferrari NV and Rivian Automotive Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ferrari NV and Rivian Automotive
The main advantage of trading using opposite Ferrari NV and Rivian Automotive positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ferrari NV position performs unexpectedly, Rivian Automotive 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 Rivian Automotive will offset losses from the drop in Rivian Automotive's long position.| Ferrari NV vs. Volkswagen AG Pref | Ferrari NV vs. Volkswagen AG 110 | Ferrari NV vs. Porsche Automobil Holding | Ferrari NV vs. Toyota Motor |
| Rivian Automotive vs. Nio Class A | Rivian Automotive vs. Xpeng Inc | Rivian Automotive vs. Mullen Automotive | Rivian Automotive vs. Tesla Inc |
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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