Correlation Between CNH Industrial and GreenPower
Can any of the company-specific risk be diversified away by investing in both CNH Industrial and GreenPower 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 CNH Industrial and GreenPower into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CNH Industrial NV and GreenPower Motor, you can compare the effects of market volatilities on CNH Industrial and GreenPower 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 CNH Industrial with a short position of GreenPower. Check out your portfolio center. Please also check ongoing floating volatility patterns of CNH Industrial and GreenPower.
Diversification Opportunities for CNH Industrial and GreenPower
-0.09 | Correlation Coefficient |
Good diversification
The 3 months correlation between CNH and GreenPower is -0.09. Overlapping area represents the amount of risk that can be diversified away by holding CNH Industrial NV and GreenPower Motor in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GreenPower Motor and CNH Industrial 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 CNH Industrial NV are associated (or correlated) with GreenPower. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GreenPower Motor has no effect on the direction of CNH Industrial i.e., CNH Industrial and GreenPower go up and down completely randomly.
Pair Corralation between CNH Industrial and GreenPower
Considering the 90-day investment horizon CNH Industrial NV is expected to generate 0.18 times more return on investment than GreenPower. However, CNH Industrial NV is 5.53 times less risky than GreenPower. It trades about 0.54 of its potential returns per unit of risk. GreenPower Motor is currently generating about 0.05 per unit of risk. If you would invest 1,133 in CNH Industrial NV on November 1, 2024 and sell it today you would earn a total of 190.00 from holding CNH Industrial NV or generate 16.77% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
CNH Industrial NV vs. GreenPower Motor
Performance |
| Timeline |
| CNH Industrial NV |
| GreenPower Motor |
CNH Industrial and GreenPower Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CNH Industrial and GreenPower
The main advantage of trading using opposite CNH Industrial and GreenPower positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CNH Industrial position performs unexpectedly, GreenPower 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 GreenPower will offset losses from the drop in GreenPower's long position.| CNH Industrial vs. Tradeweb Markets | CNH Industrial vs. Alternative Investment | CNH Industrial vs. Compania Cervecerias Unidas | CNH Industrial vs. Summit Hotel Properties |
| GreenPower vs. Phoenix Motor Common | GreenPower vs. Envirotech Vehicles | GreenPower vs. Volcon Inc | GreenPower vs. Zapp Electric Vehicles |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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