Correlation Between Cardinal Health and Custom Truck
Can any of the company-specific risk be diversified away by investing in both Cardinal Health and Custom Truck 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 Cardinal Health and Custom Truck into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cardinal Health and Custom Truck One, you can compare the effects of market volatilities on Cardinal Health and Custom Truck 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 Cardinal Health with a short position of Custom Truck. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cardinal Health and Custom Truck.
Diversification Opportunities for Cardinal Health and Custom Truck
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Cardinal and Custom is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Cardinal Health and Custom Truck One in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Custom Truck One and Cardinal Health 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 Cardinal Health are associated (or correlated) with Custom Truck. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Custom Truck One has no effect on the direction of Cardinal Health i.e., Cardinal Health and Custom Truck go up and down completely randomly.
Pair Corralation between Cardinal Health and Custom Truck
Considering the 90-day investment horizon Cardinal Health is expected to generate 0.39 times more return on investment than Custom Truck. However, Cardinal Health is 2.55 times less risky than Custom Truck. It trades about 0.07 of its potential returns per unit of risk. Custom Truck One is currently generating about 0.0 per unit of risk. If you would invest 10,362 in Cardinal Health on August 29, 2024 and sell it today you would earn a total of 1,926 from holding Cardinal Health or generate 18.59% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Cardinal Health vs. Custom Truck One
Performance |
| Timeline |
| Cardinal Health |
| Custom Truck One |
Cardinal Health and Custom Truck Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cardinal Health and Custom Truck
The main advantage of trading using opposite Cardinal Health and Custom Truck positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cardinal Health position performs unexpectedly, Custom Truck 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 Custom Truck will offset losses from the drop in Custom Truck's long position.| Cardinal Health vs. Henry Schein | Cardinal Health vs. Owens Minor | Cardinal Health vs. Patterson Companies | Cardinal Health vs. McKesson |
| Custom Truck vs. PROG Holdings | Custom Truck vs. McGrath RentCorp | Custom Truck vs. HE Equipment Services | Custom Truck vs. GATX Corporation |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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