Correlation Between CATLIN GROUP and Cardinal Health
Can any of the company-specific risk be diversified away by investing in both CATLIN GROUP and Cardinal Health 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 CATLIN GROUP and Cardinal Health into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CATLIN GROUP and Cardinal Health, you can compare the effects of market volatilities on CATLIN GROUP and Cardinal Health 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 CATLIN GROUP with a short position of Cardinal Health. Check out your portfolio center. Please also check ongoing floating volatility patterns of CATLIN GROUP and Cardinal Health.
Diversification Opportunities for CATLIN GROUP and Cardinal Health
-0.61 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between CATLIN and Cardinal is -0.61. Overlapping area represents the amount of risk that can be diversified away by holding CATLIN GROUP and Cardinal Health in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cardinal Health and CATLIN GROUP 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 CATLIN GROUP are associated (or correlated) with Cardinal Health. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cardinal Health has no effect on the direction of CATLIN GROUP i.e., CATLIN GROUP and Cardinal Health go up and down completely randomly.
Pair Corralation between CATLIN GROUP and Cardinal Health
Assuming the 90 days trading horizon CATLIN GROUP is expected to generate 1.04 times less return on investment than Cardinal Health. In addition to that, CATLIN GROUP is 1.5 times more volatile than Cardinal Health. It trades about 0.07 of its total potential returns per unit of risk. Cardinal Health is currently generating about 0.11 per unit of volatility. If you would invest 9,886 in Cardinal Health on September 3, 2024 and sell it today you would earn a total of 2,349 from holding Cardinal Health or generate 23.76% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 98.67% |
| Values | Daily Returns |
CATLIN GROUP vs. Cardinal Health
Performance |
| Timeline |
| CATLIN GROUP |
| Cardinal Health |
CATLIN GROUP and Cardinal Health Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CATLIN GROUP and Cardinal Health
The main advantage of trading using opposite CATLIN GROUP and Cardinal Health positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CATLIN GROUP position performs unexpectedly, Cardinal Health 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 Cardinal Health will offset losses from the drop in Cardinal Health's long position.| CATLIN GROUP vs. Molson Coors Beverage | CATLIN GROUP vs. Flowtech Fluidpower plc | CATLIN GROUP vs. CleanTech Lithium plc | CATLIN GROUP vs. Monster Beverage Corp |
| Cardinal Health vs. Catalyst Media Group | Cardinal Health vs. CATLIN GROUP | Cardinal Health vs. Magnora ASA | Cardinal Health vs. RTW Venture Fund |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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