Correlation Between Cardinal Health and G III
Can any of the company-specific risk be diversified away by investing in both Cardinal Health and G III 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 G III into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cardinal Health and G III Apparel Group, you can compare the effects of market volatilities on Cardinal Health and G III 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 G III. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cardinal Health and G III.
Diversification Opportunities for Cardinal Health and G III
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Cardinal and GI4 is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding Cardinal Health and G III Apparel Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on G III Apparel 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 G III. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of G III Apparel has no effect on the direction of Cardinal Health i.e., Cardinal Health and G III go up and down completely randomly.
Pair Corralation between Cardinal Health and G III
Assuming the 90 days horizon Cardinal Health is expected to generate 1.04 times more return on investment than G III. However, Cardinal Health is 1.04 times more volatile than G III Apparel Group. It trades about 0.16 of its potential returns per unit of risk. G III Apparel Group is currently generating about 0.05 per unit of risk. If you would invest 11,705 in Cardinal Health on November 7, 2024 and sell it today you would earn a total of 610.00 from holding Cardinal Health or generate 5.21% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Cardinal Health vs. G III Apparel Group
Performance |
| Timeline |
| Cardinal Health |
| G III Apparel |
Cardinal Health and G III Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Cardinal Health and G III
The main advantage of trading using opposite Cardinal Health and G III positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cardinal Health position performs unexpectedly, G III 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 G III will offset losses from the drop in G III's long position.| Cardinal Health vs. AmerisourceBergen | Cardinal Health vs. Henry Schein | Cardinal Health vs. Shanghai Pharmaceuticals Holding | Cardinal Health vs. SINOPHARM GROUP 15ON |
| G III vs. ADRIATIC METALS LS 013355 | G III vs. NORTHEAST UTILITIES | G III vs. SCANSOURCE | G III vs. Air Transport Services |
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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