Correlation Between Old Dominion and Cardinal Health
Can any of the company-specific risk be diversified away by investing in both Old Dominion 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 Old Dominion and Cardinal Health into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Old Dominion Freight and Cardinal Health, you can compare the effects of market volatilities on Old Dominion 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 Old Dominion with a short position of Cardinal Health. Check out your portfolio center. Please also check ongoing floating volatility patterns of Old Dominion and Cardinal Health.
Diversification Opportunities for Old Dominion and Cardinal Health
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Old and Cardinal is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Old Dominion Freight and Cardinal Health in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cardinal Health and Old Dominion 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 Old Dominion Freight 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 Old Dominion i.e., Old Dominion and Cardinal Health go up and down completely randomly.
Pair Corralation between Old Dominion and Cardinal Health
Given the investment horizon of 90 days Old Dominion Freight is expected to under-perform the Cardinal Health. In addition to that, Old Dominion is 1.48 times more volatile than Cardinal Health. It trades about -0.04 of its total potential returns per unit of risk. Cardinal Health is currently generating about 0.06 per unit of volatility. If you would invest 11,133 in Cardinal Health on September 22, 2024 and sell it today you would earn a total of 567.00 from holding Cardinal Health or generate 5.09% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Old Dominion Freight vs. Cardinal Health
Performance |
Timeline |
Old Dominion Freight |
Cardinal Health |
Old Dominion and Cardinal Health Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Old Dominion and Cardinal Health
The main advantage of trading using opposite Old Dominion and Cardinal Health positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Old Dominion 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.Old Dominion vs. ArcBest Corp | Old Dominion vs. Marten Transport | Old Dominion vs. Werner Enterprises | Old Dominion vs. Knight Transportation |
Cardinal Health vs. ASGN Inc | Cardinal Health vs. Kforce Inc | Cardinal Health vs. Kelly Services A | Cardinal Health vs. Central Garden Pet |
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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