Correlation Between Automatic Data and Datagroup
Can any of the company-specific risk be diversified away by investing in both Automatic Data and Datagroup 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 Automatic Data and Datagroup into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Automatic Data Processing and Datagroup SE, you can compare the effects of market volatilities on Automatic Data and Datagroup 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 Automatic Data with a short position of Datagroup. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automatic Data and Datagroup.
Diversification Opportunities for Automatic Data and Datagroup
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Automatic and Datagroup is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding Automatic Data Processing and Datagroup SE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Datagroup SE and Automatic Data 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 Automatic Data Processing are associated (or correlated) with Datagroup. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Datagroup SE has no effect on the direction of Automatic Data i.e., Automatic Data and Datagroup go up and down completely randomly.
Pair Corralation between Automatic Data and Datagroup
Assuming the 90 days trading horizon Automatic Data is expected to generate 1.33 times less return on investment than Datagroup. But when comparing it to its historical volatility, Automatic Data Processing is 2.61 times less risky than Datagroup. It trades about 0.24 of its potential returns per unit of risk. Datagroup SE is currently generating about 0.12 of returns per unit of risk over similar time horizon. If you would invest 4,210 in Datagroup SE on September 2, 2024 and sell it today you would earn a total of 335.00 from holding Datagroup SE or generate 7.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Automatic Data Processing vs. Datagroup SE
Performance |
Timeline |
Automatic Data Processing |
Datagroup SE |
Automatic Data and Datagroup Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Automatic Data and Datagroup
The main advantage of trading using opposite Automatic Data and Datagroup positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automatic Data position performs unexpectedly, Datagroup 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 Datagroup will offset losses from the drop in Datagroup's long position.Automatic Data vs. National Beverage Corp | Automatic Data vs. Infrastrutture Wireless Italiane | Automatic Data vs. Broadcom | Automatic Data vs. Gaztransport et Technigaz |
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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 Positions Ratings module to determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance.
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