Correlation Between Automatic Data and LION ONE
Can any of the company-specific risk be diversified away by investing in both Automatic Data and LION ONE 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 LION ONE 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 LION ONE METALS, you can compare the effects of market volatilities on Automatic Data and LION ONE 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 LION ONE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automatic Data and LION ONE.
Diversification Opportunities for Automatic Data and LION ONE
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Automatic and LION is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Automatic Data Processing and LION ONE METALS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LION ONE METALS 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 LION ONE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LION ONE METALS has no effect on the direction of Automatic Data i.e., Automatic Data and LION ONE go up and down completely randomly.
Pair Corralation between Automatic Data and LION ONE
Assuming the 90 days horizon Automatic Data Processing is expected to generate 0.34 times more return on investment than LION ONE. However, Automatic Data Processing is 2.94 times less risky than LION ONE. It trades about 0.38 of its potential returns per unit of risk. LION ONE METALS is currently generating about -0.05 per unit of risk. If you would invest 26,550 in Automatic Data Processing on September 2, 2024 and sell it today you would earn a total of 2,560 from holding Automatic Data Processing or generate 9.64% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Automatic Data Processing vs. LION ONE METALS
Performance |
| Timeline |
| Automatic Data Processing |
| LION ONE METALS |
Automatic Data and LION ONE Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Automatic Data and LION ONE
The main advantage of trading using opposite Automatic Data and LION ONE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automatic Data position performs unexpectedly, LION ONE 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 LION ONE will offset losses from the drop in LION ONE's long position.| Automatic Data vs. Superior Plus Corp | Automatic Data vs. NMI Holdings | Automatic Data vs. Origin Agritech | Automatic Data vs. SIVERS SEMICONDUCTORS AB |
| LION ONE vs. Public Storage | LION ONE vs. NTG Nordic Transport | LION ONE vs. Automatic Data Processing | LION ONE vs. Fidelity National Information |
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 ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.
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