Correlation Between Automatic Data and SUN LIFE
Can any of the company-specific risk be diversified away by investing in both Automatic Data and SUN LIFE 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 SUN LIFE 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 SUN LIFE FINANCIAL, you can compare the effects of market volatilities on Automatic Data and SUN LIFE 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 SUN LIFE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automatic Data and SUN LIFE.
Diversification Opportunities for Automatic Data and SUN LIFE
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Automatic and SUN is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding Automatic Data Processing and SUN LIFE FINANCIAL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SUN LIFE FINANCIAL 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 SUN LIFE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SUN LIFE FINANCIAL has no effect on the direction of Automatic Data i.e., Automatic Data and SUN LIFE go up and down completely randomly.
Pair Corralation between Automatic Data and SUN LIFE
Assuming the 90 days horizon Automatic Data Processing is expected to generate 1.35 times more return on investment than SUN LIFE. However, Automatic Data is 1.35 times more volatile than SUN LIFE FINANCIAL. It trades about 0.01 of its potential returns per unit of risk. SUN LIFE FINANCIAL is currently generating about -0.1 per unit of risk. If you would invest 28,340 in Automatic Data Processing on October 26, 2024 and sell it today you would earn a total of 10.00 from holding Automatic Data Processing or generate 0.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Automatic Data Processing vs. SUN LIFE FINANCIAL
Performance |
| Timeline |
| Automatic Data Processing |
| SUN LIFE FINANCIAL |
Automatic Data and SUN LIFE Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Automatic Data and SUN LIFE
The main advantage of trading using opposite Automatic Data and SUN LIFE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automatic Data position performs unexpectedly, SUN LIFE 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 SUN LIFE will offset losses from the drop in SUN LIFE's long position.| Automatic Data vs. AGNC INVESTMENT | Automatic Data vs. REINET INVESTMENTS SCA | Automatic Data vs. Datadog | Automatic Data vs. MICRONIC MYDATA |
| SUN LIFE vs. ANTA SPORTS PRODUCT | SUN LIFE vs. DALATA HOTEL | SUN LIFE vs. PENN Entertainment | SUN LIFE vs. RCS MediaGroup SpA |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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