Correlation Between Automatic Data and Hirequest
Can any of the company-specific risk be diversified away by investing in both Automatic Data and Hirequest 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 Hirequest 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 Hirequest, you can compare the effects of market volatilities on Automatic Data and Hirequest 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 Hirequest. Check out your portfolio center. Please also check ongoing floating volatility patterns of Automatic Data and Hirequest.
Diversification Opportunities for Automatic Data and Hirequest
0.1 | Correlation Coefficient |
Average diversification
The 3 months correlation between Automatic and Hirequest is 0.1. Overlapping area represents the amount of risk that can be diversified away by holding Automatic Data Processing and Hirequest in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hirequest 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 Hirequest. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hirequest has no effect on the direction of Automatic Data i.e., Automatic Data and Hirequest go up and down completely randomly.
Pair Corralation between Automatic Data and Hirequest
Considering the 90-day investment horizon Automatic Data Processing is expected to generate 0.45 times more return on investment than Hirequest. However, Automatic Data Processing is 2.24 times less risky than Hirequest. It trades about -0.05 of its potential returns per unit of risk. Hirequest is currently generating about -0.08 per unit of risk. If you would invest 25,209 in Automatic Data Processing on January 25, 2024 and sell it today you would lose (525.00) from holding Automatic Data Processing or give up 2.08% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Automatic Data Processing vs. Hirequest
Performance |
| Timeline |
| Automatic Data Processing |
| Hirequest |
Automatic Data and Hirequest Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Automatic Data and Hirequest
The main advantage of trading using opposite Automatic Data and Hirequest positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Automatic Data position performs unexpectedly, Hirequest 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 Hirequest will offset losses from the drop in Hirequest's long position.| Automatic Data vs. Robert Half International | Automatic Data vs. Barrett Business Services | Automatic Data vs. ManpowerGroup | Automatic Data vs. Kforce Inc |
| Hirequest vs. Kforce Inc | Hirequest vs. Heidrick Struggles International | Hirequest vs. Hudson Global | Hirequest vs. Kelly Services A |
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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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