Correlation Between Ultra Clean and Automatic Data
Can any of the company-specific risk be diversified away by investing in both Ultra Clean and Automatic Data 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 Ultra Clean and Automatic Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ultra Clean Holdings and Automatic Data Processing, you can compare the effects of market volatilities on Ultra Clean and Automatic Data 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 Ultra Clean with a short position of Automatic Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ultra Clean and Automatic Data.
Diversification Opportunities for Ultra Clean and Automatic Data
-0.81 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Ultra and Automatic is -0.81. Overlapping area represents the amount of risk that can be diversified away by holding Ultra Clean Holdings and Automatic Data Processing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Automatic Data Processing and Ultra Clean 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 Ultra Clean Holdings are associated (or correlated) with Automatic Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Automatic Data Processing has no effect on the direction of Ultra Clean i.e., Ultra Clean and Automatic Data go up and down completely randomly.
Pair Corralation between Ultra Clean and Automatic Data
Assuming the 90 days horizon Ultra Clean Holdings is expected to generate 2.29 times more return on investment than Automatic Data. However, Ultra Clean is 2.29 times more volatile than Automatic Data Processing. It trades about 0.21 of its potential returns per unit of risk. Automatic Data Processing is currently generating about 0.38 per unit of risk. If you would invest 3,120 in Ultra Clean Holdings on September 2, 2024 and sell it today you would earn a total of 380.00 from holding Ultra Clean Holdings or generate 12.18% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ultra Clean Holdings vs. Automatic Data Processing
Performance |
| Timeline |
| Ultra Clean Holdings |
| Automatic Data Processing |
Ultra Clean and Automatic Data Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ultra Clean and Automatic Data
The main advantage of trading using opposite Ultra Clean and Automatic Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ultra Clean position performs unexpectedly, Automatic Data 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 Automatic Data will offset losses from the drop in Automatic Data's long position.| Ultra Clean vs. SENECA FOODS A | Ultra Clean vs. OURGAME INTHOLDL 00005 | Ultra Clean vs. AUSNUTRIA DAIRY | Ultra Clean vs. QINGCI GAMES INC |
| Automatic Data vs. Superior Plus Corp | Automatic Data vs. NMI Holdings | Automatic Data vs. Origin Agritech | Automatic Data vs. SIVERS SEMICONDUCTORS AB |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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