Correlation Between RadNet and Abercrombie Fitch
Can any of the company-specific risk be diversified away by investing in both RadNet and Abercrombie Fitch 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 RadNet and Abercrombie Fitch into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between RadNet Inc and Abercrombie Fitch, you can compare the effects of market volatilities on RadNet and Abercrombie Fitch 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 RadNet with a short position of Abercrombie Fitch. Check out your portfolio center. Please also check ongoing floating volatility patterns of RadNet and Abercrombie Fitch.
Diversification Opportunities for RadNet and Abercrombie Fitch
0.36 | Correlation Coefficient |
Weak diversification
The 3 months correlation between RadNet and Abercrombie is 0.36. Overlapping area represents the amount of risk that can be diversified away by holding RadNet Inc and Abercrombie Fitch in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Abercrombie Fitch and RadNet 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 RadNet Inc are associated (or correlated) with Abercrombie Fitch. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Abercrombie Fitch has no effect on the direction of RadNet i.e., RadNet and Abercrombie Fitch go up and down completely randomly.
Pair Corralation between RadNet and Abercrombie Fitch
Given the investment horizon of 90 days RadNet is expected to generate 1.34 times less return on investment than Abercrombie Fitch. But when comparing it to its historical volatility, RadNet Inc is 1.41 times less risky than Abercrombie Fitch. It trades about 0.1 of its potential returns per unit of risk. Abercrombie Fitch is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 3,051 in Abercrombie Fitch on October 26, 2024 and sell it today you would earn a total of 9,291 from holding Abercrombie Fitch or generate 304.52% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
RadNet Inc vs. Abercrombie Fitch
Performance |
| Timeline |
| RadNet Inc |
| Abercrombie Fitch |
RadNet and Abercrombie Fitch Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with RadNet and Abercrombie Fitch
The main advantage of trading using opposite RadNet and Abercrombie Fitch positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if RadNet position performs unexpectedly, Abercrombie Fitch 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 Abercrombie Fitch will offset losses from the drop in Abercrombie Fitch's long position.| RadNet vs. Sotera Health Co | RadNet vs. Neogen | RadNet vs. Myriad Genetics | RadNet vs. bioAffinity Technologies Warrant |
| Abercrombie Fitch vs. Urban Outfitters | Abercrombie Fitch vs. Foot Locker | Abercrombie Fitch vs. Childrens Place | Abercrombie Fitch vs. American Eagle Outfitters |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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