Correlation Between X FAB and CVS Health
Can any of the company-specific risk be diversified away by investing in both X FAB and CVS Health 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 X FAB and CVS Health into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between X FAB Silicon Foundries and CVS Health, you can compare the effects of market volatilities on X FAB and CVS Health 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 X FAB with a short position of CVS Health. Check out your portfolio center. Please also check ongoing floating volatility patterns of X FAB and CVS Health.
Diversification Opportunities for X FAB and CVS Health
0.37 | Correlation Coefficient |
Weak diversification
The 3 months correlation between XFB and CVS is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding X FAB Silicon Foundries and CVS Health in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CVS Health and X FAB 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 X FAB Silicon Foundries are associated (or correlated) with CVS Health. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CVS Health has no effect on the direction of X FAB i.e., X FAB and CVS Health go up and down completely randomly.
Pair Corralation between X FAB and CVS Health
Assuming the 90 days trading horizon X FAB Silicon Foundries is expected to generate 1.55 times more return on investment than CVS Health. However, X FAB is 1.55 times more volatile than CVS Health. It trades about 0.13 of its potential returns per unit of risk. CVS Health is currently generating about 0.02 per unit of risk. If you would invest 462.00 in X FAB Silicon Foundries on September 12, 2024 and sell it today you would earn a total of 39.00 from holding X FAB Silicon Foundries or generate 8.44% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 95.65% |
| Values | Daily Returns |
X FAB Silicon Foundries vs. CVS Health
Performance |
| Timeline |
| X FAB Silicon |
| CVS Health |
X FAB and CVS Health Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with X FAB and CVS Health
The main advantage of trading using opposite X FAB and CVS Health positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if X FAB position performs unexpectedly, CVS Health 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 CVS Health will offset losses from the drop in CVS Health's long position.The idea behind X FAB Silicon Foundries and CVS Health pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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