Correlation Between CV Sciences and CanSino Biologics
Can any of the company-specific risk be diversified away by investing in both CV Sciences and CanSino Biologics 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 CV Sciences and CanSino Biologics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CV Sciences and CanSino Biologics, you can compare the effects of market volatilities on CV Sciences and CanSino Biologics 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 CV Sciences with a short position of CanSino Biologics. Check out your portfolio center. Please also check ongoing floating volatility patterns of CV Sciences and CanSino Biologics.
Diversification Opportunities for CV Sciences and CanSino Biologics
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between CVSI and CanSino is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding CV Sciences and CanSino Biologics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CanSino Biologics and CV Sciences 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 CV Sciences are associated (or correlated) with CanSino Biologics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CanSino Biologics has no effect on the direction of CV Sciences i.e., CV Sciences and CanSino Biologics go up and down completely randomly.
Pair Corralation between CV Sciences and CanSino Biologics
Given the investment horizon of 90 days CV Sciences is expected to under-perform the CanSino Biologics. In addition to that, CV Sciences is 4.73 times more volatile than CanSino Biologics. It trades about -0.03 of its total potential returns per unit of risk. CanSino Biologics is currently generating about 0.21 per unit of volatility. If you would invest 351.00 in CanSino Biologics on August 24, 2024 and sell it today you would earn a total of 39.00 from holding CanSino Biologics or generate 11.11% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
CV Sciences vs. CanSino Biologics
Performance |
| Timeline |
| CV Sciences |
| CanSino Biologics |
CV Sciences and CanSino Biologics Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CV Sciences and CanSino Biologics
The main advantage of trading using opposite CV Sciences and CanSino Biologics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CV Sciences position performs unexpectedly, CanSino Biologics 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 CanSino Biologics will offset losses from the drop in CanSino Biologics' long position.| CV Sciences vs. Marimed | CV Sciences vs. General Cannabis Corp | CV Sciences vs. American Cannabis | CV Sciences vs. Cannabis Sativa |
| CanSino Biologics vs. Holloman Energy Corp | CanSino Biologics vs. cbdMD Inc | CanSino Biologics vs. Evolus Inc | CanSino Biologics vs. CV Sciences |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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