Correlation Between Bio-Techne Corp and CanSino Biologics
Can any of the company-specific risk be diversified away by investing in both Bio-Techne Corp 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 Bio-Techne Corp and CanSino Biologics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bio Techne Corp and CanSino Biologics, you can compare the effects of market volatilities on Bio-Techne Corp 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 Bio-Techne Corp with a short position of CanSino Biologics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bio-Techne Corp and CanSino Biologics.
Diversification Opportunities for Bio-Techne Corp and CanSino Biologics
0.23 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bio-Techne and CanSino is 0.23. Overlapping area represents the amount of risk that can be diversified away by holding Bio Techne Corp and CanSino Biologics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CanSino Biologics and Bio-Techne Corp 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 Bio Techne Corp 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 Bio-Techne Corp i.e., Bio-Techne Corp and CanSino Biologics go up and down completely randomly.
Pair Corralation between Bio-Techne Corp and CanSino Biologics
Assuming the 90 days trading horizon Bio-Techne Corp is expected to generate 5.66 times less return on investment than CanSino Biologics. But when comparing it to its historical volatility, Bio Techne Corp is 1.29 times less risky than CanSino Biologics. It trades about 0.02 of its potential returns per unit of risk. CanSino Biologics is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 346.00 in CanSino Biologics on April 24, 2025 and sell it today you would earn a total of 67.00 from holding CanSino Biologics or generate 19.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bio Techne Corp vs. CanSino Biologics
Performance |
Timeline |
Bio Techne Corp |
CanSino Biologics |
Bio-Techne Corp and CanSino Biologics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bio-Techne Corp and CanSino Biologics
The main advantage of trading using opposite Bio-Techne Corp and CanSino Biologics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bio-Techne Corp 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.Bio-Techne Corp vs. Apple Inc | Bio-Techne Corp vs. Apple Inc | Bio-Techne Corp vs. Apple Inc | Bio-Techne Corp vs. Apple Inc |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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