Correlation Between Cannabis Suisse and Maple Leaf
Can any of the company-specific risk be diversified away by investing in both Cannabis Suisse and Maple Leaf 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 Cannabis Suisse and Maple Leaf into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cannabis Suisse Corp and Maple Leaf Green, you can compare the effects of market volatilities on Cannabis Suisse and Maple Leaf 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 Cannabis Suisse with a short position of Maple Leaf. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cannabis Suisse and Maple Leaf.
Diversification Opportunities for Cannabis Suisse and Maple Leaf
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Cannabis and Maple is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Cannabis Suisse Corp and Maple Leaf Green in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Maple Leaf Green and Cannabis Suisse 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 Cannabis Suisse Corp are associated (or correlated) with Maple Leaf. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Maple Leaf Green has no effect on the direction of Cannabis Suisse i.e., Cannabis Suisse and Maple Leaf go up and down completely randomly.
Pair Corralation between Cannabis Suisse and Maple Leaf
Given the investment horizon of 90 days Cannabis Suisse Corp is expected to generate 3.67 times more return on investment than Maple Leaf. However, Cannabis Suisse is 3.67 times more volatile than Maple Leaf Green. It trades about 0.15 of its potential returns per unit of risk. Maple Leaf Green is currently generating about 0.01 per unit of risk. If you would invest 1.90 in Cannabis Suisse Corp on December 1, 2024 and sell it today you would lose (0.20) from holding Cannabis Suisse Corp or give up 10.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 95.24% |
Values | Daily Returns |
Cannabis Suisse Corp vs. Maple Leaf Green
Performance |
Timeline |
Cannabis Suisse Corp |
Maple Leaf Green |
Cannabis Suisse and Maple Leaf Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cannabis Suisse and Maple Leaf
The main advantage of trading using opposite Cannabis Suisse and Maple Leaf positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cannabis Suisse position performs unexpectedly, Maple Leaf 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 Maple Leaf will offset losses from the drop in Maple Leaf's long position.Cannabis Suisse vs. Greater Cannabis | Cannabis Suisse vs. Global Hemp Group | Cannabis Suisse vs. Maple Leaf Green | Cannabis Suisse vs. Mc Endvrs |
Maple Leaf vs. Greater Cannabis | Maple Leaf vs. Global Hemp Group | Maple Leaf vs. Cannabis Suisse Corp | Maple Leaf vs. Mc Endvrs |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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