Correlation Between Willamette Valley and Canopy Growth
Can any of the company-specific risk be diversified away by investing in both Willamette Valley and Canopy Growth 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 Willamette Valley and Canopy Growth into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Willamette Valley Vineyards and Canopy Growth Corp, you can compare the effects of market volatilities on Willamette Valley and Canopy Growth 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 Willamette Valley with a short position of Canopy Growth. Check out your portfolio center. Please also check ongoing floating volatility patterns of Willamette Valley and Canopy Growth.
Diversification Opportunities for Willamette Valley and Canopy Growth
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Willamette and Canopy is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Willamette Valley Vineyards and Canopy Growth Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Canopy Growth Corp and Willamette Valley 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 Willamette Valley Vineyards are associated (or correlated) with Canopy Growth. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Canopy Growth Corp has no effect on the direction of Willamette Valley i.e., Willamette Valley and Canopy Growth go up and down completely randomly.
Pair Corralation between Willamette Valley and Canopy Growth
Given the investment horizon of 90 days Willamette Valley Vineyards is expected to generate 0.5 times more return on investment than Canopy Growth. However, Willamette Valley Vineyards is 2.01 times less risky than Canopy Growth. It trades about 0.12 of its potential returns per unit of risk. Canopy Growth Corp is currently generating about -0.57 per unit of risk. If you would invest 331.00 in Willamette Valley Vineyards on September 25, 2024 and sell it today you would earn a total of 13.00 from holding Willamette Valley Vineyards or generate 3.93% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Willamette Valley Vineyards vs. Canopy Growth Corp
Performance |
Timeline |
Willamette Valley |
Canopy Growth Corp |
Willamette Valley and Canopy Growth Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Willamette Valley and Canopy Growth
The main advantage of trading using opposite Willamette Valley and Canopy Growth positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Willamette Valley position performs unexpectedly, Canopy Growth 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 Canopy Growth will offset losses from the drop in Canopy Growth's long position.Willamette Valley vs. Brown Forman | Willamette Valley vs. MGP Ingredients | Willamette Valley vs. Brown Forman | Willamette Valley vs. Constellation Brands Class |
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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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