Correlation Between Canna Consumer and AMC Networks
Can any of the company-specific risk be diversified away by investing in both Canna Consumer and AMC Networks 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 Canna Consumer and AMC Networks into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Canna Consumer Goods and AMC Networks, you can compare the effects of market volatilities on Canna Consumer and AMC Networks 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 Canna Consumer with a short position of AMC Networks. Check out your portfolio center. Please also check ongoing floating volatility patterns of Canna Consumer and AMC Networks.
Diversification Opportunities for Canna Consumer and AMC Networks
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Canna and AMC is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Canna Consumer Goods and AMC Networks in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AMC Networks and Canna Consumer 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 Canna Consumer Goods are associated (or correlated) with AMC Networks. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AMC Networks has no effect on the direction of Canna Consumer i.e., Canna Consumer and AMC Networks go up and down completely randomly.
Pair Corralation between Canna Consumer and AMC Networks
Given the investment horizon of 90 days Canna Consumer Goods is expected to generate 4.92 times more return on investment than AMC Networks. However, Canna Consumer is 4.92 times more volatile than AMC Networks. It trades about 0.13 of its potential returns per unit of risk. AMC Networks is currently generating about 0.13 per unit of risk. If you would invest 2.40 in Canna Consumer Goods on July 17, 2025 and sell it today you would earn a total of 2.13 from holding Canna Consumer Goods or generate 88.75% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Canna Consumer Goods vs. AMC Networks
Performance |
| Timeline |
| Canna Consumer Goods |
| AMC Networks |
Canna Consumer and AMC Networks Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Canna Consumer and AMC Networks
The main advantage of trading using opposite Canna Consumer and AMC Networks positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Canna Consumer position performs unexpectedly, AMC Networks 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 AMC Networks will offset losses from the drop in AMC Networks' long position.| Canna Consumer vs. Elvictor Group | Canna Consumer vs. Frontera Group | Canna Consumer vs. Bryn Resources | Canna Consumer vs. Team Inc |
| AMC Networks vs. National Beverage Corp | AMC Networks vs. Fox Corp Class | AMC Networks vs. Liberty Media | AMC Networks vs. Nexstar Broadcasting Group |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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