Correlation Between Dividend Growth and Canoe EIT
Can any of the company-specific risk be diversified away by investing in both Dividend Growth and Canoe EIT 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 Dividend Growth and Canoe EIT into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dividend Growth Split and Canoe EIT Income, you can compare the effects of market volatilities on Dividend Growth and Canoe EIT 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 Dividend Growth with a short position of Canoe EIT. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dividend Growth and Canoe EIT.
Diversification Opportunities for Dividend Growth and Canoe EIT
0.93 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Dividend and Canoe is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding Dividend Growth Split and Canoe EIT Income in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Canoe EIT Income and Dividend Growth 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 Dividend Growth Split are associated (or correlated) with Canoe EIT. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Canoe EIT Income has no effect on the direction of Dividend Growth i.e., Dividend Growth and Canoe EIT go up and down completely randomly.
Pair Corralation between Dividend Growth and Canoe EIT
Assuming the 90 days trading horizon Dividend Growth Split is expected to under-perform the Canoe EIT. In addition to that, Dividend Growth is 1.82 times more volatile than Canoe EIT Income. It trades about -0.19 of its total potential returns per unit of risk. Canoe EIT Income is currently generating about -0.26 per unit of volatility. If you would invest 1,557 in Canoe EIT Income on October 4, 2024 and sell it today you would lose (38.00) from holding Canoe EIT Income or give up 2.44% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Dividend Growth Split vs. Canoe EIT Income
Performance |
Timeline |
Dividend Growth Split |
Canoe EIT Income |
Dividend Growth and Canoe EIT Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dividend Growth and Canoe EIT
The main advantage of trading using opposite Dividend Growth and Canoe EIT positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dividend Growth position performs unexpectedly, Canoe EIT 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 Canoe EIT will offset losses from the drop in Canoe EIT's long position.Dividend Growth vs. Life Banc Split | Dividend Growth vs. North American Financial | Dividend Growth vs. Financial 15 Split | Dividend Growth vs. Dividend 15 Split |
Canoe EIT vs. Dividend 15 Split | Canoe EIT vs. E Split Corp | Canoe EIT vs. Global Dividend Growth | Canoe EIT vs. Dividend Growth Split |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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