Correlation Between Emera Pref and Gfl Environmental
Can any of the company-specific risk be diversified away by investing in both Emera Pref and Gfl Environmental 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 Emera Pref and Gfl Environmental into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Emera Pref A and Gfl Environmental Holdings, you can compare the effects of market volatilities on Emera Pref and Gfl Environmental 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 Emera Pref with a short position of Gfl Environmental. Check out your portfolio center. Please also check ongoing floating volatility patterns of Emera Pref and Gfl Environmental.
Diversification Opportunities for Emera Pref and Gfl Environmental
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Emera and Gfl is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Emera Pref A and Gfl Environmental Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Gfl Environmental and Emera Pref 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 Emera Pref A are associated (or correlated) with Gfl Environmental. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Gfl Environmental has no effect on the direction of Emera Pref i.e., Emera Pref and Gfl Environmental go up and down completely randomly.
Pair Corralation between Emera Pref and Gfl Environmental
Assuming the 90 days trading horizon Emera Pref is expected to generate 2.09 times less return on investment than Gfl Environmental. But when comparing it to its historical volatility, Emera Pref A is 1.64 times less risky than Gfl Environmental. It trades about 0.05 of its potential returns per unit of risk. Gfl Environmental Holdings is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 4,084 in Gfl Environmental Holdings on September 25, 2024 and sell it today you would earn a total of 2,341 from holding Gfl Environmental Holdings or generate 57.32% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Emera Pref A vs. Gfl Environmental Holdings
Performance |
Timeline |
Emera Pref A |
Gfl Environmental |
Emera Pref and Gfl Environmental Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Emera Pref and Gfl Environmental
The main advantage of trading using opposite Emera Pref and Gfl Environmental positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Emera Pref position performs unexpectedly, Gfl Environmental 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 Gfl Environmental will offset losses from the drop in Gfl Environmental's long position.Emera Pref vs. Gfl Environmental Holdings | Emera Pref vs. Constellation Software | Emera Pref vs. Summa Silver Corp | Emera Pref vs. Millennium Silver Corp |
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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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