Correlation Between Pembina Pipeline and Imperial Metals
Can any of the company-specific risk be diversified away by investing in both Pembina Pipeline and Imperial Metals 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 Pembina Pipeline and Imperial Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Pembina Pipeline Corp and Imperial Metals, you can compare the effects of market volatilities on Pembina Pipeline and Imperial Metals 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 Pembina Pipeline with a short position of Imperial Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Pembina Pipeline and Imperial Metals.
Diversification Opportunities for Pembina Pipeline and Imperial Metals
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Pembina and Imperial is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding Pembina Pipeline Corp and Imperial Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Imperial Metals and Pembina Pipeline 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 Pembina Pipeline Corp are associated (or correlated) with Imperial Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Imperial Metals has no effect on the direction of Pembina Pipeline i.e., Pembina Pipeline and Imperial Metals go up and down completely randomly.
Pair Corralation between Pembina Pipeline and Imperial Metals
Assuming the 90 days trading horizon Pembina Pipeline Corp is expected to generate 0.29 times more return on investment than Imperial Metals. However, Pembina Pipeline Corp is 3.43 times less risky than Imperial Metals. It trades about 0.09 of its potential returns per unit of risk. Imperial Metals is currently generating about 0.01 per unit of risk. If you would invest 1,641 in Pembina Pipeline Corp on October 6, 2024 and sell it today you would earn a total of 684.00 from holding Pembina Pipeline Corp or generate 41.68% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Pembina Pipeline Corp vs. Imperial Metals
Performance |
Timeline |
Pembina Pipeline Corp |
Imperial Metals |
Pembina Pipeline and Imperial Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Pembina Pipeline and Imperial Metals
The main advantage of trading using opposite Pembina Pipeline and Imperial Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Pembina Pipeline position performs unexpectedly, Imperial Metals 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 Imperial Metals will offset losses from the drop in Imperial Metals' long position.Pembina Pipeline vs. Enbridge Pref 5 | Pembina Pipeline vs. Enbridge Pref 11 | Pembina Pipeline vs. E Split Corp | Pembina Pipeline vs. E Split 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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