Correlation Between CopperCorp Resources and Imperial Metals
Can any of the company-specific risk be diversified away by investing in both CopperCorp Resources 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 CopperCorp Resources and Imperial Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CopperCorp Resources and Imperial Metals, you can compare the effects of market volatilities on CopperCorp Resources 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 CopperCorp Resources with a short position of Imperial Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of CopperCorp Resources and Imperial Metals.
Diversification Opportunities for CopperCorp Resources and Imperial Metals
-0.66 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between CopperCorp and Imperial is -0.66. Overlapping area represents the amount of risk that can be diversified away by holding CopperCorp Resources and Imperial Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Imperial Metals and CopperCorp Resources 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 CopperCorp Resources 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 CopperCorp Resources i.e., CopperCorp Resources and Imperial Metals go up and down completely randomly.
Pair Corralation between CopperCorp Resources and Imperial Metals
Assuming the 90 days horizon CopperCorp Resources is expected to generate 5.66 times more return on investment than Imperial Metals. However, CopperCorp Resources is 5.66 times more volatile than Imperial Metals. It trades about 0.06 of its potential returns per unit of risk. Imperial Metals is currently generating about 0.02 per unit of risk. If you would invest 12.00 in CopperCorp Resources on September 20, 2024 and sell it today you would earn a total of 3.00 from holding CopperCorp Resources or generate 25.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
CopperCorp Resources vs. Imperial Metals
Performance |
Timeline |
CopperCorp Resources |
Imperial Metals |
CopperCorp Resources and Imperial Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CopperCorp Resources and Imperial Metals
The main advantage of trading using opposite CopperCorp Resources and Imperial Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CopperCorp Resources 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.CopperCorp Resources vs. Copper Fox Metals | CopperCorp Resources vs. Imperial Metals | CopperCorp Resources vs. Bell Copper | CopperCorp Resources vs. Arizona Sonoran Copper |
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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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