Correlation Between Sun Summit and Amarc Resources
Can any of the company-specific risk be diversified away by investing in both Sun Summit and Amarc Resources 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 Sun Summit and Amarc Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sun Summit Minerals and Amarc Resources, you can compare the effects of market volatilities on Sun Summit and Amarc Resources 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 Sun Summit with a short position of Amarc Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sun Summit and Amarc Resources.
Diversification Opportunities for Sun Summit and Amarc Resources
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Sun and Amarc is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Sun Summit Minerals and Amarc Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Amarc Resources and Sun Summit 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 Sun Summit Minerals are associated (or correlated) with Amarc Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Amarc Resources has no effect on the direction of Sun Summit i.e., Sun Summit and Amarc Resources go up and down completely randomly.
Pair Corralation between Sun Summit and Amarc Resources
Assuming the 90 days horizon Sun Summit Minerals is expected to generate 1.94 times more return on investment than Amarc Resources. However, Sun Summit is 1.94 times more volatile than Amarc Resources. It trades about 0.11 of its potential returns per unit of risk. Amarc Resources is currently generating about 0.11 per unit of risk. If you would invest 4.75 in Sun Summit Minerals on May 6, 2025 and sell it today you would earn a total of 2.02 from holding Sun Summit Minerals or generate 42.53% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Sun Summit Minerals vs. Amarc Resources
Performance |
Timeline |
Sun Summit Minerals |
Amarc Resources |
Sun Summit and Amarc Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sun Summit and Amarc Resources
The main advantage of trading using opposite Sun Summit and Amarc Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sun Summit position performs unexpectedly, Amarc Resources 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 Amarc Resources will offset losses from the drop in Amarc Resources' long position.Sun Summit vs. Durango Resources | Sun Summit vs. Avarone Metals | Sun Summit vs. Amarc Resources | Sun Summit vs. Pampa Metals |
Amarc Resources vs. Durango Resources | Amarc Resources vs. Avarone Metals | Amarc Resources vs. Pampa Metals | Amarc Resources vs. Sun Summit Minerals |
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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