Correlation Between SSR Mining and Atlas Engineered
Can any of the company-specific risk be diversified away by investing in both SSR Mining and Atlas Engineered 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 SSR Mining and Atlas Engineered into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SSR Mining and Atlas Engineered Products, you can compare the effects of market volatilities on SSR Mining and Atlas Engineered 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 SSR Mining with a short position of Atlas Engineered. Check out your portfolio center. Please also check ongoing floating volatility patterns of SSR Mining and Atlas Engineered.
Diversification Opportunities for SSR Mining and Atlas Engineered
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between SSR and Atlas is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding SSR Mining and Atlas Engineered Products in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Atlas Engineered Products and SSR Mining 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 SSR Mining are associated (or correlated) with Atlas Engineered. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Atlas Engineered Products has no effect on the direction of SSR Mining i.e., SSR Mining and Atlas Engineered go up and down completely randomly.
Pair Corralation between SSR Mining and Atlas Engineered
Assuming the 90 days trading horizon SSR Mining is expected to generate 0.99 times more return on investment than Atlas Engineered. However, SSR Mining is 1.01 times less risky than Atlas Engineered. It trades about 0.12 of its potential returns per unit of risk. Atlas Engineered Products is currently generating about 0.04 per unit of risk. If you would invest 1,403 in SSR Mining on April 23, 2025 and sell it today you would earn a total of 306.00 from holding SSR Mining or generate 21.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.41% |
Values | Daily Returns |
SSR Mining vs. Atlas Engineered Products
Performance |
Timeline |
SSR Mining |
Atlas Engineered Products |
SSR Mining and Atlas Engineered Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SSR Mining and Atlas Engineered
The main advantage of trading using opposite SSR Mining and Atlas Engineered positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SSR Mining position performs unexpectedly, Atlas Engineered 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 Atlas Engineered will offset losses from the drop in Atlas Engineered's long position.SSR Mining vs. Pan American Silver | SSR Mining vs. MAG Silver Corp | SSR Mining vs. Osisko Gold Ro | SSR Mining vs. Sandstorm Gold Ltd |
Atlas Engineered vs. Atlas Engineered Products | Atlas Engineered vs. Masco | Atlas Engineered vs. Fab Form Industries | Atlas Engineered vs. Inventronics |
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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