Correlation Between Greenfire Resources and SM Energy
Can any of the company-specific risk be diversified away by investing in both Greenfire Resources and SM Energy 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 Greenfire Resources and SM Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Greenfire Resources and SM Energy Co, you can compare the effects of market volatilities on Greenfire Resources and SM Energy 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 Greenfire Resources with a short position of SM Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Greenfire Resources and SM Energy.
Diversification Opportunities for Greenfire Resources and SM Energy
0.41 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Greenfire and SM Energy is 0.41. Overlapping area represents the amount of risk that can be diversified away by holding Greenfire Resources and SM Energy Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SM Energy and Greenfire 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 Greenfire Resources are associated (or correlated) with SM Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SM Energy has no effect on the direction of Greenfire Resources i.e., Greenfire Resources and SM Energy go up and down completely randomly.
Pair Corralation between Greenfire Resources and SM Energy
Considering the 90-day investment horizon Greenfire Resources is expected to under-perform the SM Energy. In addition to that, Greenfire Resources is 1.12 times more volatile than SM Energy Co. It trades about -0.01 of its total potential returns per unit of risk. SM Energy Co is currently generating about 0.03 per unit of volatility. If you would invest 3,432 in SM Energy Co on September 14, 2024 and sell it today you would earn a total of 606.00 from holding SM Energy Co or generate 17.66% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 99.8% |
| Values | Daily Returns |
Greenfire Resources vs. SM Energy Co
Performance |
| Timeline |
| Greenfire Resources |
| SM Energy |
Greenfire Resources and SM Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Greenfire Resources and SM Energy
The main advantage of trading using opposite Greenfire Resources and SM Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Greenfire Resources position performs unexpectedly, SM Energy 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 SM Energy will offset losses from the drop in SM Energy's long position.| Greenfire Resources vs. Evolution Petroleum | Greenfire Resources vs. Ring Energy | Greenfire Resources vs. Gran Tierra Energy | Greenfire Resources vs. Permian Resources |
| SM Energy vs. Vital Energy | SM Energy vs. Permian Resources | SM Energy vs. Matador Resources | SM Energy vs. Obsidian Energy |
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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