Correlation Between Highpeak Energy and SM Energy
Can any of the company-specific risk be diversified away by investing in both Highpeak Energy 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 Highpeak Energy and SM Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Highpeak Energy Acquisition and SM Energy Co, you can compare the effects of market volatilities on Highpeak Energy 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 Highpeak Energy with a short position of SM Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Highpeak Energy and SM Energy.
Diversification Opportunities for Highpeak Energy and SM Energy
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Highpeak and SM Energy is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Highpeak Energy Acquisition and SM Energy Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SM Energy and Highpeak Energy 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 Highpeak Energy Acquisition 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 Highpeak Energy i.e., Highpeak Energy and SM Energy go up and down completely randomly.
Pair Corralation between Highpeak Energy and SM Energy
Considering the 90-day investment horizon Highpeak Energy Acquisition is expected to generate 1.4 times more return on investment than SM Energy. However, Highpeak Energy is 1.4 times more volatile than SM Energy Co. It trades about 0.19 of its potential returns per unit of risk. SM Energy Co is currently generating about 0.12 per unit of risk. If you would invest 1,312 in Highpeak Energy Acquisition on August 31, 2024 and sell it today you would earn a total of 174.00 from holding Highpeak Energy Acquisition or generate 13.26% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Highpeak Energy Acquisition vs. SM Energy Co
Performance |
| Timeline |
| Highpeak Energy Acqu |
| SM Energy |
Highpeak Energy and SM Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Highpeak Energy and SM Energy
The main advantage of trading using opposite Highpeak Energy and SM Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Highpeak Energy 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.| Highpeak Energy vs. Vital Energy | Highpeak Energy vs. Permian Resources | Highpeak Energy vs. Magnolia Oil Gas | Highpeak Energy vs. Ring Energy |
| 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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