Correlation Between EOG Resources and Questerre Energy
Can any of the company-specific risk be diversified away by investing in both EOG Resources and Questerre 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 EOG Resources and Questerre Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between EOG Resources and Questerre Energy, you can compare the effects of market volatilities on EOG Resources and Questerre 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 EOG Resources with a short position of Questerre Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of EOG Resources and Questerre Energy.
Diversification Opportunities for EOG Resources and Questerre Energy
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between EOG and Questerre is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding EOG Resources and Questerre Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Questerre Energy and EOG 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 EOG Resources are associated (or correlated) with Questerre Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Questerre Energy has no effect on the direction of EOG Resources i.e., EOG Resources and Questerre Energy go up and down completely randomly.
Pair Corralation between EOG Resources and Questerre Energy
Considering the 90-day investment horizon EOG Resources is expected to generate 2.6 times less return on investment than Questerre Energy. But when comparing it to its historical volatility, EOG Resources is 2.59 times less risky than Questerre Energy. It trades about 0.02 of its potential returns per unit of risk. Questerre Energy is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 17.00 in Questerre Energy on September 3, 2024 and sell it today you would earn a total of 0.00 from holding Questerre Energy or generate 0.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
EOG Resources vs. Questerre Energy
Performance |
| Timeline |
| EOG Resources |
| Questerre Energy |
EOG Resources and Questerre Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with EOG Resources and Questerre Energy
The main advantage of trading using opposite EOG Resources and Questerre Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if EOG Resources position performs unexpectedly, Questerre 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 Questerre Energy will offset losses from the drop in Questerre Energy's long position.| EOG Resources vs. Permian Resources | EOG Resources vs. Devon Energy | EOG Resources vs. Coterra Energy | EOG Resources vs. Diamondback Energy |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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