Correlation Between Enerflex and Dawson Geophysical
Can any of the company-specific risk be diversified away by investing in both Enerflex and Dawson Geophysical 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 Enerflex and Dawson Geophysical into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Enerflex and Dawson Geophysical, you can compare the effects of market volatilities on Enerflex and Dawson Geophysical 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 Enerflex with a short position of Dawson Geophysical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Enerflex and Dawson Geophysical.
Diversification Opportunities for Enerflex and Dawson Geophysical
-0.18 | Correlation Coefficient |
Good diversification
The 3 months correlation between Enerflex and Dawson is -0.18. Overlapping area represents the amount of risk that can be diversified away by holding Enerflex and Dawson Geophysical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dawson Geophysical and Enerflex 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 Enerflex are associated (or correlated) with Dawson Geophysical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dawson Geophysical has no effect on the direction of Enerflex i.e., Enerflex and Dawson Geophysical go up and down completely randomly.
Pair Corralation between Enerflex and Dawson Geophysical
Given the investment horizon of 90 days Enerflex is expected to generate 0.54 times more return on investment than Dawson Geophysical. However, Enerflex is 1.86 times less risky than Dawson Geophysical. It trades about 0.23 of its potential returns per unit of risk. Dawson Geophysical is currently generating about -0.03 per unit of risk. If you would invest 477.00 in Enerflex on September 2, 2024 and sell it today you would earn a total of 438.00 from holding Enerflex or generate 91.82% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Enerflex vs. Dawson Geophysical
Performance |
| Timeline |
| Enerflex |
| Dawson Geophysical |
Enerflex and Dawson Geophysical Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Enerflex and Dawson Geophysical
The main advantage of trading using opposite Enerflex and Dawson Geophysical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Enerflex position performs unexpectedly, Dawson Geophysical 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 Dawson Geophysical will offset losses from the drop in Dawson Geophysical's long position.| Enerflex vs. Natural Gas Services | Enerflex vs. Archrock | Enerflex vs. Geospace Technologies | Enerflex vs. Newpark Resources |
| Dawson Geophysical vs. NXT Energy Solutions | Dawson Geophysical vs. Mccoy Global | Dawson Geophysical vs. National Energy Services | Dawson Geophysical vs. Ranger Energy Services |
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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