Correlation Between Woodside Energy and Ring Energy
Can any of the company-specific risk be diversified away by investing in both Woodside Energy and Ring 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 Woodside Energy and Ring Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Woodside Energy Group and Ring Energy, you can compare the effects of market volatilities on Woodside Energy and Ring 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 Woodside Energy with a short position of Ring Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Woodside Energy and Ring Energy.
Diversification Opportunities for Woodside Energy and Ring Energy
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Woodside and Ring is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Woodside Energy Group and Ring Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ring Energy and Woodside 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 Woodside Energy Group are associated (or correlated) with Ring Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ring Energy has no effect on the direction of Woodside Energy i.e., Woodside Energy and Ring Energy go up and down completely randomly.
Pair Corralation between Woodside Energy and Ring Energy
Assuming the 90 days trading horizon Woodside Energy is expected to generate 1.07 times less return on investment than Ring Energy. But when comparing it to its historical volatility, Woodside Energy Group is 2.12 times less risky than Ring Energy. It trades about 0.1 of its potential returns per unit of risk. Ring Energy is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 136.00 in Ring Energy on September 5, 2024 and sell it today you would earn a total of 4.00 from holding Ring Energy or generate 2.94% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Woodside Energy Group vs. Ring Energy
Performance |
| Timeline |
| Woodside Energy Group |
| Ring Energy |
Woodside Energy and Ring Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Woodside Energy and Ring Energy
The main advantage of trading using opposite Woodside Energy and Ring Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Woodside Energy position performs unexpectedly, Ring 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 Ring Energy will offset losses from the drop in Ring Energy's long position.| Woodside Energy vs. CANON MARKETING JP | Woodside Energy vs. Salesforce | Woodside Energy vs. SIDETRADE EO 1 | Woodside Energy vs. CeoTronics AG |
| Ring Energy vs. Alibaba Group Holding | Ring Energy vs. Occidental Petroleum | Ring Energy vs. WOODSIDE ENE SPADR | Ring Energy vs. Woodside Energy Group |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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