Correlation Between Eidesvik Offshore and BW Energy
Can any of the company-specific risk be diversified away by investing in both Eidesvik Offshore and BW 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 Eidesvik Offshore and BW Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Eidesvik Offshore ASA and BW Energy, you can compare the effects of market volatilities on Eidesvik Offshore and BW 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 Eidesvik Offshore with a short position of BW Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Eidesvik Offshore and BW Energy.
Diversification Opportunities for Eidesvik Offshore and BW Energy
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Eidesvik and BWE is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding Eidesvik Offshore ASA and BW Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BW Energy and Eidesvik Offshore 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 Eidesvik Offshore ASA are associated (or correlated) with BW Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BW Energy has no effect on the direction of Eidesvik Offshore i.e., Eidesvik Offshore and BW Energy go up and down completely randomly.
Pair Corralation between Eidesvik Offshore and BW Energy
Assuming the 90 days trading horizon Eidesvik Offshore ASA is expected to under-perform the BW Energy. But the stock apears to be less risky and, when comparing its historical volatility, Eidesvik Offshore ASA is 1.07 times less risky than BW Energy. The stock trades about -0.11 of its potential returns per unit of risk. The BW Energy is currently generating about -0.08 of returns per unit of risk over similar time horizon. If you would invest 2,525 in BW Energy on September 3, 2024 and sell it today you would lose (300.00) from holding BW Energy or give up 11.88% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Eidesvik Offshore ASA vs. BW Energy
Performance |
| Timeline |
| Eidesvik Offshore ASA |
| BW Energy |
Eidesvik Offshore and BW Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Eidesvik Offshore and BW Energy
The main advantage of trading using opposite Eidesvik Offshore and BW Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Eidesvik Offshore position performs unexpectedly, BW 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 BW Energy will offset losses from the drop in BW Energy's long position.| Eidesvik Offshore vs. BW Energy | Eidesvik Offshore vs. Subsea 7 SA | Eidesvik Offshore vs. BW LPG | Eidesvik Offshore vs. Dno ASA |
| BW Energy vs. BW Offshore | BW Energy vs. Panoro Energy ASA | BW Energy vs. Aker BP ASA | BW Energy vs. BW LPG |
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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