Correlation Between BW OFFSHORE and GREEN PLAINS
Can any of the company-specific risk be diversified away by investing in both BW OFFSHORE and GREEN PLAINS 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 BW OFFSHORE and GREEN PLAINS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BW OFFSHORE LTD and GREEN PLAINS, you can compare the effects of market volatilities on BW OFFSHORE and GREEN PLAINS 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 BW OFFSHORE with a short position of GREEN PLAINS. Check out your portfolio center. Please also check ongoing floating volatility patterns of BW OFFSHORE and GREEN PLAINS.
Diversification Opportunities for BW OFFSHORE and GREEN PLAINS
-0.38 | Correlation Coefficient |
Very good diversification
The 3 months correlation between XY81 and GREEN is -0.38. Overlapping area represents the amount of risk that can be diversified away by holding BW OFFSHORE LTD and GREEN PLAINS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GREEN PLAINS and BW 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 BW OFFSHORE LTD are associated (or correlated) with GREEN PLAINS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GREEN PLAINS has no effect on the direction of BW OFFSHORE i.e., BW OFFSHORE and GREEN PLAINS go up and down completely randomly.
Pair Corralation between BW OFFSHORE and GREEN PLAINS
Assuming the 90 days trading horizon BW OFFSHORE LTD is expected to generate 0.45 times more return on investment than GREEN PLAINS. However, BW OFFSHORE LTD is 2.21 times less risky than GREEN PLAINS. It trades about 0.11 of its potential returns per unit of risk. GREEN PLAINS is currently generating about -0.18 per unit of risk. If you would invest 218.00 in BW OFFSHORE LTD on December 21, 2024 and sell it today you would earn a total of 31.00 from holding BW OFFSHORE LTD or generate 14.22% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
BW OFFSHORE LTD vs. GREEN PLAINS
Performance |
Timeline |
BW OFFSHORE LTD |
GREEN PLAINS |
BW OFFSHORE and GREEN PLAINS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BW OFFSHORE and GREEN PLAINS
The main advantage of trading using opposite BW OFFSHORE and GREEN PLAINS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BW OFFSHORE position performs unexpectedly, GREEN PLAINS 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 GREEN PLAINS will offset losses from the drop in GREEN PLAINS's long position.BW OFFSHORE vs. TROPHY GAMES DEV | BW OFFSHORE vs. International Game Technology | BW OFFSHORE vs. REMEDY ENTERTAINMENT OYJ | BW OFFSHORE vs. Media and Games |
GREEN PLAINS vs. Diversified Healthcare Trust | GREEN PLAINS vs. SLR Investment Corp | GREEN PLAINS vs. PennyMac Mortgage Investment | GREEN PLAINS vs. JAPAN TOBACCO UNSPADR12 |
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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