Correlation Between GreenX Metals and Berkeley Energy
Can any of the company-specific risk be diversified away by investing in both GreenX Metals and Berkeley 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 GreenX Metals and Berkeley Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GreenX Metals and Berkeley Energy, you can compare the effects of market volatilities on GreenX Metals and Berkeley 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 GreenX Metals with a short position of Berkeley Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of GreenX Metals and Berkeley Energy.
Diversification Opportunities for GreenX Metals and Berkeley Energy
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between GreenX and Berkeley is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding GreenX Metals and Berkeley Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Berkeley Energy and GreenX Metals 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 GreenX Metals are associated (or correlated) with Berkeley Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Berkeley Energy has no effect on the direction of GreenX Metals i.e., GreenX Metals and Berkeley Energy go up and down completely randomly.
Pair Corralation between GreenX Metals and Berkeley Energy
Assuming the 90 days trading horizon GreenX Metals is expected to generate 0.91 times more return on investment than Berkeley Energy. However, GreenX Metals is 1.09 times less risky than Berkeley Energy. It trades about 0.02 of its potential returns per unit of risk. Berkeley Energy is currently generating about 0.01 per unit of risk. If you would invest 67.00 in GreenX Metals on August 31, 2024 and sell it today you would earn a total of 0.00 from holding GreenX Metals or generate 0.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 97.78% |
| Values | Daily Returns |
GreenX Metals vs. Berkeley Energy
Performance |
| Timeline |
| GreenX Metals |
| Berkeley Energy |
GreenX Metals and Berkeley Energy Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GreenX Metals and Berkeley Energy
The main advantage of trading using opposite GreenX Metals and Berkeley Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GreenX Metals position performs unexpectedly, Berkeley 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 Berkeley Energy will offset losses from the drop in Berkeley Energy's long position.| GreenX Metals vs. Northern Star Resources | GreenX Metals vs. Evolution Mining | GreenX Metals vs. Bluescope Steel | GreenX Metals vs. De Grey Mining |
| Berkeley Energy vs. Sky Metals | Berkeley Energy vs. Queste Communications | Berkeley Energy vs. Stelar Metals | Berkeley Energy vs. GreenX Metals |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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