Correlation Between Generation Mining and Group Ten
Can any of the company-specific risk be diversified away by investing in both Generation Mining and Group Ten 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 Generation Mining and Group Ten into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Generation Mining Limited and Group Ten Metals, you can compare the effects of market volatilities on Generation Mining and Group Ten 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 Generation Mining with a short position of Group Ten. Check out your portfolio center. Please also check ongoing floating volatility patterns of Generation Mining and Group Ten.
Diversification Opportunities for Generation Mining and Group Ten
0.43 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Generation and Group is 0.43. Overlapping area represents the amount of risk that can be diversified away by holding Generation Mining Limited and Group Ten Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Group Ten Metals and Generation Mining 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 Generation Mining Limited are associated (or correlated) with Group Ten. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Group Ten Metals has no effect on the direction of Generation Mining i.e., Generation Mining and Group Ten go up and down completely randomly.
Pair Corralation between Generation Mining and Group Ten
Assuming the 90 days horizon Generation Mining Limited is expected to under-perform the Group Ten. In addition to that, Generation Mining is 1.15 times more volatile than Group Ten Metals. It trades about -0.01 of its total potential returns per unit of risk. Group Ten Metals is currently generating about 0.01 per unit of volatility. If you would invest 14.00 in Group Ten Metals on August 31, 2024 and sell it today you would lose (4.00) from holding Group Ten Metals or give up 28.57% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Generation Mining Limited vs. Group Ten Metals
Performance |
| Timeline |
| Generation Mining |
| Group Ten Metals |
Generation Mining and Group Ten Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Generation Mining and Group Ten
The main advantage of trading using opposite Generation Mining and Group Ten positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Generation Mining position performs unexpectedly, Group Ten 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 Group Ten will offset losses from the drop in Group Ten's long position.| Generation Mining vs. Mundoro Capital | Generation Mining vs. Norra Metals Corp | Generation Mining vs. E79 Resources Corp | Generation Mining vs. Voltage Metals Corp |
| Group Ten vs. Ascendant Resources | Group Ten vs. Atico Mining | Group Ten vs. Prime Mining Corp | Group Ten vs. Wallbridge Mining |
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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