Correlation Between Sigma Lithium and BHP Group
Can any of the company-specific risk be diversified away by investing in both Sigma Lithium and BHP Group 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 Sigma Lithium and BHP Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sigma Lithium Resources and BHP Group Limited, you can compare the effects of market volatilities on Sigma Lithium and BHP Group 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 Sigma Lithium with a short position of BHP Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sigma Lithium and BHP Group.
Diversification Opportunities for Sigma Lithium and BHP Group
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Sigma and BHP is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Sigma Lithium Resources and BHP Group Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BHP Group Limited and Sigma Lithium 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 Sigma Lithium Resources are associated (or correlated) with BHP Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BHP Group Limited has no effect on the direction of Sigma Lithium i.e., Sigma Lithium and BHP Group go up and down completely randomly.
Pair Corralation between Sigma Lithium and BHP Group
Given the investment horizon of 90 days Sigma Lithium Resources is expected to generate 2.43 times more return on investment than BHP Group. However, Sigma Lithium is 2.43 times more volatile than BHP Group Limited. It trades about 0.05 of its potential returns per unit of risk. BHP Group Limited is currently generating about -0.19 per unit of risk. If you would invest 1,421 in Sigma Lithium Resources on August 24, 2024 and sell it today you would earn a total of 44.00 from holding Sigma Lithium Resources or generate 3.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Sigma Lithium Resources vs. BHP Group Limited
Performance |
| Timeline |
| Sigma Lithium Resources |
| BHP Group Limited |
Sigma Lithium and BHP Group Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sigma Lithium and BHP Group
The main advantage of trading using opposite Sigma Lithium and BHP Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sigma Lithium position performs unexpectedly, BHP Group 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 BHP Group will offset losses from the drop in BHP Group's long position.| Sigma Lithium vs. Piedmont Lithium Ltd | Sigma Lithium vs. Standard Lithium | Sigma Lithium vs. MP Materials Corp | Sigma Lithium vs. Vale SA ADR |
| BHP Group vs. Vale SA ADR | BHP Group vs. Teck Resources Ltd | BHP Group vs. Lithium Americas Corp | BHP Group vs. MP Materials Corp |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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