Correlation Between Sigma Lithium and Pilbara Minerals
Can any of the company-specific risk be diversified away by investing in both Sigma Lithium and Pilbara Minerals 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 Pilbara Minerals 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 Pilbara Minerals Limited, you can compare the effects of market volatilities on Sigma Lithium and Pilbara Minerals 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 Pilbara Minerals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sigma Lithium and Pilbara Minerals.
Diversification Opportunities for Sigma Lithium and Pilbara Minerals
0.06 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Sigma and Pilbara is 0.06. Overlapping area represents the amount of risk that can be diversified away by holding Sigma Lithium Resources and Pilbara Minerals Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pilbara Minerals 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 Pilbara Minerals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pilbara Minerals has no effect on the direction of Sigma Lithium i.e., Sigma Lithium and Pilbara Minerals go up and down completely randomly.
Pair Corralation between Sigma Lithium and Pilbara Minerals
Given the investment horizon of 90 days Sigma Lithium Resources is expected to generate 1.36 times more return on investment than Pilbara Minerals. However, Sigma Lithium is 1.36 times more volatile than Pilbara Minerals Limited. It trades about -0.12 of its potential returns per unit of risk. Pilbara Minerals Limited is currently generating about -0.57 per unit of risk. If you would invest 1,359 in Sigma Lithium Resources on September 13, 2024 and sell it today you would lose (139.00) from holding Sigma Lithium Resources or give up 10.23% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 95.45% |
Values | Daily Returns |
Sigma Lithium Resources vs. Pilbara Minerals Limited
Performance |
Timeline |
Sigma Lithium Resources |
Pilbara Minerals |
Sigma Lithium and Pilbara Minerals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sigma Lithium and Pilbara Minerals
The main advantage of trading using opposite Sigma Lithium and Pilbara Minerals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sigma Lithium position performs unexpectedly, Pilbara Minerals 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 Pilbara Minerals will offset losses from the drop in Pilbara Minerals' 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 |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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