Correlation Between Lynas Rare and Rare Element
Can any of the company-specific risk be diversified away by investing in both Lynas Rare and Rare Element 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 Lynas Rare and Rare Element into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lynas Rare Earths and Rare Element Resources, you can compare the effects of market volatilities on Lynas Rare and Rare Element 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 Lynas Rare with a short position of Rare Element. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lynas Rare and Rare Element.
Diversification Opportunities for Lynas Rare and Rare Element
0.08 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Lynas and Rare is 0.08. Overlapping area represents the amount of risk that can be diversified away by holding Lynas Rare Earths and Rare Element Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Rare Element Resources and Lynas Rare 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 Lynas Rare Earths are associated (or correlated) with Rare Element. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Rare Element Resources has no effect on the direction of Lynas Rare i.e., Lynas Rare and Rare Element go up and down completely randomly.
Pair Corralation between Lynas Rare and Rare Element
Assuming the 90 days horizon Lynas Rare Earths is expected to under-perform the Rare Element. But the pink sheet apears to be less risky and, when comparing its historical volatility, Lynas Rare Earths is 2.96 times less risky than Rare Element. The pink sheet trades about -0.01 of its potential returns per unit of risk. The Rare Element Resources is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 41.00 in Rare Element Resources on August 26, 2024 and sell it today you would earn a total of 22.00 from holding Rare Element Resources or generate 53.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 31.99% |
Values | Daily Returns |
Lynas Rare Earths vs. Rare Element Resources
Performance |
Timeline |
Lynas Rare Earths |
Rare Element Resources |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Lynas Rare and Rare Element Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lynas Rare and Rare Element
The main advantage of trading using opposite Lynas Rare and Rare Element positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lynas Rare position performs unexpectedly, Rare Element 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 Rare Element will offset losses from the drop in Rare Element's long position.Lynas Rare vs. Norra Metals Corp | Lynas Rare vs. ZincX Resources Corp | Lynas Rare vs. Nuinsco Resources Limited | Lynas Rare vs. South Star Battery |
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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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