Correlation Between China Rare and Aurelia Metals
Can any of the company-specific risk be diversified away by investing in both China Rare and Aurelia Metals 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 China Rare and Aurelia Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Rare Earth and Aurelia Metals Limited, you can compare the effects of market volatilities on China Rare and Aurelia Metals 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 China Rare with a short position of Aurelia Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Rare and Aurelia Metals.
Diversification Opportunities for China Rare and Aurelia Metals
-0.25 | Correlation Coefficient |
Very good diversification
The 3 months correlation between China and Aurelia is -0.25. Overlapping area represents the amount of risk that can be diversified away by holding China Rare Earth and Aurelia Metals Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aurelia Metals and China 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 China Rare Earth are associated (or correlated) with Aurelia Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aurelia Metals has no effect on the direction of China Rare i.e., China Rare and Aurelia Metals go up and down completely randomly.
Pair Corralation between China Rare and Aurelia Metals
Assuming the 90 days horizon China Rare Earth is expected to generate 15.92 times more return on investment than Aurelia Metals. However, China Rare is 15.92 times more volatile than Aurelia Metals Limited. It trades about 0.07 of its potential returns per unit of risk. Aurelia Metals Limited is currently generating about 0.12 per unit of risk. If you would invest 6.00 in China Rare Earth on December 29, 2024 and sell it today you would earn a total of 0.00 from holding China Rare Earth or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.31% |
Values | Daily Returns |
China Rare Earth vs. Aurelia Metals Limited
Performance |
Timeline |
China Rare Earth |
Aurelia Metals |
China Rare and Aurelia Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with China Rare and Aurelia Metals
The main advantage of trading using opposite China Rare and Aurelia Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Rare position performs unexpectedly, Aurelia Metals 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 Aurelia Metals will offset losses from the drop in Aurelia Metals' long position.China Rare vs. Edison Cobalt Corp | China Rare vs. Baroyeca Gold Silver | China Rare vs. Aurelia Metals Limited | China Rare vs. Champion Bear Resources |
Aurelia Metals vs. Champion Bear Resources | Aurelia Metals vs. Baroyeca Gold Silver | Aurelia Metals vs. Centaurus Metals Limited | Aurelia Metals vs. Edison Cobalt 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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.
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