Correlation Between Impala Platinum and China Resources
Can any of the company-specific risk be diversified away by investing in both Impala Platinum and China Resources 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 Impala Platinum and China Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Impala Platinum Holdings and China Resources Beer, you can compare the effects of market volatilities on Impala Platinum and China Resources 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 Impala Platinum with a short position of China Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Impala Platinum and China Resources.
Diversification Opportunities for Impala Platinum and China Resources
0.3 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Impala and China is 0.3. Overlapping area represents the amount of risk that can be diversified away by holding Impala Platinum Holdings and China Resources Beer in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Resources Beer and Impala Platinum 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 Impala Platinum Holdings are associated (or correlated) with China Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Resources Beer has no effect on the direction of Impala Platinum i.e., Impala Platinum and China Resources go up and down completely randomly.
Pair Corralation between Impala Platinum and China Resources
Assuming the 90 days trading horizon Impala Platinum Holdings is expected to under-perform the China Resources. In addition to that, Impala Platinum is 1.01 times more volatile than China Resources Beer. It trades about -0.21 of its total potential returns per unit of risk. China Resources Beer is currently generating about -0.11 per unit of volatility. If you would invest 352.00 in China Resources Beer on October 6, 2024 and sell it today you would lose (58.00) from holding China Resources Beer or give up 16.48% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 97.5% |
Values | Daily Returns |
Impala Platinum Holdings vs. China Resources Beer
Performance |
Timeline |
Impala Platinum Holdings |
China Resources Beer |
Impala Platinum and China Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Impala Platinum and China Resources
The main advantage of trading using opposite Impala Platinum and China Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Impala Platinum position performs unexpectedly, China Resources 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 China Resources will offset losses from the drop in China Resources' long position.Impala Platinum vs. Gaming and Leisure | Impala Platinum vs. American Airlines Group | Impala Platinum vs. USWE SPORTS AB | Impala Platinum vs. International Consolidated Airlines |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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