Correlation Between Elite Material and China Mobile
Can any of the company-specific risk be diversified away by investing in both Elite Material and China Mobile 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 Elite Material and China Mobile into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Elite Material Co and China Mobile, you can compare the effects of market volatilities on Elite Material and China Mobile 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 Elite Material with a short position of China Mobile. Check out your portfolio center. Please also check ongoing floating volatility patterns of Elite Material and China Mobile.
Diversification Opportunities for Elite Material and China Mobile
-0.29 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Elite and China is -0.29. Overlapping area represents the amount of risk that can be diversified away by holding Elite Material Co and China Mobile in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Mobile and Elite Material 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 Elite Material Co are associated (or correlated) with China Mobile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Mobile has no effect on the direction of Elite Material i.e., Elite Material and China Mobile go up and down completely randomly.
Pair Corralation between Elite Material and China Mobile
Assuming the 90 days trading horizon Elite Material Co is expected to generate 2.29 times more return on investment than China Mobile. However, Elite Material is 2.29 times more volatile than China Mobile. It trades about 0.16 of its potential returns per unit of risk. China Mobile is currently generating about -0.04 per unit of risk. If you would invest 47,200 in Elite Material Co on September 15, 2024 and sell it today you would earn a total of 12,700 from holding Elite Material Co or generate 26.91% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Elite Material Co vs. China Mobile
Performance |
Timeline |
Elite Material |
China Mobile |
Elite Material and China Mobile Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Elite Material and China Mobile
The main advantage of trading using opposite Elite Material and China Mobile positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Elite Material position performs unexpectedly, China Mobile 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 Mobile will offset losses from the drop in China Mobile's long position.Elite Material vs. AU Optronics | Elite Material vs. Innolux Corp | Elite Material vs. Ruentex Development Co | Elite Material vs. WiseChip Semiconductor |
China Mobile vs. Elite Material Co | China Mobile vs. Advanced Echem Materials | China Mobile vs. U Ming Marine Transport | China Mobile vs. Fulin Plastic Industry |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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