Correlation Between China TowerLimited and XL Axiata
Can any of the company-specific risk be diversified away by investing in both China TowerLimited and XL Axiata 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 TowerLimited and XL Axiata into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Tower and XL Axiata Tbk, you can compare the effects of market volatilities on China TowerLimited and XL Axiata 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 TowerLimited with a short position of XL Axiata. Check out your portfolio center. Please also check ongoing floating volatility patterns of China TowerLimited and XL Axiata.
Diversification Opportunities for China TowerLimited and XL Axiata
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between China and PTXKY is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding China Tower and XL Axiata Tbk in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on XL Axiata Tbk and China TowerLimited 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 Tower are associated (or correlated) with XL Axiata. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of XL Axiata Tbk has no effect on the direction of China TowerLimited i.e., China TowerLimited and XL Axiata go up and down completely randomly.
Pair Corralation between China TowerLimited and XL Axiata
Assuming the 90 days horizon China Tower is expected to generate 49.74 times more return on investment than XL Axiata. However, China TowerLimited is 49.74 times more volatile than XL Axiata Tbk. It trades about 0.25 of its potential returns per unit of risk. XL Axiata Tbk is currently generating about 0.04 per unit of risk. If you would invest 109.00 in China Tower on January 13, 2025 and sell it today you would earn a total of 76.00 from holding China Tower or generate 69.72% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 59.51% |
| Values | Daily Returns |
China Tower vs. XL Axiata Tbk
Performance |
| Timeline |
| China TowerLimited |
| XL Axiata Tbk |
China TowerLimited and XL Axiata Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with China TowerLimited and XL Axiata
The main advantage of trading using opposite China TowerLimited and XL Axiata positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China TowerLimited position performs unexpectedly, XL Axiata 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 XL Axiata will offset losses from the drop in XL Axiata's long position.| China TowerLimited vs. BCE Inc | China TowerLimited vs. Axiologix | China TowerLimited vs. Advanced Info Service | China TowerLimited vs. Access Power Co |
| XL Axiata vs. BCE Inc | XL Axiata vs. Axiologix | XL Axiata vs. Advanced Info Service | XL Axiata vs. Access Power Co |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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