Correlation Between Merck and China TowerLimited
Can any of the company-specific risk be diversified away by investing in both Merck and China TowerLimited 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 Merck and China TowerLimited into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Merck Company and China Tower, you can compare the effects of market volatilities on Merck and China TowerLimited 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 Merck with a short position of China TowerLimited. Check out your portfolio center. Please also check ongoing floating volatility patterns of Merck and China TowerLimited.
Diversification Opportunities for Merck and China TowerLimited
-0.66 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Merck and China is -0.66. Overlapping area represents the amount of risk that can be diversified away by holding Merck Company and China Tower in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China TowerLimited and Merck 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 Merck Company are associated (or correlated) with China TowerLimited. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China TowerLimited has no effect on the direction of Merck i.e., Merck and China TowerLimited go up and down completely randomly.
Pair Corralation between Merck and China TowerLimited
Considering the 90-day investment horizon Merck Company is expected to under-perform the China TowerLimited. But the stock apears to be less risky and, when comparing its historical volatility, Merck Company is 2.75 times less risky than China TowerLimited. The stock trades about -0.17 of its potential returns per unit of risk. The China Tower is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 13.00 in China Tower on August 26, 2024 and sell it today you would earn a total of 0.00 from holding China Tower or generate 0.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Merck Company vs. China Tower
Performance |
| Timeline |
| Merck Company |
| China TowerLimited |
Merck and China TowerLimited Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Merck and China TowerLimited
The main advantage of trading using opposite Merck and China TowerLimited positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Merck position performs unexpectedly, China TowerLimited 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 TowerLimited will offset losses from the drop in China TowerLimited's long position.| Merck vs. Capricor Therapeutics | Merck vs. Soleno Therapeutics | Merck vs. Bio Path Holdings | Merck vs. Moleculin Biotech |
| China TowerLimited vs. Singapore Telecommunications Limited | China TowerLimited vs. Vodafone Group PLC | China TowerLimited vs. PT Indosat Tbk | China TowerLimited vs. KDDI 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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