Correlation Between WUXI BIOLOGICS and Mercedes Benz
Can any of the company-specific risk be diversified away by investing in both WUXI BIOLOGICS and Mercedes Benz 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 WUXI BIOLOGICS and Mercedes Benz into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between WUXI BIOLOGICS UNSPADR2 and Mercedes Benz Group AG, you can compare the effects of market volatilities on WUXI BIOLOGICS and Mercedes Benz 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 WUXI BIOLOGICS with a short position of Mercedes Benz. Check out your portfolio center. Please also check ongoing floating volatility patterns of WUXI BIOLOGICS and Mercedes Benz.
Diversification Opportunities for WUXI BIOLOGICS and Mercedes Benz
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between WUXI and Mercedes is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding WUXI BIOLOGICS UNSPADR2 and Mercedes Benz Group AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mercedes Benz Group and WUXI BIOLOGICS 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 WUXI BIOLOGICS UNSPADR2 are associated (or correlated) with Mercedes Benz. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mercedes Benz Group has no effect on the direction of WUXI BIOLOGICS i.e., WUXI BIOLOGICS and Mercedes Benz go up and down completely randomly.
Pair Corralation between WUXI BIOLOGICS and Mercedes Benz
Assuming the 90 days trading horizon WUXI BIOLOGICS UNSPADR2 is expected to generate 2.82 times more return on investment than Mercedes Benz. However, WUXI BIOLOGICS is 2.82 times more volatile than Mercedes Benz Group AG. It trades about 0.14 of its potential returns per unit of risk. Mercedes Benz Group AG is currently generating about 0.12 per unit of risk. If you would invest 428.00 in WUXI BIOLOGICS UNSPADR2 on December 27, 2024 and sell it today you would earn a total of 167.00 from holding WUXI BIOLOGICS UNSPADR2 or generate 39.02% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
WUXI BIOLOGICS UNSPADR2 vs. Mercedes Benz Group AG
Performance |
Timeline |
WUXI BIOLOGICS UNSPADR2 |
Mercedes Benz Group |
WUXI BIOLOGICS and Mercedes Benz Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with WUXI BIOLOGICS and Mercedes Benz
The main advantage of trading using opposite WUXI BIOLOGICS and Mercedes Benz positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if WUXI BIOLOGICS position performs unexpectedly, Mercedes Benz 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 Mercedes Benz will offset losses from the drop in Mercedes Benz's long position.WUXI BIOLOGICS vs. Kaufman Broad SA | WUXI BIOLOGICS vs. PennyMac Mortgage Investment | WUXI BIOLOGICS vs. GOLD ROAD RES | WUXI BIOLOGICS vs. Fukuyama Transporting Co |
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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 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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