Correlation Between China Construction and Barclays PLC
Can any of the company-specific risk be diversified away by investing in both China Construction and Barclays PLC 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 Construction and Barclays PLC into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Construction Bank and Barclays PLC, you can compare the effects of market volatilities on China Construction and Barclays PLC 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 Construction with a short position of Barclays PLC. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Construction and Barclays PLC.
Diversification Opportunities for China Construction and Barclays PLC
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between China and Barclays is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding China Construction Bank and Barclays PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Barclays PLC and China Construction 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 Construction Bank are associated (or correlated) with Barclays PLC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Barclays PLC has no effect on the direction of China Construction i.e., China Construction and Barclays PLC go up and down completely randomly.
Pair Corralation between China Construction and Barclays PLC
Assuming the 90 days horizon China Construction is expected to generate 1.26 times less return on investment than Barclays PLC. In addition to that, China Construction is 1.42 times more volatile than Barclays PLC. It trades about 0.05 of its total potential returns per unit of risk. Barclays PLC is currently generating about 0.09 per unit of volatility. If you would invest 291.00 in Barclays PLC on September 6, 2024 and sell it today you would earn a total of 43.00 from holding Barclays PLC or generate 14.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 98.44% |
Values | Daily Returns |
China Construction Bank vs. Barclays PLC
Performance |
Timeline |
China Construction Bank |
Barclays PLC |
China Construction and Barclays PLC Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with China Construction and Barclays PLC
The main advantage of trading using opposite China Construction and Barclays PLC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Construction position performs unexpectedly, Barclays PLC 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 Barclays PLC will offset losses from the drop in Barclays PLC's long position.China Construction vs. Svenska Handelsbanken PK | China Construction vs. Industrial and Commercial | China Construction vs. Bank of America | China Construction vs. Bank of America |
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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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