Correlation Between China Construction and Dow Jones
Can any of the company-specific risk be diversified away by investing in both China Construction and Dow Jones 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 Dow Jones 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 Dow Jones Industrial, you can compare the effects of market volatilities on China Construction and Dow Jones 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 Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Construction and Dow Jones.
Diversification Opportunities for China Construction and Dow Jones
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between China and Dow is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding China Construction Bank and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial 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 Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of China Construction i.e., China Construction and Dow Jones go up and down completely randomly.
Pair Corralation between China Construction and Dow Jones
Assuming the 90 days horizon China Construction Bank is expected to generate 3.12 times more return on investment than Dow Jones. However, China Construction is 3.12 times more volatile than Dow Jones Industrial. It trades about 0.08 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.2 per unit of risk. If you would invest 1,366 in China Construction Bank on September 3, 2024 and sell it today you would earn a total of 153.00 from holding China Construction Bank or generate 11.2% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
China Construction Bank vs. Dow Jones Industrial
Performance |
Timeline |
China Construction and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
China Construction Bank
Pair trading matchups for China Construction
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with China Construction and Dow Jones
The main advantage of trading using opposite China Construction and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Construction position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.China Construction vs. Bank of China | China Construction vs. Industrial and Commercial | China Construction vs. China Construction Bank | 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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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