Correlation Between China Building and Digital China
Specify exactly 2 symbols:
By analyzing existing cross correlation between China Building Material and Digital China Information, you can compare the effects of market volatilities on China Building and Digital China 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 Building with a short position of Digital China. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Building and Digital China.
Diversification Opportunities for China Building and Digital China
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between China and Digital is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding China Building Material and Digital China Information in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Digital China Information and China Building 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 Building Material are associated (or correlated) with Digital China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Digital China Information has no effect on the direction of China Building i.e., China Building and Digital China go up and down completely randomly.
Pair Corralation between China Building and Digital China
Assuming the 90 days trading horizon China Building Material is expected to generate 0.75 times more return on investment than Digital China. However, China Building Material is 1.33 times less risky than Digital China. It trades about -0.01 of its potential returns per unit of risk. Digital China Information is currently generating about -0.06 per unit of risk. If you would invest 735.00 in China Building Material on November 7, 2024 and sell it today you would lose (19.00) from holding China Building Material or give up 2.59% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
China Building Material vs. Digital China Information
Performance |
Timeline |
China Building Material |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Digital China Information |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
China Building and Digital China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with China Building and Digital China
The main advantage of trading using opposite China Building and Digital China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Building position performs unexpectedly, Digital China 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 Digital China will offset losses from the drop in Digital China's long position.The idea behind China Building Material and Digital China Information pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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