Correlation Between Zhongtong Guomai and Dawning Information
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By analyzing existing cross correlation between Zhongtong Guomai Communication and Dawning Information Industry, you can compare the effects of market volatilities on Zhongtong Guomai and Dawning Information 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 Zhongtong Guomai with a short position of Dawning Information. Check out your portfolio center. Please also check ongoing floating volatility patterns of Zhongtong Guomai and Dawning Information.
Diversification Opportunities for Zhongtong Guomai and Dawning Information
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Zhongtong and Dawning is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Zhongtong Guomai Communication and Dawning Information Industry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dawning Information and Zhongtong Guomai 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 Zhongtong Guomai Communication are associated (or correlated) with Dawning Information. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dawning Information has no effect on the direction of Zhongtong Guomai i.e., Zhongtong Guomai and Dawning Information go up and down completely randomly.
Pair Corralation between Zhongtong Guomai and Dawning Information
Assuming the 90 days trading horizon Zhongtong Guomai is expected to generate 1.89 times less return on investment than Dawning Information. But when comparing it to its historical volatility, Zhongtong Guomai Communication is 1.12 times less risky than Dawning Information. It trades about 0.2 of its potential returns per unit of risk. Dawning Information Industry is currently generating about 0.33 of returns per unit of risk over similar time horizon. If you would invest 3,432 in Dawning Information Industry on September 6, 2024 and sell it today you would earn a total of 4,368 from holding Dawning Information Industry or generate 127.27% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Zhongtong Guomai Communication vs. Dawning Information Industry
Performance |
Timeline |
Zhongtong Guomai Com |
Dawning Information |
Zhongtong Guomai and Dawning Information Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Zhongtong Guomai and Dawning Information
The main advantage of trading using opposite Zhongtong Guomai and Dawning Information positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Zhongtong Guomai position performs unexpectedly, Dawning Information 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 Dawning Information will offset losses from the drop in Dawning Information's long position.Zhongtong Guomai vs. Industrial and Commercial | Zhongtong Guomai vs. Agricultural Bank of | Zhongtong Guomai vs. China Construction Bank | Zhongtong Guomai vs. Bank of China |
Dawning Information vs. Industrial and Commercial | Dawning Information vs. Agricultural Bank of | Dawning Information vs. China Construction Bank | Dawning Information vs. Bank of China |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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