Correlation Between Bank of China and Zhengzhou Qianweiyangchu
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By analyzing existing cross correlation between Bank of China and Zhengzhou Qianweiyangchu Food, you can compare the effects of market volatilities on Bank of China and Zhengzhou Qianweiyangchu 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 Bank of China with a short position of Zhengzhou Qianweiyangchu. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of China and Zhengzhou Qianweiyangchu.
Diversification Opportunities for Bank of China and Zhengzhou Qianweiyangchu
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Bank and Zhengzhou is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding Bank of China and Zhengzhou Qianweiyangchu Food in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhengzhou Qianweiyangchu and Bank of China 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 Bank of China are associated (or correlated) with Zhengzhou Qianweiyangchu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhengzhou Qianweiyangchu has no effect on the direction of Bank of China i.e., Bank of China and Zhengzhou Qianweiyangchu go up and down completely randomly.
Pair Corralation between Bank of China and Zhengzhou Qianweiyangchu
Assuming the 90 days trading horizon Bank of China is expected to generate 5.58 times less return on investment than Zhengzhou Qianweiyangchu. But when comparing it to its historical volatility, Bank of China is 4.37 times less risky than Zhengzhou Qianweiyangchu. It trades about 0.18 of its potential returns per unit of risk. Zhengzhou Qianweiyangchu Food is currently generating about 0.23 of returns per unit of risk over similar time horizon. If you would invest 2,980 in Zhengzhou Qianweiyangchu Food on August 31, 2024 and sell it today you would earn a total of 597.00 from holding Zhengzhou Qianweiyangchu Food or generate 20.03% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 95.65% |
| Values | Daily Returns |
Bank of China vs. Zhengzhou Qianweiyangchu Food
Performance |
| Timeline |
| Bank of China |
| Zhengzhou Qianweiyangchu |
Bank of China and Zhengzhou Qianweiyangchu Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Bank of China and Zhengzhou Qianweiyangchu
The main advantage of trading using opposite Bank of China and Zhengzhou Qianweiyangchu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of China position performs unexpectedly, Zhengzhou Qianweiyangchu 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 Zhengzhou Qianweiyangchu will offset losses from the drop in Zhengzhou Qianweiyangchu's long position.| Bank of China vs. Tianjin Hi Tech Development | Bank of China vs. Dazhong Transportation Group | Bank of China vs. Hubeiyichang Transportation Group | Bank of China vs. Guangdong Shenglu Telecommunication |
| Zhengzhou Qianweiyangchu vs. Lutian Machinery Co | Zhengzhou Qianweiyangchu vs. PetroChina Co Ltd | Zhengzhou Qianweiyangchu vs. Bank of China | Zhengzhou Qianweiyangchu vs. Gansu Jiu Steel |
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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