Correlation Between Beijing Seeyon and Zhejiang Construction
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By analyzing existing cross correlation between Beijing Seeyon Internet and Zhejiang Construction Investment, you can compare the effects of market volatilities on Beijing Seeyon and Zhejiang Construction 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 Beijing Seeyon with a short position of Zhejiang Construction. Check out your portfolio center. Please also check ongoing floating volatility patterns of Beijing Seeyon and Zhejiang Construction.
Diversification Opportunities for Beijing Seeyon and Zhejiang Construction
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Beijing and Zhejiang is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Beijing Seeyon Internet and Zhejiang Construction Investme in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhejiang Construction and Beijing Seeyon 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 Beijing Seeyon Internet are associated (or correlated) with Zhejiang Construction. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhejiang Construction has no effect on the direction of Beijing Seeyon i.e., Beijing Seeyon and Zhejiang Construction go up and down completely randomly.
Pair Corralation between Beijing Seeyon and Zhejiang Construction
Assuming the 90 days trading horizon Beijing Seeyon Internet is expected to generate 1.35 times more return on investment than Zhejiang Construction. However, Beijing Seeyon is 1.35 times more volatile than Zhejiang Construction Investment. It trades about -0.04 of its potential returns per unit of risk. Zhejiang Construction Investment is currently generating about -0.05 per unit of risk. If you would invest 5,471 in Beijing Seeyon Internet on October 18, 2024 and sell it today you would lose (3,621) from holding Beijing Seeyon Internet or give up 66.19% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 99.79% |
| Values | Daily Returns |
Beijing Seeyon Internet vs. Zhejiang Construction Investme
Performance |
| Timeline |
| Beijing Seeyon Internet |
| Zhejiang Construction |
Beijing Seeyon and Zhejiang Construction Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Beijing Seeyon and Zhejiang Construction
The main advantage of trading using opposite Beijing Seeyon and Zhejiang Construction positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Beijing Seeyon position performs unexpectedly, Zhejiang Construction 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 Zhejiang Construction will offset losses from the drop in Zhejiang Construction's long position.| Beijing Seeyon vs. Zhejiang Construction Investment | Beijing Seeyon vs. Bangyan Technology Co | Beijing Seeyon vs. Xiandai Investment Co | Beijing Seeyon vs. Beijing Mainstreets Investment |
| Zhejiang Construction vs. Tangel Publishing | Zhejiang Construction vs. Anji Foodstuff Co | Zhejiang Construction vs. Suzhou Weizhixiang Food | Zhejiang Construction vs. Shandong Publishing Media |
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 Portfolio Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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