Correlation Between Zhejiang Qianjiang and Shenzhen Clou
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By analyzing existing cross correlation between Zhejiang Qianjiang Motorcycle and Shenzhen Clou Electronics, you can compare the effects of market volatilities on Zhejiang Qianjiang and Shenzhen Clou 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 Zhejiang Qianjiang with a short position of Shenzhen Clou. Check out your portfolio center. Please also check ongoing floating volatility patterns of Zhejiang Qianjiang and Shenzhen Clou.
Diversification Opportunities for Zhejiang Qianjiang and Shenzhen Clou
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Zhejiang and Shenzhen is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Zhejiang Qianjiang Motorcycle and Shenzhen Clou Electronics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shenzhen Clou Electronics and Zhejiang Qianjiang 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 Zhejiang Qianjiang Motorcycle are associated (or correlated) with Shenzhen Clou. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shenzhen Clou Electronics has no effect on the direction of Zhejiang Qianjiang i.e., Zhejiang Qianjiang and Shenzhen Clou go up and down completely randomly.
Pair Corralation between Zhejiang Qianjiang and Shenzhen Clou
Assuming the 90 days trading horizon Zhejiang Qianjiang Motorcycle is expected to under-perform the Shenzhen Clou. But the stock apears to be less risky and, when comparing its historical volatility, Zhejiang Qianjiang Motorcycle is 1.34 times less risky than Shenzhen Clou. The stock trades about -0.13 of its potential returns per unit of risk. The Shenzhen Clou Electronics is currently generating about 0.19 of returns per unit of risk over similar time horizon. If you would invest 417.00 in Shenzhen Clou Electronics on August 25, 2024 and sell it today you would earn a total of 56.00 from holding Shenzhen Clou Electronics or generate 13.43% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 95.65% |
| Values | Daily Returns |
Zhejiang Qianjiang Motorcycle vs. Shenzhen Clou Electronics
Performance |
| Timeline |
| Zhejiang Qianjiang |
| Shenzhen Clou Electronics |
Zhejiang Qianjiang and Shenzhen Clou Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Zhejiang Qianjiang and Shenzhen Clou
The main advantage of trading using opposite Zhejiang Qianjiang and Shenzhen Clou positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Zhejiang Qianjiang position performs unexpectedly, Shenzhen Clou 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 Shenzhen Clou will offset losses from the drop in Shenzhen Clou's long position.| Zhejiang Qianjiang vs. Chengdu Kanghua Biological | Zhejiang Qianjiang vs. Beijing Wantai Biological | Zhejiang Qianjiang vs. Suzhou Novoprotein Scientific | Zhejiang Qianjiang vs. Aluminum Corp of |
| Shenzhen Clou vs. Sunwave Communications Co | Shenzhen Clou vs. Zhejiang Qianjiang Motorcycle | Shenzhen Clou vs. Chongqing Brewery Co | Shenzhen Clou vs. State Grid InformationCommunication |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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