Correlation Between Ningxia Building and Zhejiang Yinlun
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By analyzing existing cross correlation between Ningxia Building Materials and Zhejiang Yinlun Machinery, you can compare the effects of market volatilities on Ningxia Building and Zhejiang Yinlun 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 Ningxia Building with a short position of Zhejiang Yinlun. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ningxia Building and Zhejiang Yinlun.
Diversification Opportunities for Ningxia Building and Zhejiang Yinlun
-0.27 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ningxia and Zhejiang is -0.27. Overlapping area represents the amount of risk that can be diversified away by holding Ningxia Building Materials and Zhejiang Yinlun Machinery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhejiang Yinlun Machinery and Ningxia 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 Ningxia Building Materials are associated (or correlated) with Zhejiang Yinlun. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhejiang Yinlun Machinery has no effect on the direction of Ningxia Building i.e., Ningxia Building and Zhejiang Yinlun go up and down completely randomly.
Pair Corralation between Ningxia Building and Zhejiang Yinlun
Assuming the 90 days trading horizon Ningxia Building Materials is expected to under-perform the Zhejiang Yinlun. In addition to that, Ningxia Building is 1.09 times more volatile than Zhejiang Yinlun Machinery. It trades about -0.18 of its total potential returns per unit of risk. Zhejiang Yinlun Machinery is currently generating about 0.16 per unit of volatility. If you would invest 1,740 in Zhejiang Yinlun Machinery on October 14, 2024 and sell it today you would earn a total of 162.00 from holding Zhejiang Yinlun Machinery or generate 9.31% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ningxia Building Materials vs. Zhejiang Yinlun Machinery
Performance |
| Timeline |
| Ningxia Building Mat |
| Zhejiang Yinlun Machinery |
Ningxia Building and Zhejiang Yinlun Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ningxia Building and Zhejiang Yinlun
The main advantage of trading using opposite Ningxia Building and Zhejiang Yinlun positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ningxia Building position performs unexpectedly, Zhejiang Yinlun 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 Yinlun will offset losses from the drop in Zhejiang Yinlun's long position.The idea behind Ningxia Building Materials and Zhejiang Yinlun Machinery 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.
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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 Valuation module to check real value of public entities based on technical and fundamental data.
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