Correlation Between Shenzhen Centralcon and Tianjin Pengling
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By analyzing existing cross correlation between Shenzhen Centralcon Investment and Tianjin Pengling Rubber, you can compare the effects of market volatilities on Shenzhen Centralcon and Tianjin Pengling 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 Shenzhen Centralcon with a short position of Tianjin Pengling. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shenzhen Centralcon and Tianjin Pengling.
Diversification Opportunities for Shenzhen Centralcon and Tianjin Pengling
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Shenzhen and Tianjin is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding Shenzhen Centralcon Investment and Tianjin Pengling Rubber in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tianjin Pengling Rubber and Shenzhen Centralcon 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 Shenzhen Centralcon Investment are associated (or correlated) with Tianjin Pengling. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tianjin Pengling Rubber has no effect on the direction of Shenzhen Centralcon i.e., Shenzhen Centralcon and Tianjin Pengling go up and down completely randomly.
Pair Corralation between Shenzhen Centralcon and Tianjin Pengling
Assuming the 90 days trading horizon Shenzhen Centralcon Investment is expected to generate 0.94 times more return on investment than Tianjin Pengling. However, Shenzhen Centralcon Investment is 1.07 times less risky than Tianjin Pengling. It trades about 0.2 of its potential returns per unit of risk. Tianjin Pengling Rubber is currently generating about 0.15 per unit of risk. If you would invest 367.00 in Shenzhen Centralcon Investment on September 6, 2024 and sell it today you would earn a total of 163.00 from holding Shenzhen Centralcon Investment or generate 44.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Shenzhen Centralcon Investment vs. Tianjin Pengling Rubber
Performance |
Timeline |
Shenzhen Centralcon |
Tianjin Pengling Rubber |
Shenzhen Centralcon and Tianjin Pengling Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shenzhen Centralcon and Tianjin Pengling
The main advantage of trading using opposite Shenzhen Centralcon and Tianjin Pengling positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shenzhen Centralcon position performs unexpectedly, Tianjin Pengling 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 Tianjin Pengling will offset losses from the drop in Tianjin Pengling's long position.The idea behind Shenzhen Centralcon Investment and Tianjin Pengling Rubber 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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