Correlation Between Dongfeng Automobile and Cangzhou Mingzhu
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By analyzing existing cross correlation between Dongfeng Automobile Co and Cangzhou Mingzhu Plastic, you can compare the effects of market volatilities on Dongfeng Automobile and Cangzhou Mingzhu 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 Dongfeng Automobile with a short position of Cangzhou Mingzhu. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dongfeng Automobile and Cangzhou Mingzhu.
Diversification Opportunities for Dongfeng Automobile and Cangzhou Mingzhu
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Dongfeng and Cangzhou is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding Dongfeng Automobile Co and Cangzhou Mingzhu Plastic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cangzhou Mingzhu Plastic and Dongfeng Automobile 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 Dongfeng Automobile Co are associated (or correlated) with Cangzhou Mingzhu. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cangzhou Mingzhu Plastic has no effect on the direction of Dongfeng Automobile i.e., Dongfeng Automobile and Cangzhou Mingzhu go up and down completely randomly.
Pair Corralation between Dongfeng Automobile and Cangzhou Mingzhu
Assuming the 90 days trading horizon Dongfeng Automobile Co is expected to under-perform the Cangzhou Mingzhu. In addition to that, Dongfeng Automobile is 1.94 times more volatile than Cangzhou Mingzhu Plastic. It trades about -0.19 of its total potential returns per unit of risk. Cangzhou Mingzhu Plastic is currently generating about -0.14 per unit of volatility. If you would invest 355.00 in Cangzhou Mingzhu Plastic on November 3, 2024 and sell it today you would lose (14.00) from holding Cangzhou Mingzhu Plastic or give up 3.94% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Dongfeng Automobile Co vs. Cangzhou Mingzhu Plastic
Performance |
Timeline |
Dongfeng Automobile |
Cangzhou Mingzhu Plastic |
Dongfeng Automobile and Cangzhou Mingzhu Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dongfeng Automobile and Cangzhou Mingzhu
The main advantage of trading using opposite Dongfeng Automobile and Cangzhou Mingzhu positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dongfeng Automobile position performs unexpectedly, Cangzhou Mingzhu 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 Cangzhou Mingzhu will offset losses from the drop in Cangzhou Mingzhu's long position.The idea behind Dongfeng Automobile Co and Cangzhou Mingzhu Plastic 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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
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