Correlation Between Maoming Petro and Beijing Jiaman
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By analyzing existing cross correlation between Maoming Petro Chemical Shihua and Beijing Jiaman Dress, you can compare the effects of market volatilities on Maoming Petro and Beijing Jiaman 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 Maoming Petro with a short position of Beijing Jiaman. Check out your portfolio center. Please also check ongoing floating volatility patterns of Maoming Petro and Beijing Jiaman.
Diversification Opportunities for Maoming Petro and Beijing Jiaman
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Maoming and Beijing is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Maoming Petro Chemical Shihua and Beijing Jiaman Dress in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Beijing Jiaman Dress and Maoming Petro 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 Maoming Petro Chemical Shihua are associated (or correlated) with Beijing Jiaman. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Beijing Jiaman Dress has no effect on the direction of Maoming Petro i.e., Maoming Petro and Beijing Jiaman go up and down completely randomly.
Pair Corralation between Maoming Petro and Beijing Jiaman
Assuming the 90 days trading horizon Maoming Petro Chemical Shihua is expected to generate 0.8 times more return on investment than Beijing Jiaman. However, Maoming Petro Chemical Shihua is 1.26 times less risky than Beijing Jiaman. It trades about 0.09 of its potential returns per unit of risk. Beijing Jiaman Dress is currently generating about 0.06 per unit of risk. If you would invest 355.00 in Maoming Petro Chemical Shihua on November 7, 2024 and sell it today you would earn a total of 8.00 from holding Maoming Petro Chemical Shihua or generate 2.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Maoming Petro Chemical Shihua vs. Beijing Jiaman Dress
Performance |
| Timeline |
| Maoming Petro Chemical |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| Beijing Jiaman Dress |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Maoming Petro and Beijing Jiaman Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Maoming Petro and Beijing Jiaman
The main advantage of trading using opposite Maoming Petro and Beijing Jiaman positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Maoming Petro position performs unexpectedly, Beijing Jiaman 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 Beijing Jiaman will offset losses from the drop in Beijing Jiaman's long position.The idea behind Maoming Petro Chemical Shihua and Beijing Jiaman Dress 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.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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