Correlation Between Da Nang and Picomat Plastic
Can any of the company-specific risk be diversified away by investing in both Da Nang and Picomat Plastic at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Da Nang and Picomat Plastic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Da Nang Construction and Picomat Plastic JSC, you can compare the effects of market volatilities on Da Nang and Picomat Plastic 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 Da Nang with a short position of Picomat Plastic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Da Nang and Picomat Plastic.
Diversification Opportunities for Da Nang and Picomat Plastic
-0.19 | Correlation Coefficient |
Good diversification
The 3 months correlation between DXV and Picomat is -0.19. Overlapping area represents the amount of risk that can be diversified away by holding Da Nang Construction and Picomat Plastic JSC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Picomat Plastic JSC and Da Nang 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 Da Nang Construction are associated (or correlated) with Picomat Plastic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Picomat Plastic JSC has no effect on the direction of Da Nang i.e., Da Nang and Picomat Plastic go up and down completely randomly.
Pair Corralation between Da Nang and Picomat Plastic
Assuming the 90 days trading horizon Da Nang is expected to generate 1.09 times less return on investment than Picomat Plastic. In addition to that, Da Nang is 1.32 times more volatile than Picomat Plastic JSC. It trades about 0.07 of its total potential returns per unit of risk. Picomat Plastic JSC is currently generating about 0.1 per unit of volatility. If you would invest 1,260,000 in Picomat Plastic JSC on October 25, 2024 and sell it today you would earn a total of 60,000 from holding Picomat Plastic JSC or generate 4.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 95.45% |
Values | Daily Returns |
Da Nang Construction vs. Picomat Plastic JSC
Performance |
Timeline |
Da Nang Construction |
Picomat Plastic JSC |
Da Nang and Picomat Plastic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Da Nang and Picomat Plastic
The main advantage of trading using opposite Da Nang and Picomat Plastic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Da Nang position performs unexpectedly, Picomat Plastic 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 Picomat Plastic will offset losses from the drop in Picomat Plastic's long position.Da Nang vs. FIT INVEST JSC | Da Nang vs. Damsan JSC | Da Nang vs. An Phat Plastic | Da Nang vs. APG Securities Joint |
Picomat Plastic vs. FIT INVEST JSC | Picomat Plastic vs. Damsan JSC | Picomat Plastic vs. An Phat Plastic | Picomat Plastic vs. APG Securities Joint |
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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