Correlation Between Ama Marine and Yong Concrete
Can any of the company-specific risk be diversified away by investing in both Ama Marine and Yong Concrete 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 Ama Marine and Yong Concrete into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ama Marine Public and Yong Concrete PCL, you can compare the effects of market volatilities on Ama Marine and Yong Concrete 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 Ama Marine with a short position of Yong Concrete. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ama Marine and Yong Concrete.
Diversification Opportunities for Ama Marine and Yong Concrete
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Ama and Yong is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Ama Marine Public and Yong Concrete PCL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Yong Concrete PCL and Ama Marine 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 Ama Marine Public are associated (or correlated) with Yong Concrete. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Yong Concrete PCL has no effect on the direction of Ama Marine i.e., Ama Marine and Yong Concrete go up and down completely randomly.
Pair Corralation between Ama Marine and Yong Concrete
Assuming the 90 days trading horizon Ama Marine Public is expected to generate 0.36 times more return on investment than Yong Concrete. However, Ama Marine Public is 2.81 times less risky than Yong Concrete. It trades about -0.29 of its potential returns per unit of risk. Yong Concrete PCL is currently generating about -0.24 per unit of risk. If you would invest 438.00 in Ama Marine Public on August 29, 2024 and sell it today you would lose (26.00) from holding Ama Marine Public or give up 5.94% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ama Marine Public vs. Yong Concrete PCL
Performance |
| Timeline |
| Ama Marine Public |
| Yong Concrete PCL |
Ama Marine and Yong Concrete Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ama Marine and Yong Concrete
The main advantage of trading using opposite Ama Marine and Yong Concrete positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ama Marine position performs unexpectedly, Yong Concrete 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 Yong Concrete will offset losses from the drop in Yong Concrete's long position.| Ama Marine vs. After You Public | Ama Marine vs. Akkhie Prakarn Public | Ama Marine vs. ASIA Capital Group | Ama Marine vs. The Erawan Group |
| Yong Concrete vs. Wave Entertainment Public | Yong Concrete vs. Vibhavadi Medical Center | Yong Concrete vs. TPI Polene Public | Yong Concrete vs. Asia Green Energy |
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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