Correlation Between Binh Duong and Tien Phong
Can any of the company-specific risk be diversified away by investing in both Binh Duong and Tien Phong 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 Binh Duong and Tien Phong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Binh Duong Construction and Tien Phong Plastic, you can compare the effects of market volatilities on Binh Duong and Tien Phong 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 Binh Duong with a short position of Tien Phong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Binh Duong and Tien Phong.
Diversification Opportunities for Binh Duong and Tien Phong
-0.41 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Binh and Tien is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding Binh Duong Construction and Tien Phong Plastic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Tien Phong Plastic and Binh Duong 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 Binh Duong Construction are associated (or correlated) with Tien Phong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Tien Phong Plastic has no effect on the direction of Binh Duong i.e., Binh Duong and Tien Phong go up and down completely randomly.
Pair Corralation between Binh Duong and Tien Phong
Assuming the 90 days trading horizon Binh Duong is expected to generate 2.75 times less return on investment than Tien Phong. But when comparing it to its historical volatility, Binh Duong Construction is 2.05 times less risky than Tien Phong. It trades about 0.06 of its potential returns per unit of risk. Tien Phong Plastic is currently generating about 0.09 of returns per unit of risk over similar time horizon. If you would invest 3,896,342 in Tien Phong Plastic on August 29, 2024 and sell it today you would earn a total of 2,003,658 from holding Tien Phong Plastic or generate 51.42% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 99.51% |
| Values | Daily Returns |
Binh Duong Construction vs. Tien Phong Plastic
Performance |
| Timeline |
| Binh Duong Construction |
| Tien Phong Plastic |
Binh Duong and Tien Phong Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Binh Duong and Tien Phong
The main advantage of trading using opposite Binh Duong and Tien Phong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Binh Duong position performs unexpectedly, Tien Phong 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 Tien Phong will offset losses from the drop in Tien Phong's long position.| Binh Duong vs. FIT INVEST JSC | Binh Duong vs. Damsan JSC | Binh Duong vs. An Phat Plastic | Binh Duong vs. Alphanam ME |
| Tien Phong vs. FIT INVEST JSC | Tien Phong vs. Damsan JSC | Tien Phong vs. An Phat Plastic | Tien Phong vs. Alphanam ME |
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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