Correlation Between Hochiminh City and Binh Minh
Can any of the company-specific risk be diversified away by investing in both Hochiminh City and Binh Minh 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 Hochiminh City and Binh Minh into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hochiminh City Metal and Binh Minh Plastics, you can compare the effects of market volatilities on Hochiminh City and Binh Minh 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 Hochiminh City with a short position of Binh Minh. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hochiminh City and Binh Minh.
Diversification Opportunities for Hochiminh City and Binh Minh
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Hochiminh and Binh is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Hochiminh City Metal and Binh Minh Plastics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Binh Minh Plastics and Hochiminh City 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 Hochiminh City Metal are associated (or correlated) with Binh Minh. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Binh Minh Plastics has no effect on the direction of Hochiminh City i.e., Hochiminh City and Binh Minh go up and down completely randomly.
Pair Corralation between Hochiminh City and Binh Minh
Assuming the 90 days trading horizon Hochiminh City Metal is expected to under-perform the Binh Minh. In addition to that, Hochiminh City is 1.69 times more volatile than Binh Minh Plastics. It trades about -0.31 of its total potential returns per unit of risk. Binh Minh Plastics is currently generating about -0.15 per unit of volatility. If you would invest 13,310,000 in Binh Minh Plastics on November 2, 2024 and sell it today you would lose (630,000) from holding Binh Minh Plastics or give up 4.73% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hochiminh City Metal vs. Binh Minh Plastics
Performance |
| Timeline |
| Hochiminh City Metal |
| Binh Minh Plastics |
Hochiminh City and Binh Minh Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hochiminh City and Binh Minh
The main advantage of trading using opposite Hochiminh City and Binh Minh positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hochiminh City position performs unexpectedly, Binh Minh 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 Binh Minh will offset losses from the drop in Binh Minh's long position.| Hochiminh City vs. Post and Telecommunications | Hochiminh City vs. Tien Giang Investment | Hochiminh City vs. Fecon Mining JSC | Hochiminh City vs. PV2 Investment JSC |
| Binh Minh vs. Saigon Beer Alcohol | Binh Minh vs. Cotec Construction JSC | Binh Minh vs. Petrovietnam Drilling Mud | Binh Minh vs. Hung Hau Agricultural |
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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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