Correlation Between Binh Duong and Saigon Viendong
Can any of the company-specific risk be diversified away by investing in both Binh Duong and Saigon Viendong 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 Saigon Viendong into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Binh Duong Trade and Saigon Viendong Technology, you can compare the effects of market volatilities on Binh Duong and Saigon Viendong 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 Saigon Viendong. Check out your portfolio center. Please also check ongoing floating volatility patterns of Binh Duong and Saigon Viendong.
Diversification Opportunities for Binh Duong and Saigon Viendong
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Binh and Saigon is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding Binh Duong Trade and Saigon Viendong Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Saigon Viendong Tech 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 Trade are associated (or correlated) with Saigon Viendong. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Saigon Viendong Tech has no effect on the direction of Binh Duong i.e., Binh Duong and Saigon Viendong go up and down completely randomly.
Pair Corralation between Binh Duong and Saigon Viendong
Assuming the 90 days trading horizon Binh Duong Trade is expected to generate 0.62 times more return on investment than Saigon Viendong. However, Binh Duong Trade is 1.61 times less risky than Saigon Viendong. It trades about 0.31 of its potential returns per unit of risk. Saigon Viendong Technology is currently generating about 0.11 per unit of risk. If you would invest 1,020,000 in Binh Duong Trade on September 29, 2024 and sell it today you would earn a total of 110,000 from holding Binh Duong Trade or generate 10.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 91.3% |
Values | Daily Returns |
Binh Duong Trade vs. Saigon Viendong Technology
Performance |
Timeline |
Binh Duong Trade |
Saigon Viendong Tech |
Binh Duong and Saigon Viendong Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Binh Duong and Saigon Viendong
The main advantage of trading using opposite Binh Duong and Saigon Viendong positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Binh Duong position performs unexpectedly, Saigon Viendong 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 Saigon Viendong will offset losses from the drop in Saigon Viendong'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 |
Saigon Viendong vs. FIT INVEST JSC | Saigon Viendong vs. Damsan JSC | Saigon Viendong vs. An Phat Plastic | Saigon Viendong 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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