Correlation Between Viettel Construction and Long An
Can any of the company-specific risk be diversified away by investing in both Viettel Construction and Long An 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 Viettel Construction and Long An into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Viettel Construction JSC and Long An Food, you can compare the effects of market volatilities on Viettel Construction and Long An 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 Viettel Construction with a short position of Long An. Check out your portfolio center. Please also check ongoing floating volatility patterns of Viettel Construction and Long An.
Diversification Opportunities for Viettel Construction and Long An
-0.38 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Viettel and Long is -0.38. Overlapping area represents the amount of risk that can be diversified away by holding Viettel Construction JSC and Long An Food in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Long An Food and Viettel Construction 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 Viettel Construction JSC are associated (or correlated) with Long An. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Long An Food has no effect on the direction of Viettel Construction i.e., Viettel Construction and Long An go up and down completely randomly.
Pair Corralation between Viettel Construction and Long An
Assuming the 90 days trading horizon Viettel Construction JSC is expected to generate 0.85 times more return on investment than Long An. However, Viettel Construction JSC is 1.17 times less risky than Long An. It trades about 0.09 of its potential returns per unit of risk. Long An Food is currently generating about 0.06 per unit of risk. If you would invest 5,076,104 in Viettel Construction JSC on October 4, 2024 and sell it today you would earn a total of 7,373,896 from holding Viettel Construction JSC or generate 145.27% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 87.6% |
Values | Daily Returns |
Viettel Construction JSC vs. Long An Food
Performance |
Timeline |
Viettel Construction JSC |
Long An Food |
Viettel Construction and Long An Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Viettel Construction and Long An
The main advantage of trading using opposite Viettel Construction and Long An positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Viettel Construction position performs unexpectedly, Long An 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 Long An will offset losses from the drop in Long An's long position.Viettel Construction vs. FIT INVEST JSC | Viettel Construction vs. Damsan JSC | Viettel Construction vs. An Phat Plastic | Viettel Construction vs. APG Securities Joint |
Long An vs. FIT INVEST JSC | Long An vs. Damsan JSC | Long An vs. An Phat Plastic | Long An 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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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