Correlation Between Ba Ria and Hung Hau
Can any of the company-specific risk be diversified away by investing in both Ba Ria and Hung Hau 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 Ba Ria and Hung Hau into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ba Ria Thermal and Hung Hau Agricultural, you can compare the effects of market volatilities on Ba Ria and Hung Hau 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 Ba Ria with a short position of Hung Hau. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ba Ria and Hung Hau.
Diversification Opportunities for Ba Ria and Hung Hau
Average diversification
The 3 months correlation between BTP and Hung is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding Ba Ria Thermal and Hung Hau Agricultural in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hung Hau Agricultural and Ba Ria 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 Ba Ria Thermal are associated (or correlated) with Hung Hau. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hung Hau Agricultural has no effect on the direction of Ba Ria i.e., Ba Ria and Hung Hau go up and down completely randomly.
Pair Corralation between Ba Ria and Hung Hau
Assuming the 90 days trading horizon Ba Ria Thermal is expected to generate 0.14 times more return on investment than Hung Hau. However, Ba Ria Thermal is 7.11 times less risky than Hung Hau. It trades about 0.0 of its potential returns per unit of risk. Hung Hau Agricultural is currently generating about -0.05 per unit of risk. If you would invest 1,185,000 in Ba Ria Thermal on November 9, 2024 and sell it today you would earn a total of 0.00 from holding Ba Ria Thermal or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 64.71% |
Values | Daily Returns |
Ba Ria Thermal vs. Hung Hau Agricultural
Performance |
Timeline |
Ba Ria Thermal |
Risk-Adjusted Performance
Very Weak
Weak | Strong |
Hung Hau Agricultural |
Risk-Adjusted Performance
Insignificant
Weak | Strong |
Ba Ria and Hung Hau Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ba Ria and Hung Hau
The main advantage of trading using opposite Ba Ria and Hung Hau positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ba Ria position performs unexpectedly, Hung Hau 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 Hung Hau will offset losses from the drop in Hung Hau's long position.The idea behind Ba Ria Thermal and Hung Hau Agricultural pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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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