Correlation Between Aqua Public and Bangkok Aviation
Can any of the company-specific risk be diversified away by investing in both Aqua Public and Bangkok Aviation 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 Aqua Public and Bangkok Aviation into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Aqua Public and Bangkok Aviation Fuel, you can compare the effects of market volatilities on Aqua Public and Bangkok Aviation 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 Aqua Public with a short position of Bangkok Aviation. Check out your portfolio center. Please also check ongoing floating volatility patterns of Aqua Public and Bangkok Aviation.
Diversification Opportunities for Aqua Public and Bangkok Aviation
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Aqua and Bangkok is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding Aqua Public and Bangkok Aviation Fuel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bangkok Aviation Fuel and Aqua Public 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 Aqua Public are associated (or correlated) with Bangkok Aviation. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bangkok Aviation Fuel has no effect on the direction of Aqua Public i.e., Aqua Public and Bangkok Aviation go up and down completely randomly.
Pair Corralation between Aqua Public and Bangkok Aviation
Assuming the 90 days trading horizon Aqua Public is expected to generate 0.96 times more return on investment than Bangkok Aviation. However, Aqua Public is 1.04 times less risky than Bangkok Aviation. It trades about -0.09 of its potential returns per unit of risk. Bangkok Aviation Fuel is currently generating about -0.25 per unit of risk. If you would invest 37.00 in Aqua Public on September 3, 2024 and sell it today you would lose (3.00) from holding Aqua Public or give up 8.11% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Aqua Public vs. Bangkok Aviation Fuel
Performance |
| Timeline |
| Aqua Public |
| Bangkok Aviation Fuel |
Aqua Public and Bangkok Aviation Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Aqua Public and Bangkok Aviation
The main advantage of trading using opposite Aqua Public and Bangkok Aviation positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Aqua Public position performs unexpectedly, Bangkok Aviation 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 Bangkok Aviation will offset losses from the drop in Bangkok Aviation's long position.| Aqua Public vs. Big Camera | Aqua Public vs. Bangkok Chain Hospital | Aqua Public vs. Grande Asset Hotels | Aqua Public vs. Better World Green |
| Bangkok Aviation vs. Bangchak Public | Bangkok Aviation vs. Airports of Thailand | Bangkok Aviation vs. AP Public | Bangkok Aviation vs. Central Pattana Public |
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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