Correlation Between Moong Pattana and Airports
Can any of the company-specific risk be diversified away by investing in both Moong Pattana and Airports 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 Moong Pattana and Airports into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Moong Pattana International and Airports of Thailand, you can compare the effects of market volatilities on Moong Pattana and Airports 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 Moong Pattana with a short position of Airports. Check out your portfolio center. Please also check ongoing floating volatility patterns of Moong Pattana and Airports.
Diversification Opportunities for Moong Pattana and Airports
0.24 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Moong and Airports is 0.24. Overlapping area represents the amount of risk that can be diversified away by holding Moong Pattana International and Airports of Thailand in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Airports of Thailand and Moong Pattana 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 Moong Pattana International are associated (or correlated) with Airports. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Airports of Thailand has no effect on the direction of Moong Pattana i.e., Moong Pattana and Airports go up and down completely randomly.
Pair Corralation between Moong Pattana and Airports
Assuming the 90 days trading horizon Moong Pattana International is expected to generate 66.38 times more return on investment than Airports. However, Moong Pattana is 66.38 times more volatile than Airports of Thailand. It trades about 0.07 of its potential returns per unit of risk. Airports of Thailand is currently generating about -0.02 per unit of risk. If you would invest 207.00 in Moong Pattana International on September 1, 2024 and sell it today you would earn a total of 7.00 from holding Moong Pattana International or generate 3.38% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 99.45% |
| Values | Daily Returns |
Moong Pattana International vs. Airports of Thailand
Performance |
| Timeline |
| Moong Pattana Intern |
| Airports of Thailand |
Moong Pattana and Airports Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Moong Pattana and Airports
The main advantage of trading using opposite Moong Pattana and Airports positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Moong Pattana position performs unexpectedly, Airports 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 Airports will offset losses from the drop in Airports' long position.| Moong Pattana vs. Metro Systems | Moong Pattana vs. Mega Lifesciences Public | Moong Pattana vs. Hana Microelectronics Public | Moong Pattana vs. Karmarts Public |
| Airports vs. CP ALL Public | Airports vs. PTT Public | Airports vs. Kasikornbank Public | Airports vs. Bangkok Dusit Medical |
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 Bollinger Bands module to use Bollinger Bands indicator to analyze target price for a given investing horizon.
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