Correlation Between CP ALL and Airports
Specify exactly 2 symbols:
By analyzing existing cross correlation between CP ALL Public and Airports of Thailand, you can compare the effects of market volatilities on CP ALL 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 CP ALL with a short position of Airports. Check out your portfolio center. Please also check ongoing floating volatility patterns of CP ALL and Airports.
Diversification Opportunities for CP ALL and Airports
Significant diversification
The 3 months correlation between CPALL-R and Airports is 0.08. Overlapping area represents the amount of risk that can be diversified away by holding CP ALL Public 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 CP ALL 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 CP ALL Public 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 CP ALL i.e., CP ALL and Airports go up and down completely randomly.
Pair Corralation between CP ALL and Airports
Assuming the 90 days trading horizon CP ALL is expected to generate 242.66 times less return on investment than Airports. But when comparing it to its historical volatility, CP ALL Public is 49.35 times less risky than Airports. It trades about 0.01 of its potential returns per unit of risk. Airports of Thailand is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 7,432 in Airports of Thailand on August 24, 2024 and sell it today you would lose (1,282) from holding Airports of Thailand or give up 17.25% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 99.79% |
| Values | Daily Returns |
CP ALL Public vs. Airports of Thailand
Performance |
| Timeline |
| CP ALL Public |
| Airports of Thailand |
CP ALL and Airports Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with CP ALL and Airports
The main advantage of trading using opposite CP ALL and Airports positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CP ALL 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.| CP ALL vs. Airports of Thailand | CP ALL vs. CP ALL Public | CP ALL vs. Charoen Pokphand Foods | CP ALL vs. Bangkok Dusit Medical |
| Airports vs. CP ALL Public | Airports vs. PTT Public | Airports vs. Bangkok Dusit Medical | Airports vs. The Siam Cement |
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 Piotroski F Score module to get Piotroski F Score based on the binary analysis strategy of nine different fundamentals.
Other Complementary Tools
| Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
| Share Portfolio Track or share privately all of your investments from the convenience of any device | |
| USA ETFs Find actively traded Exchange Traded Funds (ETF) in USA | |
| Odds Of Bankruptcy Get analysis of equity chance of financial distress in the next 2 years | |
| Equity Valuation Check real value of public entities based on technical and fundamental data |