Correlation Between Airports and Taokaenoi Food
Can any of the company-specific risk be diversified away by investing in both Airports and Taokaenoi Food 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 Airports and Taokaenoi Food into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Airports of Thailand and Taokaenoi Food Marketing, you can compare the effects of market volatilities on Airports and Taokaenoi Food 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 Airports with a short position of Taokaenoi Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Airports and Taokaenoi Food.
Diversification Opportunities for Airports and Taokaenoi Food
0.37 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Airports and Taokaenoi is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding Airports of Thailand and Taokaenoi Food Marketing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Taokaenoi Food Marketing and Airports 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 Airports of Thailand are associated (or correlated) with Taokaenoi Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Taokaenoi Food Marketing has no effect on the direction of Airports i.e., Airports and Taokaenoi Food go up and down completely randomly.
Pair Corralation between Airports and Taokaenoi Food
Assuming the 90 days trading horizon Airports of Thailand is expected to generate 0.48 times more return on investment than Taokaenoi Food. However, Airports of Thailand is 2.08 times less risky than Taokaenoi Food. It trades about -0.01 of its potential returns per unit of risk. Taokaenoi Food Marketing is currently generating about -0.38 per unit of risk. If you would invest 6,225 in Airports of Thailand on September 5, 2024 and sell it today you would lose (25.00) from holding Airports of Thailand or give up 0.4% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Airports of Thailand vs. Taokaenoi Food Marketing
Performance |
Timeline |
Airports of Thailand |
Taokaenoi Food Marketing |
Airports and Taokaenoi Food Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Airports and Taokaenoi Food
The main advantage of trading using opposite Airports and Taokaenoi Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Airports position performs unexpectedly, Taokaenoi Food 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 Taokaenoi Food will offset losses from the drop in Taokaenoi Food's long position.Airports vs. CP ALL Public | Airports vs. PTT Public | Airports vs. Kasikornbank Public | Airports vs. Bangkok Dusit Medical |
Taokaenoi Food vs. Airports of Thailand | Taokaenoi Food vs. PTT Public | Taokaenoi Food vs. Bangkok Dusit Medical | Taokaenoi Food vs. Kasikornbank 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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