Correlation Between Mena Transport and Kiattana Transport
Can any of the company-specific risk be diversified away by investing in both Mena Transport and Kiattana Transport 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 Mena Transport and Kiattana Transport into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mena Transport Public and Kiattana Transport Public, you can compare the effects of market volatilities on Mena Transport and Kiattana Transport 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 Mena Transport with a short position of Kiattana Transport. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mena Transport and Kiattana Transport.
Diversification Opportunities for Mena Transport and Kiattana Transport
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Mena and Kiattana is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Mena Transport Public and Kiattana Transport Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kiattana Transport Public and Mena Transport 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 Mena Transport Public are associated (or correlated) with Kiattana Transport. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kiattana Transport Public has no effect on the direction of Mena Transport i.e., Mena Transport and Kiattana Transport go up and down completely randomly.
Pair Corralation between Mena Transport and Kiattana Transport
Assuming the 90 days trading horizon Mena Transport Public is expected to under-perform the Kiattana Transport. In addition to that, Mena Transport is 1.04 times more volatile than Kiattana Transport Public. It trades about -0.03 of its total potential returns per unit of risk. Kiattana Transport Public is currently generating about -0.01 per unit of volatility. If you would invest 31.00 in Kiattana Transport Public on December 23, 2024 and sell it today you would lose (1.00) from holding Kiattana Transport Public or give up 3.23% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Mena Transport Public vs. Kiattana Transport Public
Performance |
Timeline |
Mena Transport Public |
Kiattana Transport Public |
Mena Transport and Kiattana Transport Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mena Transport and Kiattana Transport
The main advantage of trading using opposite Mena Transport and Kiattana Transport positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mena Transport position performs unexpectedly, Kiattana Transport 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 Kiattana Transport will offset losses from the drop in Kiattana Transport's long position.Mena Transport vs. Mono Next Public | Mena Transport vs. Triple i Logistics | Mena Transport vs. Dynasty Ceramic Public |
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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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