Correlation Between Thai Union and Mega Lifesciences
Can any of the company-specific risk be diversified away by investing in both Thai Union and Mega Lifesciences 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 Thai Union and Mega Lifesciences into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Thai Union Group and Mega Lifesciences Public, you can compare the effects of market volatilities on Thai Union and Mega Lifesciences 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 Thai Union with a short position of Mega Lifesciences. Check out your portfolio center. Please also check ongoing floating volatility patterns of Thai Union and Mega Lifesciences.
Diversification Opportunities for Thai Union and Mega Lifesciences
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Thai and Mega is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Thai Union Group and Mega Lifesciences Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mega Lifesciences Public and Thai Union 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 Thai Union Group are associated (or correlated) with Mega Lifesciences. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mega Lifesciences Public has no effect on the direction of Thai Union i.e., Thai Union and Mega Lifesciences go up and down completely randomly.
Pair Corralation between Thai Union and Mega Lifesciences
Assuming the 90 days horizon Thai Union Group is expected to under-perform the Mega Lifesciences. But the stock apears to be less risky and, when comparing its historical volatility, Thai Union Group is 1.15 times less risky than Mega Lifesciences. The stock trades about -0.1 of its potential returns per unit of risk. The Mega Lifesciences Public is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 3,275 in Mega Lifesciences Public on December 29, 2024 and sell it today you would lose (225.00) from holding Mega Lifesciences Public or give up 6.87% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Thai Union Group vs. Mega Lifesciences Public
Performance |
Timeline |
Thai Union Group |
Mega Lifesciences Public |
Thai Union and Mega Lifesciences Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Thai Union and Mega Lifesciences
The main advantage of trading using opposite Thai Union and Mega Lifesciences positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Thai Union position performs unexpectedly, Mega Lifesciences 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 Mega Lifesciences will offset losses from the drop in Mega Lifesciences' long position.Thai Union vs. Charoen Pokphand Foods | Thai Union vs. CP ALL Public | Thai Union vs. Minor International Public | Thai Union vs. Advanced Info Service |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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