Correlation Between Mega Lifesciences and TAC Consumer
Can any of the company-specific risk be diversified away by investing in both Mega Lifesciences and TAC Consumer 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 Mega Lifesciences and TAC Consumer into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mega Lifesciences Public and TAC Consumer Public, you can compare the effects of market volatilities on Mega Lifesciences and TAC Consumer 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 Mega Lifesciences with a short position of TAC Consumer. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mega Lifesciences and TAC Consumer.
Diversification Opportunities for Mega Lifesciences and TAC Consumer
0.59 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Mega and TAC is 0.59. Overlapping area represents the amount of risk that can be diversified away by holding Mega Lifesciences Public and TAC Consumer Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TAC Consumer Public and Mega Lifesciences 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 Mega Lifesciences Public are associated (or correlated) with TAC Consumer. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TAC Consumer Public has no effect on the direction of Mega Lifesciences i.e., Mega Lifesciences and TAC Consumer go up and down completely randomly.
Pair Corralation between Mega Lifesciences and TAC Consumer
Assuming the 90 days trading horizon Mega Lifesciences Public is expected to under-perform the TAC Consumer. In addition to that, Mega Lifesciences is 1.31 times more volatile than TAC Consumer Public. It trades about -0.34 of its total potential returns per unit of risk. TAC Consumer Public is currently generating about -0.17 per unit of volatility. If you would invest 488.00 in TAC Consumer Public on August 25, 2024 and sell it today you would lose (18.00) from holding TAC Consumer Public or give up 3.69% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mega Lifesciences Public vs. TAC Consumer Public
Performance |
Timeline |
Mega Lifesciences Public |
TAC Consumer Public |
Mega Lifesciences and TAC Consumer Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mega Lifesciences and TAC Consumer
The main advantage of trading using opposite Mega Lifesciences and TAC Consumer positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mega Lifesciences position performs unexpectedly, TAC Consumer 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 TAC Consumer will offset losses from the drop in TAC Consumer's long position.Mega Lifesciences vs. Chularat Hospital Public | Mega Lifesciences vs. Ekachai Medical Care | Mega Lifesciences vs. Bangkok Chain Hospital | Mega Lifesciences vs. Srivichaivejvivat 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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