Correlation Between Great China and Mega Financial
Can any of the company-specific risk be diversified away by investing in both Great China and Mega Financial 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 Great China and Mega Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Great China Metal and Mega Financial Holding, you can compare the effects of market volatilities on Great China and Mega Financial 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 Great China with a short position of Mega Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great China and Mega Financial.
Diversification Opportunities for Great China and Mega Financial
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Great and Mega is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding Great China Metal and Mega Financial Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mega Financial Holding and Great China 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 Great China Metal are associated (or correlated) with Mega Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mega Financial Holding has no effect on the direction of Great China i.e., Great China and Mega Financial go up and down completely randomly.
Pair Corralation between Great China and Mega Financial
Assuming the 90 days trading horizon Great China Metal is expected to under-perform the Mega Financial. But the stock apears to be less risky and, when comparing its historical volatility, Great China Metal is 2.0 times less risky than Mega Financial. The stock trades about -0.01 of its potential returns per unit of risk. The Mega Financial Holding is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 3,940 in Mega Financial Holding on September 17, 2024 and sell it today you would earn a total of 10.00 from holding Mega Financial Holding or generate 0.25% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 98.44% |
Values | Daily Returns |
Great China Metal vs. Mega Financial Holding
Performance |
Timeline |
Great China Metal |
Mega Financial Holding |
Great China and Mega Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Great China and Mega Financial
The main advantage of trading using opposite Great China and Mega Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great China position performs unexpectedly, Mega Financial 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 Financial will offset losses from the drop in Mega Financial's long position.Great China vs. Taiwan Hon Chuan | Great China vs. Taiwan Secom Co | Great China vs. Taiwan Fu Hsing | Great China vs. Taiwan Shin Kong |
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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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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