Correlation Between Samsung Card and Chorokbaem Healthcare
Can any of the company-specific risk be diversified away by investing in both Samsung Card and Chorokbaem Healthcare 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 Samsung Card and Chorokbaem Healthcare into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Card Co and Chorokbaem Healthcare Co, you can compare the effects of market volatilities on Samsung Card and Chorokbaem Healthcare 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 Samsung Card with a short position of Chorokbaem Healthcare. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Card and Chorokbaem Healthcare.
Diversification Opportunities for Samsung Card and Chorokbaem Healthcare
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Samsung and Chorokbaem is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Card Co and Chorokbaem Healthcare Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chorokbaem Healthcare and Samsung Card 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 Samsung Card Co are associated (or correlated) with Chorokbaem Healthcare. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chorokbaem Healthcare has no effect on the direction of Samsung Card i.e., Samsung Card and Chorokbaem Healthcare go up and down completely randomly.
Pair Corralation between Samsung Card and Chorokbaem Healthcare
Assuming the 90 days trading horizon Samsung Card Co is expected to generate 1.04 times more return on investment than Chorokbaem Healthcare. However, Samsung Card is 1.04 times more volatile than Chorokbaem Healthcare Co. It trades about -0.05 of its potential returns per unit of risk. Chorokbaem Healthcare Co is currently generating about -0.26 per unit of risk. If you would invest 4,520,000 in Samsung Card Co on September 3, 2024 and sell it today you would lose (250,000) from holding Samsung Card Co or give up 5.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Card Co vs. Chorokbaem Healthcare Co
Performance |
Timeline |
Samsung Card |
Chorokbaem Healthcare |
Samsung Card and Chorokbaem Healthcare Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Card and Chorokbaem Healthcare
The main advantage of trading using opposite Samsung Card and Chorokbaem Healthcare positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Card position performs unexpectedly, Chorokbaem Healthcare 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 Chorokbaem Healthcare will offset losses from the drop in Chorokbaem Healthcare's long position.Samsung Card vs. CKH Food Health | Samsung Card vs. InnoTherapy | Samsung Card vs. INNOX Advanced Materials | Samsung Card vs. LG Household Healthcare |
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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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