Correlation Between Samsung Card and Sungchang Autotech
Can any of the company-specific risk be diversified away by investing in both Samsung Card and Sungchang Autotech 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 Sungchang Autotech 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 Sungchang Autotech Co, you can compare the effects of market volatilities on Samsung Card and Sungchang Autotech 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 Sungchang Autotech. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Card and Sungchang Autotech.
Diversification Opportunities for Samsung Card and Sungchang Autotech
-0.29 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Samsung and Sungchang is -0.29. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Card Co and Sungchang Autotech Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sungchang Autotech 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 Sungchang Autotech. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sungchang Autotech has no effect on the direction of Samsung Card i.e., Samsung Card and Sungchang Autotech go up and down completely randomly.
Pair Corralation between Samsung Card and Sungchang Autotech
Assuming the 90 days trading horizon Samsung Card Co is expected to under-perform the Sungchang Autotech. But the stock apears to be less risky and, when comparing its historical volatility, Samsung Card Co is 1.23 times less risky than Sungchang Autotech. The stock trades about -0.17 of its potential returns per unit of risk. The Sungchang Autotech Co is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 360,402 in Sungchang Autotech Co on October 1, 2024 and sell it today you would lose (1,902) from holding Sungchang Autotech Co or give up 0.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Card Co vs. Sungchang Autotech Co
Performance |
Timeline |
Samsung Card |
Sungchang Autotech |
Samsung Card and Sungchang Autotech Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Card and Sungchang Autotech
The main advantage of trading using opposite Samsung Card and Sungchang Autotech positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Card position performs unexpectedly, Sungchang Autotech 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 Sungchang Autotech will offset losses from the drop in Sungchang Autotech's long position.Samsung Card vs. KB Financial Group | Samsung Card vs. Hyundai Motor | Samsung Card vs. Hyundai Motor Co | Samsung Card vs. Hyundai Motor Co |
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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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