Correlation Between SOOSAN INT and Ssangyong Information
Can any of the company-specific risk be diversified away by investing in both SOOSAN INT and Ssangyong Information 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 SOOSAN INT and Ssangyong Information into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SOOSAN INT Co and Ssangyong Information Communication, you can compare the effects of market volatilities on SOOSAN INT and Ssangyong Information 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 SOOSAN INT with a short position of Ssangyong Information. Check out your portfolio center. Please also check ongoing floating volatility patterns of SOOSAN INT and Ssangyong Information.
Diversification Opportunities for SOOSAN INT and Ssangyong Information
0.35 | Correlation Coefficient |
Weak diversification
The 3 months correlation between SOOSAN and Ssangyong is 0.35. Overlapping area represents the amount of risk that can be diversified away by holding SOOSAN INT Co and Ssangyong Information Communic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ssangyong Information and SOOSAN INT 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 SOOSAN INT Co are associated (or correlated) with Ssangyong Information. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ssangyong Information has no effect on the direction of SOOSAN INT i.e., SOOSAN INT and Ssangyong Information go up and down completely randomly.
Pair Corralation between SOOSAN INT and Ssangyong Information
Assuming the 90 days trading horizon SOOSAN INT Co is expected to generate 2.64 times more return on investment than Ssangyong Information. However, SOOSAN INT is 2.64 times more volatile than Ssangyong Information Communication. It trades about 0.5 of its potential returns per unit of risk. Ssangyong Information Communication is currently generating about 0.24 per unit of risk. If you would invest 1,390,000 in SOOSAN INT Co on November 27, 2024 and sell it today you would earn a total of 355,000 from holding SOOSAN INT Co or generate 25.54% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
SOOSAN INT Co vs. Ssangyong Information Communic
Performance |
Timeline |
SOOSAN INT |
Ssangyong Information |
SOOSAN INT and Ssangyong Information Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SOOSAN INT and Ssangyong Information
The main advantage of trading using opposite SOOSAN INT and Ssangyong Information positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SOOSAN INT position performs unexpectedly, Ssangyong Information 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 Ssangyong Information will offset losses from the drop in Ssangyong Information's long position.SOOSAN INT vs. Korea Shipbuilding Offshore | SOOSAN INT vs. InnoTherapy | SOOSAN INT vs. FOODWELL Co | SOOSAN INT 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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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