Correlation Between SM Entertainment and SHINWON STRUCTION
Can any of the company-specific risk be diversified away by investing in both SM Entertainment and SHINWON STRUCTION 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 SM Entertainment and SHINWON STRUCTION into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SM Entertainment Co and SHINWON STRUCTION COMPANY, you can compare the effects of market volatilities on SM Entertainment and SHINWON STRUCTION 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 SM Entertainment with a short position of SHINWON STRUCTION. Check out your portfolio center. Please also check ongoing floating volatility patterns of SM Entertainment and SHINWON STRUCTION.
Diversification Opportunities for SM Entertainment and SHINWON STRUCTION
-0.82 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between 041510 and SHINWON is -0.82. Overlapping area represents the amount of risk that can be diversified away by holding SM Entertainment Co and SHINWON STRUCTION COMPANY in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SHINWON STRUCTION PANY and SM Entertainment 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 SM Entertainment Co are associated (or correlated) with SHINWON STRUCTION. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SHINWON STRUCTION PANY has no effect on the direction of SM Entertainment i.e., SM Entertainment and SHINWON STRUCTION go up and down completely randomly.
Pair Corralation between SM Entertainment and SHINWON STRUCTION
Assuming the 90 days trading horizon SM Entertainment Co is expected to generate 0.56 times more return on investment than SHINWON STRUCTION. However, SM Entertainment Co is 1.78 times less risky than SHINWON STRUCTION. It trades about 0.2 of its potential returns per unit of risk. SHINWON STRUCTION COMPANY is currently generating about -0.05 per unit of risk. If you would invest 5,880,000 in SM Entertainment Co on September 16, 2024 and sell it today you would earn a total of 2,220,000 from holding SM Entertainment Co or generate 37.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
SM Entertainment Co vs. SHINWON STRUCTION COMPANY
Performance |
Timeline |
SM Entertainment |
SHINWON STRUCTION PANY |
SM Entertainment and SHINWON STRUCTION Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SM Entertainment and SHINWON STRUCTION
The main advantage of trading using opposite SM Entertainment and SHINWON STRUCTION positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SM Entertainment position performs unexpectedly, SHINWON STRUCTION 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 SHINWON STRUCTION will offset losses from the drop in SHINWON STRUCTION's long position.SM Entertainment vs. JYP Entertainment | SM Entertainment vs. Cube Entertainment | SM Entertainment vs. FNC Entertainment 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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