Correlation Between Semyung Electric and Koryo Credit
Can any of the company-specific risk be diversified away by investing in both Semyung Electric and Koryo Credit 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 Semyung Electric and Koryo Credit into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Semyung Electric Machinery and Koryo Credit Information, you can compare the effects of market volatilities on Semyung Electric and Koryo Credit 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 Semyung Electric with a short position of Koryo Credit. Check out your portfolio center. Please also check ongoing floating volatility patterns of Semyung Electric and Koryo Credit.
Diversification Opportunities for Semyung Electric and Koryo Credit
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Semyung and Koryo is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Semyung Electric Machinery and Koryo Credit Information in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Koryo Credit Information and Semyung Electric 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 Semyung Electric Machinery are associated (or correlated) with Koryo Credit. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Koryo Credit Information has no effect on the direction of Semyung Electric i.e., Semyung Electric and Koryo Credit go up and down completely randomly.
Pair Corralation between Semyung Electric and Koryo Credit
Assuming the 90 days trading horizon Semyung Electric Machinery is expected to generate 4.89 times more return on investment than Koryo Credit. However, Semyung Electric is 4.89 times more volatile than Koryo Credit Information. It trades about 0.06 of its potential returns per unit of risk. Koryo Credit Information is currently generating about 0.06 per unit of risk. If you would invest 277,975 in Semyung Electric Machinery on September 2, 2024 and sell it today you would earn a total of 169,525 from holding Semyung Electric Machinery or generate 60.99% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Semyung Electric Machinery vs. Koryo Credit Information
Performance |
Timeline |
Semyung Electric Mac |
Koryo Credit Information |
Semyung Electric and Koryo Credit Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Semyung Electric and Koryo Credit
The main advantage of trading using opposite Semyung Electric and Koryo Credit positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Semyung Electric position performs unexpectedly, Koryo Credit 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 Koryo Credit will offset losses from the drop in Koryo Credit's long position.Semyung Electric vs. Dawonsys CoLtd | Semyung Electric vs. Robostar CoLtd | Semyung Electric vs. Daebo Magnetic CoLtd | Semyung Electric vs. Vitzro Tech 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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