Correlation Between Dongbang Ship and Semyung Electric
Can any of the company-specific risk be diversified away by investing in both Dongbang Ship and Semyung Electric 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 Dongbang Ship and Semyung Electric into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dongbang Ship Machinery and Semyung Electric Machinery, you can compare the effects of market volatilities on Dongbang Ship and Semyung Electric 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 Dongbang Ship with a short position of Semyung Electric. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dongbang Ship and Semyung Electric.
Diversification Opportunities for Dongbang Ship and Semyung Electric
-0.61 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Dongbang and Semyung is -0.61. Overlapping area represents the amount of risk that can be diversified away by holding Dongbang Ship Machinery and Semyung Electric Machinery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Semyung Electric Mac and Dongbang Ship 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 Dongbang Ship Machinery are associated (or correlated) with Semyung Electric. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Semyung Electric Mac has no effect on the direction of Dongbang Ship i.e., Dongbang Ship and Semyung Electric go up and down completely randomly.
Pair Corralation between Dongbang Ship and Semyung Electric
Assuming the 90 days trading horizon Dongbang Ship Machinery is expected to generate 0.77 times more return on investment than Semyung Electric. However, Dongbang Ship Machinery is 1.29 times less risky than Semyung Electric. It trades about 0.06 of its potential returns per unit of risk. Semyung Electric Machinery is currently generating about -0.1 per unit of risk. If you would invest 252,500 in Dongbang Ship Machinery on September 4, 2024 and sell it today you would earn a total of 19,500 from holding Dongbang Ship Machinery or generate 7.72% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Dongbang Ship Machinery vs. Semyung Electric Machinery
Performance |
Timeline |
Dongbang Ship Machinery |
Semyung Electric Mac |
Dongbang Ship and Semyung Electric Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dongbang Ship and Semyung Electric
The main advantage of trading using opposite Dongbang Ship and Semyung Electric positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dongbang Ship position performs unexpectedly, Semyung Electric 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 Semyung Electric will offset losses from the drop in Semyung Electric's long position.Dongbang Ship vs. LG Display | Dongbang Ship vs. Hyundai Motor | Dongbang Ship vs. Hyundai Motor Co | Dongbang Ship 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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