Correlation Between Dongbang Ship and National Plastic
Can any of the company-specific risk be diversified away by investing in both Dongbang Ship and National Plastic 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 National Plastic 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 National Plastic Co, you can compare the effects of market volatilities on Dongbang Ship and National Plastic 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 National Plastic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dongbang Ship and National Plastic.
Diversification Opportunities for Dongbang Ship and National Plastic
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Dongbang and National is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Dongbang Ship Machinery and National Plastic Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on National Plastic 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 National Plastic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of National Plastic has no effect on the direction of Dongbang Ship i.e., Dongbang Ship and National Plastic go up and down completely randomly.
Pair Corralation between Dongbang Ship and National Plastic
Assuming the 90 days trading horizon Dongbang Ship Machinery is expected to generate 2.19 times more return on investment than National Plastic. However, Dongbang Ship is 2.19 times more volatile than National Plastic Co. It trades about 0.06 of its potential returns per unit of risk. National Plastic Co is currently generating about 0.02 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 Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Dongbang Ship Machinery vs. National Plastic Co
Performance |
Timeline |
Dongbang Ship Machinery |
National Plastic |
Dongbang Ship and National Plastic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dongbang Ship and National Plastic
The main advantage of trading using opposite Dongbang Ship and National Plastic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dongbang Ship position performs unexpectedly, National Plastic 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 National Plastic will offset losses from the drop in National Plastic'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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