Correlation Between DB Insurance and Seoam Machinery
Can any of the company-specific risk be diversified away by investing in both DB Insurance and Seoam Machinery 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 DB Insurance and Seoam Machinery into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DB Insurance Co and Seoam Machinery Industry, you can compare the effects of market volatilities on DB Insurance and Seoam Machinery 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 DB Insurance with a short position of Seoam Machinery. Check out your portfolio center. Please also check ongoing floating volatility patterns of DB Insurance and Seoam Machinery.
Diversification Opportunities for DB Insurance and Seoam Machinery
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between 005830 and Seoam is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding DB Insurance Co and Seoam Machinery Industry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Seoam Machinery Industry and DB Insurance 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 DB Insurance Co are associated (or correlated) with Seoam Machinery. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Seoam Machinery Industry has no effect on the direction of DB Insurance i.e., DB Insurance and Seoam Machinery go up and down completely randomly.
Pair Corralation between DB Insurance and Seoam Machinery
Assuming the 90 days trading horizon DB Insurance Co is expected to under-perform the Seoam Machinery. In addition to that, DB Insurance is 1.11 times more volatile than Seoam Machinery Industry. It trades about -0.06 of its total potential returns per unit of risk. Seoam Machinery Industry is currently generating about 0.33 per unit of volatility. If you would invest 337,152 in Seoam Machinery Industry on October 11, 2024 and sell it today you would earn a total of 42,348 from holding Seoam Machinery Industry or generate 12.56% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
DB Insurance Co vs. Seoam Machinery Industry
Performance |
Timeline |
DB Insurance |
Seoam Machinery Industry |
DB Insurance and Seoam Machinery Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with DB Insurance and Seoam Machinery
The main advantage of trading using opposite DB Insurance and Seoam Machinery positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DB Insurance position performs unexpectedly, Seoam Machinery 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 Seoam Machinery will offset losses from the drop in Seoam Machinery's long position.DB Insurance vs. SK Chemicals Co | DB Insurance vs. Eugene Technology CoLtd | DB Insurance vs. Neungyule Education | DB Insurance vs. Hannong Chemicals |
Seoam Machinery vs. Homecast CoLtd | Seoam Machinery vs. CJ Seafood Corp | Seoam Machinery vs. KT Submarine Telecom | Seoam Machinery vs. Samlip General Foods |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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