Correlation Between Incar Financial and Dongbang Ship
Can any of the company-specific risk be diversified away by investing in both Incar Financial and Dongbang Ship 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 Incar Financial and Dongbang Ship into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Incar Financial Service and Dongbang Ship Machinery, you can compare the effects of market volatilities on Incar Financial and Dongbang Ship 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 Incar Financial with a short position of Dongbang Ship. Check out your portfolio center. Please also check ongoing floating volatility patterns of Incar Financial and Dongbang Ship.
Diversification Opportunities for Incar Financial and Dongbang Ship
-0.25 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Incar and Dongbang is -0.25. Overlapping area represents the amount of risk that can be diversified away by holding Incar Financial Service and Dongbang Ship Machinery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dongbang Ship Machinery and Incar Financial 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 Incar Financial Service are associated (or correlated) with Dongbang Ship. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dongbang Ship Machinery has no effect on the direction of Incar Financial i.e., Incar Financial and Dongbang Ship go up and down completely randomly.
Pair Corralation between Incar Financial and Dongbang Ship
Assuming the 90 days trading horizon Incar Financial Service is expected to generate 1.07 times more return on investment than Dongbang Ship. However, Incar Financial is 1.07 times more volatile than Dongbang Ship Machinery. It trades about 0.13 of its potential returns per unit of risk. Dongbang Ship Machinery is currently generating about 0.13 per unit of risk. If you would invest 561,000 in Incar Financial Service on October 31, 2024 and sell it today you would earn a total of 33,000 from holding Incar Financial Service or generate 5.88% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Incar Financial Service vs. Dongbang Ship Machinery
Performance |
Timeline |
Incar Financial Service |
Dongbang Ship Machinery |
Incar Financial and Dongbang Ship Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Incar Financial and Dongbang Ship
The main advantage of trading using opposite Incar Financial and Dongbang Ship positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Incar Financial position performs unexpectedly, Dongbang Ship 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 Dongbang Ship will offset losses from the drop in Dongbang Ship's long position.Incar Financial vs. KakaoBank Corp | Incar Financial vs. Hyundai Industrial Co | Incar Financial vs. Jb Financial | Incar Financial vs. Daesung Industrial 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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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