Correlation Between Yang Ming and Kingcan Holdings
Can any of the company-specific risk be diversified away by investing in both Yang Ming and Kingcan Holdings 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 Yang Ming and Kingcan Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Yang Ming Marine and Kingcan Holdings, you can compare the effects of market volatilities on Yang Ming and Kingcan Holdings 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 Yang Ming with a short position of Kingcan Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Yang Ming and Kingcan Holdings.
Diversification Opportunities for Yang Ming and Kingcan Holdings
-0.39 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Yang and Kingcan is -0.39. Overlapping area represents the amount of risk that can be diversified away by holding Yang Ming Marine and Kingcan Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kingcan Holdings and Yang Ming 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 Yang Ming Marine are associated (or correlated) with Kingcan Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kingcan Holdings has no effect on the direction of Yang Ming i.e., Yang Ming and Kingcan Holdings go up and down completely randomly.
Pair Corralation between Yang Ming and Kingcan Holdings
Assuming the 90 days trading horizon Yang Ming Marine is expected to generate 2.77 times more return on investment than Kingcan Holdings. However, Yang Ming is 2.77 times more volatile than Kingcan Holdings. It trades about 0.37 of its potential returns per unit of risk. Kingcan Holdings is currently generating about 0.17 per unit of risk. If you would invest 6,610 in Yang Ming Marine on November 27, 2024 and sell it today you would earn a total of 630.00 from holding Yang Ming Marine or generate 9.53% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Yang Ming Marine vs. Kingcan Holdings
Performance |
| Timeline |
| Yang Ming Marine |
| Kingcan Holdings |
Yang Ming and Kingcan Holdings Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Yang Ming and Kingcan Holdings
The main advantage of trading using opposite Yang Ming and Kingcan Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Yang Ming position performs unexpectedly, Kingcan Holdings 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 Kingcan Holdings will offset losses from the drop in Kingcan Holdings' long position.| Yang Ming vs. Evergreen Marine Corp | Yang Ming vs. Wan Hai Lines | Yang Ming vs. China Airlines | Yang Ming vs. Eva Airways Corp |
| Kingcan Holdings vs. Jinli Group Holdings | Kingcan Holdings vs. Shinih Enterprise Co | Kingcan Holdings vs. Super Dragon Technology | Kingcan Holdings vs. Shui Mu International Co |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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