Correlation Between Nishoku Technology and Yang Ming
Can any of the company-specific risk be diversified away by investing in both Nishoku Technology and Yang Ming 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 Nishoku Technology and Yang Ming into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nishoku Technology and Yang Ming Marine, you can compare the effects of market volatilities on Nishoku Technology and Yang Ming 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 Nishoku Technology with a short position of Yang Ming. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nishoku Technology and Yang Ming.
Diversification Opportunities for Nishoku Technology and Yang Ming
-0.18 | Correlation Coefficient |
Good diversification
The 3 months correlation between Nishoku and Yang is -0.18. Overlapping area represents the amount of risk that can be diversified away by holding Nishoku Technology and Yang Ming Marine in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Yang Ming Marine and Nishoku Technology 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 Nishoku Technology are associated (or correlated) with Yang Ming. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Yang Ming Marine has no effect on the direction of Nishoku Technology i.e., Nishoku Technology and Yang Ming go up and down completely randomly.
Pair Corralation between Nishoku Technology and Yang Ming
Assuming the 90 days trading horizon Nishoku Technology is expected to generate 0.96 times more return on investment than Yang Ming. However, Nishoku Technology is 1.05 times less risky than Yang Ming. It trades about 0.13 of its potential returns per unit of risk. Yang Ming Marine is currently generating about 0.02 per unit of risk. If you would invest 13,150 in Nishoku Technology on December 27, 2024 and sell it today you would earn a total of 1,550 from holding Nishoku Technology or generate 11.79% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Nishoku Technology vs. Yang Ming Marine
Performance |
Timeline |
Nishoku Technology |
Risk-Adjusted Performance
OK
Weak | Strong |
Yang Ming Marine |
Nishoku Technology and Yang Ming Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Nishoku Technology and Yang Ming
The main advantage of trading using opposite Nishoku Technology and Yang Ming positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nishoku Technology position performs unexpectedly, Yang Ming 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 Yang Ming will offset losses from the drop in Yang Ming's long position.Nishoku Technology vs. Shin Zu Shing | Nishoku Technology vs. Arcadyan Technology Corp | Nishoku Technology vs. Tripod Technology Corp | Nishoku Technology vs. Lotes 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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