Correlation Between Nankang Rubber and Hsin Yung
Can any of the company-specific risk be diversified away by investing in both Nankang Rubber and Hsin Yung 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 Nankang Rubber and Hsin Yung into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nankang Rubber Tire and Hsin Yung Chien, you can compare the effects of market volatilities on Nankang Rubber and Hsin Yung 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 Nankang Rubber with a short position of Hsin Yung. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nankang Rubber and Hsin Yung.
Diversification Opportunities for Nankang Rubber and Hsin Yung
0.49 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Nankang and Hsin is 0.49. Overlapping area represents the amount of risk that can be diversified away by holding Nankang Rubber Tire and Hsin Yung Chien in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hsin Yung Chien and Nankang Rubber 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 Nankang Rubber Tire are associated (or correlated) with Hsin Yung. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hsin Yung Chien has no effect on the direction of Nankang Rubber i.e., Nankang Rubber and Hsin Yung go up and down completely randomly.
Pair Corralation between Nankang Rubber and Hsin Yung
Assuming the 90 days trading horizon Nankang Rubber Tire is expected to under-perform the Hsin Yung. In addition to that, Nankang Rubber is 2.88 times more volatile than Hsin Yung Chien. It trades about -0.07 of its total potential returns per unit of risk. Hsin Yung Chien is currently generating about -0.08 per unit of volatility. If you would invest 9,850 in Hsin Yung Chien on October 3, 2024 and sell it today you would lose (450.00) from holding Hsin Yung Chien or give up 4.57% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Nankang Rubber Tire vs. Hsin Yung Chien
Performance |
Timeline |
Nankang Rubber Tire |
Hsin Yung Chien |
Nankang Rubber and Hsin Yung Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Nankang Rubber and Hsin Yung
The main advantage of trading using opposite Nankang Rubber and Hsin Yung positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nankang Rubber position performs unexpectedly, Hsin Yung 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 Hsin Yung will offset losses from the drop in Hsin Yung's long position.Nankang Rubber vs. Ruentex Development Co | Nankang Rubber vs. Symtek Automation Asia | Nankang Rubber vs. WiseChip Semiconductor | Nankang Rubber vs. Novatek Microelectronics Corp |
Hsin Yung vs. Cleanaway Co | Hsin Yung vs. Nak Sealing Technologies | Hsin Yung vs. Yulon Finance Corp | Hsin Yung vs. China Steel Chemical |
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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