Correlation Between YuantaP Shares and Abnova Taiwan
Can any of the company-specific risk be diversified away by investing in both YuantaP Shares and Abnova Taiwan 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 YuantaP Shares and Abnova Taiwan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between YuantaP shares Taiwan Mid Cap and Abnova Taiwan Corp, you can compare the effects of market volatilities on YuantaP Shares and Abnova Taiwan 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 YuantaP Shares with a short position of Abnova Taiwan. Check out your portfolio center. Please also check ongoing floating volatility patterns of YuantaP Shares and Abnova Taiwan.
Diversification Opportunities for YuantaP Shares and Abnova Taiwan
0.63 | Correlation Coefficient |
Poor diversification
The 3 months correlation between YuantaP and Abnova is 0.63. Overlapping area represents the amount of risk that can be diversified away by holding YuantaP shares Taiwan Mid Cap and Abnova Taiwan Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Abnova Taiwan Corp and YuantaP Shares 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 YuantaP shares Taiwan Mid Cap are associated (or correlated) with Abnova Taiwan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Abnova Taiwan Corp has no effect on the direction of YuantaP Shares i.e., YuantaP Shares and Abnova Taiwan go up and down completely randomly.
Pair Corralation between YuantaP Shares and Abnova Taiwan
Assuming the 90 days trading horizon YuantaP shares Taiwan Mid Cap is expected to generate 1.66 times more return on investment than Abnova Taiwan. However, YuantaP Shares is 1.66 times more volatile than Abnova Taiwan Corp. It trades about -0.08 of its potential returns per unit of risk. Abnova Taiwan Corp is currently generating about -0.21 per unit of risk. If you would invest 8,140 in YuantaP shares Taiwan Mid Cap on September 3, 2024 and sell it today you would lose (455.00) from holding YuantaP shares Taiwan Mid Cap or give up 5.59% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
YuantaP shares Taiwan Mid Cap vs. Abnova Taiwan Corp
Performance |
Timeline |
YuantaP shares Taiwan |
Abnova Taiwan Corp |
YuantaP Shares and Abnova Taiwan Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with YuantaP Shares and Abnova Taiwan
The main advantage of trading using opposite YuantaP Shares and Abnova Taiwan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if YuantaP Shares position performs unexpectedly, Abnova Taiwan 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 Abnova Taiwan will offset losses from the drop in Abnova Taiwan's long position.YuantaP Shares vs. Cathay Taiwan 5G | YuantaP Shares vs. Ruentex Development Co | YuantaP Shares vs. Symtek Automation Asia | YuantaP Shares vs. CTCI Corp |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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