Correlation Between Huang Hsiang and China Times
Can any of the company-specific risk be diversified away by investing in both Huang Hsiang and China Times 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 Huang Hsiang and China Times into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Huang Hsiang Construction and China Times Publishing, you can compare the effects of market volatilities on Huang Hsiang and China Times 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 Huang Hsiang with a short position of China Times. Check out your portfolio center. Please also check ongoing floating volatility patterns of Huang Hsiang and China Times.
Diversification Opportunities for Huang Hsiang and China Times
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Huang and China is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding Huang Hsiang Construction and China Times Publishing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Times Publishing and Huang Hsiang 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 Huang Hsiang Construction are associated (or correlated) with China Times. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Times Publishing has no effect on the direction of Huang Hsiang i.e., Huang Hsiang and China Times go up and down completely randomly.
Pair Corralation between Huang Hsiang and China Times
Assuming the 90 days trading horizon Huang Hsiang is expected to generate 93.11 times less return on investment than China Times. But when comparing it to its historical volatility, Huang Hsiang Construction is 1.14 times less risky than China Times. It trades about 0.0 of its potential returns per unit of risk. China Times Publishing is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 1,780 in China Times Publishing on September 13, 2024 and sell it today you would earn a total of 180.00 from holding China Times Publishing or generate 10.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Huang Hsiang Construction vs. China Times Publishing
Performance |
Timeline |
Huang Hsiang Construction |
China Times Publishing |
Huang Hsiang and China Times Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Huang Hsiang and China Times
The main advantage of trading using opposite Huang Hsiang and China Times positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Huang Hsiang position performs unexpectedly, China Times 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 China Times will offset losses from the drop in China Times' long position.Huang Hsiang vs. Chong Hong Construction | Huang Hsiang vs. Ruentex Development Co | Huang Hsiang vs. Symtek Automation Asia | Huang Hsiang vs. WiseChip Semiconductor |
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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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