Correlation Between Chung Hung and Hsin Kuang
Can any of the company-specific risk be diversified away by investing in both Chung Hung and Hsin Kuang 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 Chung Hung and Hsin Kuang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Chung Hung Steel and Hsin Kuang Steel, you can compare the effects of market volatilities on Chung Hung and Hsin Kuang 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 Chung Hung with a short position of Hsin Kuang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chung Hung and Hsin Kuang.
Diversification Opportunities for Chung Hung and Hsin Kuang
0.32 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Chung and Hsin is 0.32. Overlapping area represents the amount of risk that can be diversified away by holding Chung Hung Steel and Hsin Kuang Steel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hsin Kuang Steel and Chung Hung 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 Chung Hung Steel are associated (or correlated) with Hsin Kuang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hsin Kuang Steel has no effect on the direction of Chung Hung i.e., Chung Hung and Hsin Kuang go up and down completely randomly.
Pair Corralation between Chung Hung and Hsin Kuang
Assuming the 90 days trading horizon Chung Hung Steel is expected to under-perform the Hsin Kuang. But the stock apears to be less risky and, when comparing its historical volatility, Chung Hung Steel is 1.02 times less risky than Hsin Kuang. The stock trades about -0.06 of its potential returns per unit of risk. The Hsin Kuang Steel is currently generating about -0.03 of returns per unit of risk over similar time horizon. If you would invest 5,800 in Hsin Kuang Steel on September 13, 2024 and sell it today you would lose (990.00) from holding Hsin Kuang Steel or give up 17.07% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Chung Hung Steel vs. Hsin Kuang Steel
Performance |
Timeline |
Chung Hung Steel |
Hsin Kuang Steel |
Chung Hung and Hsin Kuang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Chung Hung and Hsin Kuang
The main advantage of trading using opposite Chung Hung and Hsin Kuang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chung Hung position performs unexpectedly, Hsin Kuang 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 Kuang will offset losses from the drop in Hsin Kuang's long position.Chung Hung vs. Tainan Spinning Co | Chung Hung vs. Lealea Enterprise Co | Chung Hung vs. China Petrochemical Development | Chung Hung vs. Ruentex Development Co |
Hsin Kuang vs. Chung Hung Steel | Hsin Kuang vs. Tung Ho Steel | Hsin Kuang vs. Ta Chen Stainless | Hsin Kuang vs. Feng Hsin Steel |
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 Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
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