Correlation Between Chung Hsin and Chung Hung
Can any of the company-specific risk be diversified away by investing in both Chung Hsin and Chung Hung 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 Hsin and Chung Hung into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Chung Hsin Electric Machinery and Chung Hung Steel, you can compare the effects of market volatilities on Chung Hsin and Chung Hung 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 Hsin with a short position of Chung Hung. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chung Hsin and Chung Hung.
Diversification Opportunities for Chung Hsin and Chung Hung
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Chung and Chung is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Chung Hsin Electric Machinery and Chung Hung Steel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chung Hung Steel and Chung Hsin 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 Hsin Electric Machinery are associated (or correlated) with Chung Hung. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chung Hung Steel has no effect on the direction of Chung Hsin i.e., Chung Hsin and Chung Hung go up and down completely randomly.
Pair Corralation between Chung Hsin and Chung Hung
Assuming the 90 days trading horizon Chung Hsin Electric Machinery is expected to generate 0.84 times more return on investment than Chung Hung. However, Chung Hsin Electric Machinery is 1.2 times less risky than Chung Hung. It trades about -0.01 of its potential returns per unit of risk. Chung Hung Steel is currently generating about -0.39 per unit of risk. If you would invest 15,950 in Chung Hsin Electric Machinery on October 10, 2024 and sell it today you would lose (50.00) from holding Chung Hsin Electric Machinery or give up 0.31% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Chung Hsin Electric Machinery vs. Chung Hung Steel
Performance |
Timeline |
Chung Hsin Electric |
Chung Hung Steel |
Chung Hsin and Chung Hung Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Chung Hsin and Chung Hung
The main advantage of trading using opposite Chung Hsin and Chung Hung positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chung Hsin position performs unexpectedly, Chung Hung 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 Chung Hung will offset losses from the drop in Chung Hung's long position.Chung Hsin vs. TECO Electric Machinery | Chung Hsin vs. Fortune Electric Co | Chung Hsin vs. Taiwan Cement Corp | Chung Hsin vs. Walsin Lihwa Corp |
Chung Hung vs. China Steel Corp | Chung Hung vs. Yieh Phui Enterprise | Chung Hung vs. Ta Chen Stainless | Chung Hung vs. Yang Ming Marine |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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