Correlation Between Chung Hsin and Chen Full
Can any of the company-specific risk be diversified away by investing in both Chung Hsin and Chen Full 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 Chen Full 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 Chen Full International, you can compare the effects of market volatilities on Chung Hsin and Chen Full 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 Chen Full. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chung Hsin and Chen Full.
Diversification Opportunities for Chung Hsin and Chen Full
-0.15 | Correlation Coefficient |
Good diversification
The 3 months correlation between Chung and Chen is -0.15. Overlapping area represents the amount of risk that can be diversified away by holding Chung Hsin Electric Machinery and Chen Full International in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chen Full International 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 Chen Full. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chen Full International has no effect on the direction of Chung Hsin i.e., Chung Hsin and Chen Full go up and down completely randomly.
Pair Corralation between Chung Hsin and Chen Full
Assuming the 90 days trading horizon Chung Hsin Electric Machinery is expected to under-perform the Chen Full. In addition to that, Chung Hsin is 1.02 times more volatile than Chen Full International. It trades about -0.03 of its total potential returns per unit of risk. Chen Full International is currently generating about 0.2 per unit of volatility. If you would invest 4,335 in Chen Full International on December 21, 2024 and sell it today you would earn a total of 865.00 from holding Chen Full International or generate 19.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Chung Hsin Electric Machinery vs. Chen Full International
Performance |
Timeline |
Chung Hsin Electric |
Chen Full International |
Chung Hsin and Chen Full Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Chung Hsin and Chen Full
The main advantage of trading using opposite Chung Hsin and Chen Full positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chung Hsin position performs unexpectedly, Chen Full 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 Chen Full will offset losses from the drop in Chen Full'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 |
Chen Full vs. China Steel Chemical | Chen Full vs. Taiwan Secom Co | Chen Full vs. Taiwan Hon Chuan | Chen Full vs. China Ecotek Corp |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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