Correlation Between Symtek Automation and Chung Hsin
Can any of the company-specific risk be diversified away by investing in both Symtek Automation and Chung Hsin 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 Symtek Automation and Chung Hsin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Symtek Automation Asia and Chung Hsin Electric Machinery, you can compare the effects of market volatilities on Symtek Automation and Chung Hsin 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 Symtek Automation with a short position of Chung Hsin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Symtek Automation and Chung Hsin.
Diversification Opportunities for Symtek Automation and Chung Hsin
-0.54 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Symtek and Chung is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Symtek Automation Asia and Chung Hsin Electric Machinery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chung Hsin Electric and Symtek Automation 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 Symtek Automation Asia are associated (or correlated) with Chung Hsin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chung Hsin Electric has no effect on the direction of Symtek Automation i.e., Symtek Automation and Chung Hsin go up and down completely randomly.
Pair Corralation between Symtek Automation and Chung Hsin
Assuming the 90 days trading horizon Symtek Automation Asia is expected to generate 0.99 times more return on investment than Chung Hsin. However, Symtek Automation Asia is 1.02 times less risky than Chung Hsin. It trades about 0.11 of its potential returns per unit of risk. Chung Hsin Electric Machinery is currently generating about 0.05 per unit of risk. If you would invest 9,979 in Symtek Automation Asia on September 20, 2024 and sell it today you would earn a total of 9,521 from holding Symtek Automation Asia or generate 95.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Symtek Automation Asia vs. Chung Hsin Electric Machinery
Performance |
Timeline |
Symtek Automation Asia |
Chung Hsin Electric |
Symtek Automation and Chung Hsin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Symtek Automation and Chung Hsin
The main advantage of trading using opposite Symtek Automation and Chung Hsin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Symtek Automation position performs unexpectedly, Chung Hsin 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 Hsin will offset losses from the drop in Chung Hsin's long position.Symtek Automation vs. Ruentex Development Co | Symtek Automation vs. WiseChip Semiconductor | Symtek Automation vs. Novatek Microelectronics Corp | Symtek Automation vs. Leader Electronics |
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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