Correlation Between Shieh Yih and Cayman Tung
Can any of the company-specific risk be diversified away by investing in both Shieh Yih and Cayman Tung 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 Shieh Yih and Cayman Tung into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shieh Yih Machinery and Cayman Tung Ling, you can compare the effects of market volatilities on Shieh Yih and Cayman Tung 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 Shieh Yih with a short position of Cayman Tung. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shieh Yih and Cayman Tung.
Diversification Opportunities for Shieh Yih and Cayman Tung
0.37 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Shieh and Cayman is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding Shieh Yih Machinery and Cayman Tung Ling in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cayman Tung Ling and Shieh Yih 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 Shieh Yih Machinery are associated (or correlated) with Cayman Tung. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cayman Tung Ling has no effect on the direction of Shieh Yih i.e., Shieh Yih and Cayman Tung go up and down completely randomly.
Pair Corralation between Shieh Yih and Cayman Tung
Assuming the 90 days trading horizon Shieh Yih Machinery is expected to generate 1.15 times more return on investment than Cayman Tung. However, Shieh Yih is 1.15 times more volatile than Cayman Tung Ling. It trades about 0.04 of its potential returns per unit of risk. Cayman Tung Ling is currently generating about 0.03 per unit of risk. If you would invest 2,871 in Shieh Yih Machinery on August 28, 2024 and sell it today you would earn a total of 944.00 from holding Shieh Yih Machinery or generate 32.88% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 99.71% |
| Values | Daily Returns |
Shieh Yih Machinery vs. Cayman Tung Ling
Performance |
| Timeline |
| Shieh Yih Machinery |
| Cayman Tung Ling |
Shieh Yih and Cayman Tung Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shieh Yih and Cayman Tung
The main advantage of trading using opposite Shieh Yih and Cayman Tung positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shieh Yih position performs unexpectedly, Cayman Tung 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 Cayman Tung will offset losses from the drop in Cayman Tung's long position.| Shieh Yih vs. Sunny Friend Environmental | Shieh Yih vs. TTET Union Corp | Shieh Yih vs. ECOVE Environment Corp | Shieh Yih vs. Yulon Finance Corp |
| Cayman Tung vs. Dynamic Medical Technologies | Cayman Tung vs. Louisa Professional Coffee | Cayman Tung vs. PlayNitride | Cayman Tung vs. Emerging Display Technologies |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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