Correlation Between Chun Yuan and PChome Online
Can any of the company-specific risk be diversified away by investing in both Chun Yuan and PChome Online 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 Chun Yuan and PChome Online into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Chun Yuan Steel and PChome Online, you can compare the effects of market volatilities on Chun Yuan and PChome Online 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 Chun Yuan with a short position of PChome Online. Check out your portfolio center. Please also check ongoing floating volatility patterns of Chun Yuan and PChome Online.
Diversification Opportunities for Chun Yuan and PChome Online
0.29 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Chun and PChome is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding Chun Yuan Steel and PChome Online in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PChome Online and Chun Yuan 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 Chun Yuan Steel are associated (or correlated) with PChome Online. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PChome Online has no effect on the direction of Chun Yuan i.e., Chun Yuan and PChome Online go up and down completely randomly.
Pair Corralation between Chun Yuan and PChome Online
Assuming the 90 days trading horizon Chun Yuan is expected to generate 6.64 times less return on investment than PChome Online. But when comparing it to its historical volatility, Chun Yuan Steel is 4.74 times less risky than PChome Online. It trades about 0.06 of its potential returns per unit of risk. PChome Online is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 4,855 in PChome Online on September 1, 2024 and sell it today you would earn a total of 345.00 from holding PChome Online or generate 7.11% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Chun Yuan Steel vs. PChome Online
Performance |
| Timeline |
| Chun Yuan Steel |
| PChome Online |
Chun Yuan and PChome Online Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Chun Yuan and PChome Online
The main advantage of trading using opposite Chun Yuan and PChome Online positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Chun Yuan position performs unexpectedly, PChome Online 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 PChome Online will offset losses from the drop in PChome Online's long position.| Chun Yuan vs. Basso Industry Corp | Chun Yuan vs. Chung Hsin Electric Machinery | Chun Yuan vs. TYC Brother Industrial | Chun Yuan vs. TECO Electric Machinery |
| PChome Online vs. momo Inc | PChome Online vs. President Chain Store | PChome Online vs. Uni President Enterprises Corp | PChome Online vs. Taiwan FamilyMart Co |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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