Correlation Between China Datang and Hyster Yale
Can any of the company-specific risk be diversified away by investing in both China Datang and Hyster Yale 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 China Datang and Hyster Yale into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Datang and Hyster Yale Materials Handling, you can compare the effects of market volatilities on China Datang and Hyster Yale 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 China Datang with a short position of Hyster Yale. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Datang and Hyster Yale.
Diversification Opportunities for China Datang and Hyster Yale
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between China and Hyster is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding China Datang and Hyster Yale Materials Handling in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hyster Yale Materials and China Datang 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 China Datang are associated (or correlated) with Hyster Yale. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hyster Yale Materials has no effect on the direction of China Datang i.e., China Datang and Hyster Yale go up and down completely randomly.
Pair Corralation between China Datang and Hyster Yale
Assuming the 90 days horizon China Datang is expected to generate 0.95 times more return on investment than Hyster Yale. However, China Datang is 1.06 times less risky than Hyster Yale. It trades about 0.12 of its potential returns per unit of risk. Hyster Yale Materials Handling is currently generating about -0.12 per unit of risk. If you would invest 21.00 in China Datang on September 13, 2024 and sell it today you would earn a total of 3.00 from holding China Datang or generate 14.29% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
China Datang vs. Hyster Yale Materials Handling
Performance |
| Timeline |
| China Datang |
| Hyster Yale Materials |
China Datang and Hyster Yale Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with China Datang and Hyster Yale
The main advantage of trading using opposite China Datang and Hyster Yale positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Datang position performs unexpectedly, Hyster Yale 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 Hyster Yale will offset losses from the drop in Hyster Yale's long position.| China Datang vs. FANDIFI TECHNOLOGY P | China Datang vs. Check Point Software | China Datang vs. Singapore Telecommunications Limited | China Datang vs. PKSHA TECHNOLOGY INC |
| Hyster Yale vs. OURGAME INTHOLDL 00005 | Hyster Yale vs. Media and Games | Hyster Yale vs. American Eagle Outfitters | Hyster Yale vs. GigaMedia |
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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.
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