Correlation Between Hyster-Yale Materials and TERADATA
Can any of the company-specific risk be diversified away by investing in both Hyster-Yale Materials and TERADATA 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 Hyster-Yale Materials and TERADATA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hyster Yale Materials Handling and TERADATA, you can compare the effects of market volatilities on Hyster-Yale Materials and TERADATA 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 Hyster-Yale Materials with a short position of TERADATA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hyster-Yale Materials and TERADATA.
Diversification Opportunities for Hyster-Yale Materials and TERADATA
0.45 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Hyster-Yale and TERADATA is 0.45. Overlapping area represents the amount of risk that can be diversified away by holding Hyster Yale Materials Handling and TERADATA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on TERADATA and Hyster-Yale Materials 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 Hyster Yale Materials Handling are associated (or correlated) with TERADATA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of TERADATA has no effect on the direction of Hyster-Yale Materials i.e., Hyster-Yale Materials and TERADATA go up and down completely randomly.
Pair Corralation between Hyster-Yale Materials and TERADATA
Assuming the 90 days trading horizon Hyster Yale Materials Handling is expected to under-perform the TERADATA. In addition to that, Hyster-Yale Materials is 2.11 times more volatile than TERADATA. It trades about -0.08 of its total potential returns per unit of risk. TERADATA is currently generating about -0.02 per unit of volatility. If you would invest 3,000 in TERADATA on August 31, 2024 and sell it today you would lose (40.00) from holding TERADATA or give up 1.33% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hyster Yale Materials Handling vs. TERADATA
Performance |
| Timeline |
| Hyster Yale Materials |
| TERADATA |
Hyster-Yale Materials and TERADATA Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hyster-Yale Materials and TERADATA
The main advantage of trading using opposite Hyster-Yale Materials and TERADATA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hyster-Yale Materials position performs unexpectedly, TERADATA 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 TERADATA will offset losses from the drop in TERADATA's long position.| Hyster-Yale Materials vs. Superior Plus Corp | Hyster-Yale Materials vs. NMI Holdings | Hyster-Yale Materials vs. Origin Agritech | Hyster-Yale Materials vs. SIVERS SEMICONDUCTORS AB |
| TERADATA vs. Hyster Yale Materials Handling | TERADATA vs. Martin Marietta Materials | TERADATA vs. Applied Materials | TERADATA vs. Sumitomo Rubber Industries |
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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