Correlation Between ALGOMA STEEL and Hyster Yale
Can any of the company-specific risk be diversified away by investing in both ALGOMA STEEL 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 ALGOMA STEEL and Hyster Yale into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ALGOMA STEEL GROUP and Hyster Yale Materials Handling, you can compare the effects of market volatilities on ALGOMA STEEL 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 ALGOMA STEEL with a short position of Hyster Yale. Check out your portfolio center. Please also check ongoing floating volatility patterns of ALGOMA STEEL and Hyster Yale.
Diversification Opportunities for ALGOMA STEEL and Hyster Yale
-0.57 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between ALGOMA and Hyster is -0.57. Overlapping area represents the amount of risk that can be diversified away by holding ALGOMA STEEL GROUP 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 ALGOMA STEEL 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 ALGOMA STEEL GROUP 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 ALGOMA STEEL i.e., ALGOMA STEEL and Hyster Yale go up and down completely randomly.
Pair Corralation between ALGOMA STEEL and Hyster Yale
Assuming the 90 days horizon ALGOMA STEEL is expected to generate 1.29 times less return on investment than Hyster Yale. But when comparing it to its historical volatility, ALGOMA STEEL GROUP is 1.33 times less risky than Hyster Yale. It trades about 0.06 of its potential returns per unit of risk. Hyster Yale Materials Handling is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 2,550 in Hyster Yale Materials Handling on September 29, 2024 and sell it today you would earn a total of 2,230 from holding Hyster Yale Materials Handling or generate 87.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
ALGOMA STEEL GROUP vs. Hyster Yale Materials Handling
Performance |
Timeline |
ALGOMA STEEL GROUP |
Hyster Yale Materials |
ALGOMA STEEL and Hyster Yale Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with ALGOMA STEEL and Hyster Yale
The main advantage of trading using opposite ALGOMA STEEL and Hyster Yale positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ALGOMA STEEL 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.ALGOMA STEEL vs. ArcelorMittal SA | ALGOMA STEEL vs. ArcelorMittal | ALGOMA STEEL vs. Steel Dynamics | ALGOMA STEEL vs. Nippon Steel |
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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 Analyzer module to portfolio analysis module that provides access to portfolio diagnostics and optimization engine.
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