Correlation Between Cleveland Cliffs and Hongli Group
Can any of the company-specific risk be diversified away by investing in both Cleveland Cliffs and Hongli Group 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 Cleveland Cliffs and Hongli Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Cleveland Cliffs and Hongli Group Ordinary, you can compare the effects of market volatilities on Cleveland Cliffs and Hongli Group 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 Cleveland Cliffs with a short position of Hongli Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Cleveland Cliffs and Hongli Group.
Diversification Opportunities for Cleveland Cliffs and Hongli Group
-0.55 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Cleveland and Hongli is -0.55. Overlapping area represents the amount of risk that can be diversified away by holding Cleveland Cliffs and Hongli Group Ordinary in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hongli Group Ordinary and Cleveland Cliffs 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 Cleveland Cliffs are associated (or correlated) with Hongli Group. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hongli Group Ordinary has no effect on the direction of Cleveland Cliffs i.e., Cleveland Cliffs and Hongli Group go up and down completely randomly.
Pair Corralation between Cleveland Cliffs and Hongli Group
Considering the 90-day investment horizon Cleveland Cliffs is expected to generate 0.53 times more return on investment than Hongli Group. However, Cleveland Cliffs is 1.9 times less risky than Hongli Group. It trades about 0.19 of its potential returns per unit of risk. Hongli Group Ordinary is currently generating about -0.01 per unit of risk. If you would invest 940.00 in Cleveland Cliffs on November 1, 2024 and sell it today you would earn a total of 83.00 from holding Cleveland Cliffs or generate 8.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Cleveland Cliffs vs. Hongli Group Ordinary
Performance |
Timeline |
Cleveland Cliffs |
Hongli Group Ordinary |
Cleveland Cliffs and Hongli Group Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Cleveland Cliffs and Hongli Group
The main advantage of trading using opposite Cleveland Cliffs and Hongli Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Cleveland Cliffs position performs unexpectedly, Hongli Group 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 Hongli Group will offset losses from the drop in Hongli Group's long position.Cleveland Cliffs vs. Nucor Corp | Cleveland Cliffs vs. Steel Dynamics | Cleveland Cliffs vs. ArcelorMittal SA ADR | Cleveland Cliffs vs. Gerdau SA ADR |
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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 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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