Correlation Between Synalloy and Hongli Group
Can any of the company-specific risk be diversified away by investing in both Synalloy 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 Synalloy and Hongli Group into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Synalloy and Hongli Group Ordinary, you can compare the effects of market volatilities on Synalloy 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 Synalloy with a short position of Hongli Group. Check out your portfolio center. Please also check ongoing floating volatility patterns of Synalloy and Hongli Group.
Diversification Opportunities for Synalloy and Hongli Group
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Synalloy and Hongli is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Synalloy 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 Synalloy 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 Synalloy 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 Synalloy i.e., Synalloy and Hongli Group go up and down completely randomly.
Pair Corralation between Synalloy and Hongli Group
Given the investment horizon of 90 days Synalloy is expected to generate 2.24 times less return on investment than Hongli Group. But when comparing it to its historical volatility, Synalloy is 2.46 times less risky than Hongli Group. It trades about 0.18 of its potential returns per unit of risk. Hongli Group Ordinary is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 92.00 in Hongli Group Ordinary on September 10, 2025 and sell it today you would earn a total of 47.00 from holding Hongli Group Ordinary or generate 51.09% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Synalloy vs. Hongli Group Ordinary
Performance |
| Timeline |
| Synalloy |
| Hongli Group Ordinary |
Synalloy and Hongli Group Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Synalloy and Hongli Group
The main advantage of trading using opposite Synalloy and Hongli Group positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Synalloy 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.| Synalloy vs. Hongli Group Ordinary | Synalloy vs. Westwater Resources | Synalloy vs. Nova Minerals Limited | Synalloy vs. Bioceres Crop Solutions |
| Hongli Group vs. Synalloy | Hongli Group vs. Flexible Solutions International | Hongli Group vs. Westwater Resources | Hongli Group vs. Bioceres Crop Solutions |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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