Correlation Between QBE Insurance and Sealed Air
Can any of the company-specific risk be diversified away by investing in both QBE Insurance and Sealed Air 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 QBE Insurance and Sealed Air into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between QBE Insurance Group and Sealed Air, you can compare the effects of market volatilities on QBE Insurance and Sealed Air 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 QBE Insurance with a short position of Sealed Air. Check out your portfolio center. Please also check ongoing floating volatility patterns of QBE Insurance and Sealed Air.
Diversification Opportunities for QBE Insurance and Sealed Air
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between QBE and Sealed is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding QBE Insurance Group and Sealed Air in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sealed Air and QBE Insurance 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 QBE Insurance Group are associated (or correlated) with Sealed Air. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sealed Air has no effect on the direction of QBE Insurance i.e., QBE Insurance and Sealed Air go up and down completely randomly.
Pair Corralation between QBE Insurance and Sealed Air
Assuming the 90 days horizon QBE Insurance is expected to generate 785.0 times less return on investment than Sealed Air. In addition to that, QBE Insurance is 1.13 times more volatile than Sealed Air. It trades about 0.0 of its total potential returns per unit of risk. Sealed Air is currently generating about 0.04 per unit of volatility. If you would invest 3,299 in Sealed Air on September 3, 2024 and sell it today you would earn a total of 361.00 from holding Sealed Air or generate 10.94% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
QBE Insurance Group vs. Sealed Air
Performance |
| Timeline |
| QBE Insurance Group |
| Sealed Air |
QBE Insurance and Sealed Air Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with QBE Insurance and Sealed Air
The main advantage of trading using opposite QBE Insurance and Sealed Air positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if QBE Insurance position performs unexpectedly, Sealed Air 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 Sealed Air will offset losses from the drop in Sealed Air's long position.| QBE Insurance vs. AmTrust Financial Services | QBE Insurance vs. AmTrust Financial Services | QBE Insurance vs. AmTrust Financial Services | QBE Insurance vs. AmTrust Financial Services |
| Sealed Air vs. Avery Dennison Corp | Sealed Air vs. International Paper | Sealed Air vs. Sonoco Products | Sealed Air vs. Packaging Corp of |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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