Correlation Between Fortescue and Qbe Insurance
Can any of the company-specific risk be diversified away by investing in both Fortescue and Qbe Insurance 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 Fortescue and Qbe Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fortescue and Qbe Insurance Group, you can compare the effects of market volatilities on Fortescue and Qbe Insurance 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 Fortescue with a short position of Qbe Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fortescue and Qbe Insurance.
Diversification Opportunities for Fortescue and Qbe Insurance
0.02 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Fortescue and Qbe is 0.02. Overlapping area represents the amount of risk that can be diversified away by holding Fortescue and Qbe Insurance Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Qbe Insurance Group and Fortescue 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 Fortescue are associated (or correlated) with Qbe Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Qbe Insurance Group has no effect on the direction of Fortescue i.e., Fortescue and Qbe Insurance go up and down completely randomly.
Pair Corralation between Fortescue and Qbe Insurance
Assuming the 90 days trading horizon Fortescue is expected to under-perform the Qbe Insurance. In addition to that, Fortescue is 1.28 times more volatile than Qbe Insurance Group. It trades about -0.01 of its total potential returns per unit of risk. Qbe Insurance Group is currently generating about 0.43 per unit of volatility. If you would invest 1,721 in Qbe Insurance Group on September 1, 2024 and sell it today you would earn a total of 279.00 from holding Qbe Insurance Group or generate 16.21% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fortescue vs. Qbe Insurance Group
Performance |
| Timeline |
| Fortescue |
| Qbe Insurance Group |
Fortescue and Qbe Insurance Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fortescue and Qbe Insurance
The main advantage of trading using opposite Fortescue and Qbe Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fortescue position performs unexpectedly, Qbe Insurance 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 Qbe Insurance will offset losses from the drop in Qbe Insurance's long position.| Fortescue vs. Capitol Health | Fortescue vs. Carawine Resources Limited | Fortescue vs. Event Hospitality and | Fortescue vs. Thorney Technologies |
| Qbe Insurance vs. Diversified United Investment | Qbe Insurance vs. Bank of Queensland | Qbe Insurance vs. Home Consortium | Qbe Insurance vs. Carlton Investments |
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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