Correlation Between Qbe Insurance and Champion Iron
Can any of the company-specific risk be diversified away by investing in both Qbe Insurance and Champion Iron 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 Champion Iron 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 Champion Iron, you can compare the effects of market volatilities on Qbe Insurance and Champion Iron 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 Champion Iron. Check out your portfolio center. Please also check ongoing floating volatility patterns of Qbe Insurance and Champion Iron.
Diversification Opportunities for Qbe Insurance and Champion Iron
-0.71 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Qbe and Champion is -0.71. Overlapping area represents the amount of risk that can be diversified away by holding Qbe Insurance Group and Champion Iron in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Champion Iron 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 Champion Iron. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Champion Iron has no effect on the direction of Qbe Insurance i.e., Qbe Insurance and Champion Iron go up and down completely randomly.
Pair Corralation between Qbe Insurance and Champion Iron
Assuming the 90 days trading horizon Qbe Insurance Group is expected to generate 0.6 times more return on investment than Champion Iron. However, Qbe Insurance Group is 1.68 times less risky than Champion Iron. It trades about 0.22 of its potential returns per unit of risk. Champion Iron is currently generating about -0.12 per unit of risk. If you would invest 1,628 in Qbe Insurance Group on October 1, 2024 and sell it today you would earn a total of 319.00 from holding Qbe Insurance Group or generate 19.59% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Qbe Insurance Group vs. Champion Iron
Performance |
Timeline |
Qbe Insurance Group |
Champion Iron |
Qbe Insurance and Champion Iron Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Qbe Insurance and Champion Iron
The main advantage of trading using opposite Qbe Insurance and Champion Iron positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Qbe Insurance position performs unexpectedly, Champion Iron 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 Champion Iron will offset losses from the drop in Champion Iron's long position.Qbe Insurance vs. Hotel Property Investments | Qbe Insurance vs. Commonwealth Bank of | Qbe Insurance vs. COG Financial Services | Qbe Insurance vs. Magellan Financial Group |
Champion Iron vs. Qbe Insurance Group | Champion Iron vs. Clime Investment Management | Champion Iron vs. Gold Road Resources | Champion Iron vs. Sky Metals |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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