Correlation Between Bank of Queensland and Aurelia Metals
Can any of the company-specific risk be diversified away by investing in both Bank of Queensland and Aurelia Metals 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 Bank of Queensland and Aurelia Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bank of Queensland and Aurelia Metals, you can compare the effects of market volatilities on Bank of Queensland and Aurelia Metals 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 Bank of Queensland with a short position of Aurelia Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of Queensland and Aurelia Metals.
Diversification Opportunities for Bank of Queensland and Aurelia Metals
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Bank and Aurelia is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Bank of Queensland and Aurelia Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aurelia Metals and Bank of Queensland 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 Bank of Queensland are associated (or correlated) with Aurelia Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aurelia Metals has no effect on the direction of Bank of Queensland i.e., Bank of Queensland and Aurelia Metals go up and down completely randomly.
Pair Corralation between Bank of Queensland and Aurelia Metals
Assuming the 90 days trading horizon Bank of Queensland is expected to generate 10.56 times less return on investment than Aurelia Metals. But when comparing it to its historical volatility, Bank of Queensland is 11.49 times less risky than Aurelia Metals. It trades about 0.07 of its potential returns per unit of risk. Aurelia Metals is currently generating about 0.07 of returns per unit of risk over similar time horizon. If you would invest 9.20 in Aurelia Metals on September 26, 2024 and sell it today you would earn a total of 7.80 from holding Aurelia Metals or generate 84.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Bank of Queensland vs. Aurelia Metals
Performance |
Timeline |
Bank of Queensland |
Aurelia Metals |
Bank of Queensland and Aurelia Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of Queensland and Aurelia Metals
The main advantage of trading using opposite Bank of Queensland and Aurelia Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of Queensland position performs unexpectedly, Aurelia Metals 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 Aurelia Metals will offset losses from the drop in Aurelia Metals' long position.Bank of Queensland vs. Mystate | Bank of Queensland vs. LGI | Bank of Queensland vs. Supply Network | Bank of Queensland vs. Arrow Minerals |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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