Correlation Between Bank of Queensland and Macquarie Bank
Can any of the company-specific risk be diversified away by investing in both Bank of Queensland and Macquarie Bank 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 Macquarie Bank 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 Macquarie Bank Limited, you can compare the effects of market volatilities on Bank of Queensland and Macquarie Bank 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 Macquarie Bank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bank of Queensland and Macquarie Bank.
Diversification Opportunities for Bank of Queensland and Macquarie Bank
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Bank and Macquarie is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Bank of Queensland and Macquarie Bank Limited in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Macquarie Bank 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 Macquarie Bank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Macquarie Bank has no effect on the direction of Bank of Queensland i.e., Bank of Queensland and Macquarie Bank go up and down completely randomly.
Pair Corralation between Bank of Queensland and Macquarie Bank
Assuming the 90 days trading horizon Bank of Queensland is expected to generate 0.96 times more return on investment than Macquarie Bank. However, Bank of Queensland is 1.04 times less risky than Macquarie Bank. It trades about 0.08 of its potential returns per unit of risk. Macquarie Bank Limited is currently generating about 0.07 per unit of risk. If you would invest 9,578 in Bank of Queensland on August 29, 2024 and sell it today you would earn a total of 928.00 from holding Bank of Queensland or generate 9.69% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Bank of Queensland vs. Macquarie Bank Limited
Performance |
Timeline |
Bank of Queensland |
Macquarie Bank |
Bank of Queensland and Macquarie Bank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bank of Queensland and Macquarie Bank
The main advantage of trading using opposite Bank of Queensland and Macquarie Bank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bank of Queensland position performs unexpectedly, Macquarie Bank 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 Macquarie Bank will offset losses from the drop in Macquarie Bank's long position.Bank of Queensland vs. Champion Iron | Bank of Queensland vs. Ridley | Bank of Queensland vs. Peel Mining | Bank of Queensland vs. Australian Dairy Farms |
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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 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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