Correlation Between Macquarie Bank and Havilah Resources
Can any of the company-specific risk be diversified away by investing in both Macquarie Bank and Havilah Resources 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 Macquarie Bank and Havilah Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Macquarie Bank Limited and Havilah Resources, you can compare the effects of market volatilities on Macquarie Bank and Havilah Resources 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 Macquarie Bank with a short position of Havilah Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of Macquarie Bank and Havilah Resources.
Diversification Opportunities for Macquarie Bank and Havilah Resources
-0.56 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Macquarie and Havilah is -0.56. Overlapping area represents the amount of risk that can be diversified away by holding Macquarie Bank Limited and Havilah Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Havilah Resources and Macquarie Bank 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 Macquarie Bank Limited are associated (or correlated) with Havilah Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Havilah Resources has no effect on the direction of Macquarie Bank i.e., Macquarie Bank and Havilah Resources go up and down completely randomly.
Pair Corralation between Macquarie Bank and Havilah Resources
Assuming the 90 days trading horizon Macquarie Bank Limited is expected to generate 0.09 times more return on investment than Havilah Resources. However, Macquarie Bank Limited is 11.0 times less risky than Havilah Resources. It trades about 0.05 of its potential returns per unit of risk. Havilah Resources is currently generating about -0.04 per unit of risk. If you would invest 10,228 in Macquarie Bank Limited on December 25, 2024 and sell it today you would earn a total of 75.00 from holding Macquarie Bank Limited or generate 0.73% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Macquarie Bank Limited vs. Havilah Resources
Performance |
Timeline |
Macquarie Bank |
Havilah Resources |
Macquarie Bank and Havilah Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Macquarie Bank and Havilah Resources
The main advantage of trading using opposite Macquarie Bank and Havilah Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Macquarie Bank position performs unexpectedly, Havilah Resources 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 Havilah Resources will offset losses from the drop in Havilah Resources' long position.Macquarie Bank vs. Aneka Tambang Tbk | Macquarie Bank vs. BHP Group Limited | Macquarie Bank vs. Commonwealth Bank | Macquarie Bank vs. Commonwealth Bank of |
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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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